a prometheus based monitoring #4
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WalkthroughThis pull request introduces significant architectural and functional improvements to the benchmark project. The changes span multiple domains, including dependency updates, CLI modifications, process management, metrics collection, and dashboard configurations. Key areas of focus include enhancing the modularity of database process management, improving error handling, adding Prometheus metrics support, and streamlining the benchmarking workflow. The modifications reflect a more robust and flexible approach to performance testing across different database systems. Changes
Sequence DiagramsequenceDiagram
participant CLI as Benchmark CLI
participant Scheduler as Message Scheduler
participant Worker as Parallel Workers
participant Database as Database System
participant Metrics as Prometheus Metrics
CLI->>Scheduler: Configure message rate
Scheduler->>Worker: Distribute queries
Worker->>Database: Execute queries
Database-->>Worker: Return results
Worker->>Metrics: Record performance metrics
Metrics-->>Scheduler: Update metrics
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Actionable comments posted: 13
🧹 Outside diff range and nitpick comments (15)
src/prometheus_endpoint.rs (6)
20-20: Make the listening address and port configurableThe server is currently bound to a hardcoded address
127.0.0.1:3000. Consider making the address and port configurable to allow flexibility in different deployment environments.Suggested change:
- let addr = SocketAddr::from(([127, 0, 0, 1], 3000)); + let addr = /* Retrieve address and port from configuration */;Adjust the
newmethod to accept parameters for the address and port or read from a configuration source.
61-61: Use appropriate logging levels for incoming requestsLogging incoming requests with
info!may lead to verbose logs in high-traffic scenarios. Consider using a lower logging level likedebug!ortrace!.Suggested change:
- info!("Metrics request received"); + debug!("Metrics request received");
28-29: Handle potential errors when awaiting shutdown signalThe
shutdown_rx.await.ok();line ignores any errors from the shutdown signal. While it's unlikely in this context, consider handling the potential error for completeness.Suggested change:
- shutdown_rx.await.ok(); + if let Err(e) = shutdown_rx.await { + error!("Shutdown signal error: {}", e); + }
5-5: Optimize imports by reusingtokio::sync::oneshotBoth line 5 and line 17 reference
tokio::sync::oneshot. Consider importing the module once to simplify the code.Suggested change to imports:
- use tokio::sync::oneshot::Sender; + use tokio::sync::oneshot;Update the code accordingly:
- let (shutdown_tx, shutdown_rx) = tokio::sync::oneshot::channel::<()>(); + let (shutdown_tx, shutdown_rx) = oneshot::channel::<()>();Also applies to: 17-17
22-24: Simplify service construction by removing unnecessary type annotationsThe
Ok::<_, hyper::Error>type annotation may not be necessary due to type inference. Simplify the code by removing it if possible.Suggested change:
- let make_svc = make_service_fn(|_conn| async { - Ok::<_, hyper::Error>(service_fn(metrics_handler)) - }); + let make_svc = make_service_fn(|_conn| async { + Ok(service_fn(metrics_handler)) + });Verify that the code compiles without the explicit type annotations.
30-30: Adjust logging to include proper contextIncluding context in log messages enhances debuggability. For example, specify that the server is the Prometheus metrics server.
Suggested change:
- info!("Listening on http://{}", addr); + info!("Prometheus metrics server listening on http://{}", addr);src/falkor.rs (4)
216-216: Avoid hardcoded connection informationThe
connection_infois hardcoded to"falkor://127.0.0.1:6379". To enhance flexibility and configurability, consider reading this value from an environment variable or a configuration file.Apply this diff to use an environment variable with a default fallback:
pub async fn client(&self) -> BenchmarkResult<FalkorBenchmarkClient> { - let connection_info = "falkor://127.0.0.1:6379".try_into()?; + let connection_str = env::var("FALKOR_CONNECTION").unwrap_or_else(|_| "falkor://127.0.0.1:6379".to_string()); + let connection_info = connection_str.try_into()?; let client = FalkorClientBuilder::new_async()This allows the connection information to be customized without code changes.
387-395: Remove commented-out logging codeThe logging code within the
execute_queriesmethod is commented out. If this logging is no longer needed, consider removing it to keep the codebase clean.Apply this diff to remove the commented code:
} - // info!( - // "executed: query_name={}, query_type={:?}, query:{} ", - // query_name, query_type, query - // ); }
398-410: Consider more detailed error logging inread_replyCurrently, the
read_replyfunction logs the error message without additional context. For better debugging, include more details such as the query that caused the error.Modify the error logging:
Err(e) => { tracing::Span::current().record("result", &"failure"); - error!("Error executing query: {}", e); + error!("Error executing query '{}': {}", query, e); }Note: This change requires passing the query string to
read_reply, so adjust the function signature accordingly.-fn read_reply<'a>(reply: FalkorResult<QueryResult<LazyResultSet<'a>>>) +fn read_reply<'a>(reply: FalkorResult<QueryResult<LazyResultSet<'a>>>, query: &'a str)And update the calls to
read_replyto include thequeryparameter.
215-224: Improve error handling when creating the clientIn the
clientmethod, errors fromtry_into()andawait?are propagated using the?operator. Ensure that these errors are properly handled or mapped to yourBenchmarkErrortype for consistent error reporting.Consider mapping errors to provide more context:
pub async fn client(&self) -> BenchmarkResult<FalkorBenchmarkClient> { - let connection_info = "falkor://127.0.0.1:6379".try_into()?; + let connection_info = "falkor://127.0.0.1:6379".try_into().map_err(|e| OtherError(e.to_string()))?; let client = FalkorClientBuilder::new_async() .with_connection_info(connection_info) .build() - .await?; + .await.map_err(|e| OtherError(e.to_string()))?; Ok(FalkorBenchmarkClient { graph: client.select_graph("falkor"), }) }src/main.rs (5)
132-132: Remove unnecessary explicit call todrop(prometheus_endpoint).In Rust, variables are automatically dropped when they go out of scope. The explicit call to
drop(prometheus_endpoint);is unnecessary and can be omitted for cleaner code.Apply this diff to remove the explicit drop:
-drop(prometheus_endpoint);
251-253: Use consistent logging for task failures.Instead of using
eprintln!, utilize theerror!macro from thetracingcrate for consistent logging across the application.Apply this diff to improve logging consistency:
match handle.await { Ok(result) => results.push(result), - Err(e) => eprintln!("Task failed: {:?}", e), + Err(e) => error!("Task failed: {:?}", e), }
233-237: Avoid unnecessary cloning of queries in the workers.Cloning the entire
queriesvector for each worker is inefficient. Since each worker now operates on a unique subset, cloning is no longer necessary.Apply this diff to remove redundant cloning:
let queries: Vec<(String, QueryType, String)> = queries_repository .random_queries(number_of_queries) .map(|(q_name, q_type, q)| (q_name, q_type, q.to_cypher())) .collect::<Vec<_>>(); -let queries = queries.clone();
232-238: Preallocate vector capacity for efficiency.When collecting queries into a vector, preallocating the capacity improves performance by reducing reallocations.
Apply this diff to preallocate capacity:
let mut queries = Vec::with_capacity(number_of_queries as usize); for (q_name, q_type, q) in queries_repository.random_queries(number_of_queries) { queries.push((q_name, q_type, q.to_cypher())); }
241-245: Simplify worker spawning without an additionalspawn_workerfunction.You can streamline the code by spawning tasks directly in the loop, eliminating the need for a separate
spawn_workerfunction.Apply this diff to simplify task spawning:
for spawn_id in 0..parallel { let chunk_size = (queries.len() + parallel - 1) / parallel; let start_idx = spawn_id * chunk_size; let end_idx = usize::min(start_idx + chunk_size, queries.len()); let queries_chunk = queries[start_idx..end_idx].to_vec(); - let handle = spawn_worker(&falkor, queries_chunk, spawn_id).await?; - handles.push(handle); + let mut graph = falkor.clone().client().await?; + let handle = tokio::spawn( + async move { + if let Err(e) = graph.execute_queries(queries_chunk).await { + error!("Worker {} encountered an error: {:?}", spawn_id, e); + } + } + .instrument(tracing::Span::current()), + ); + handles.push(handle); }
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📒 Files selected for processing (5)
Cargo.toml(1 hunks)src/cli.rs(1 hunks)src/falkor.rs(4 hunks)src/main.rs(9 hunks)src/prometheus_endpoint.rs(1 hunks)
🔇 Additional comments (4)
Cargo.toml (1)
42-44: LGTM! Dependencies align well with Prometheus monitoring objectives.
The addition of prometheus, lazy_static, and hyper with appropriate features provides a solid foundation for implementing Prometheus-based monitoring.
src/cli.rs (1)
72-80: LGTM! The parallel execution parameter is well-defined.
The new parallel parameter is well-documented and uses appropriate types and defaults. The implementation aligns with the PR's monitoring objectives, as parallel execution metrics would be valuable to track in Prometheus.
Let's verify the parameter usage:
✅ Verification successful
Parallel execution parameter is properly implemented and used
The parallel parameter is correctly implemented in the codebase:
- It's properly extracted from CLI args in
src/main.rs - Used to spawn multiple workers with
spawn_workerfunction - Results are collected from all parallel tasks
- Implementation follows Rust's async/await patterns for concurrent execution
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check how the parallel parameter is used in the codebase
# Expected: Find usage in main.rs or similar execution-related files
# Search for Run variant matching and parallel parameter extraction
ast-grep --pattern 'match $_ {
Commands::Run { parallel, $$$} => $$$
}'
# Search for any direct usage of the parallel parameter
rg -l "parallel" --type rust
Length of output: 129
Script:
#!/bin/bash
# Let's check the actual usage of the parallel parameter in main.rs
rg -A 10 "Commands::Run.*parallel" src/main.rs
# Also check for any parallel execution implementation
rg "parallel" src/main.rs
Length of output: 285
Script:
#!/bin/bash
# Let's see the implementation context of parallel execution
rg -B 5 -A 15 "let mut handles = Vec::with_capacity\(parallel\)" src/main.rs
# Also check if there are any tests for parallel execution
rg -l "parallel.*test" src/main.rs
Length of output: 890
src/falkor.rs (1)
366-369: Assess the necessity of Clone derivation for FalkorBenchmarkClient
The FalkorBenchmarkClient struct derives Clone. Cloning instances of structs containing asynchronous clients may lead to unintended behaviors or performance issues. Ensure that Clone is necessary and used correctly.
Run the following script to search for Clone usage and assess whether it's required:
Verify if the clone operations are essential. If not, consider removing the Clone trait derivation.
src/main.rs (1)
48-48: Verify that PrometheusEndpoint::new() initializes the metrics server correctly.
Ensure that the metrics server is properly started and listening on the expected port when PrometheusEndpoint::new() is called.
Run the following script to confirm the initialization:
✅ Verification successful
The metrics server initialization in PrometheusEndpoint::new() is correctly implemented
Based on the code analysis:
- The server is properly initialized on port 3000 and localhost (127.0.0.1)
- It includes graceful shutdown handling through a oneshot channel
- The server is spawned in a separate task to run asynchronously
- Proper logging is implemented for server start and errors
- The metrics endpoint uses the standard prometheus crate for gathering metrics
- Clean shutdown is handled via the Drop trait implementation
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Verify that PrometheusEndpoint starts the metrics server.
# Search for usage of PrometheusEndpoint methods after initialization.
rg -A 5 'prometheus_endpoint\s*=\s*PrometheusEndpoint::new\(\)'
Length of output: 65
Script:
#!/bin/bash
# Let's first find the PrometheusEndpoint implementation
ast-grep --pattern 'struct PrometheusEndpoint'
# Also search for any implementation blocks
ast-grep --pattern 'impl PrometheusEndpoint'
# Search for any usage of PrometheusEndpoint in the codebase
rg "PrometheusEndpoint" -A 5
Length of output: 3541
Script:
#!/bin/bash
# Let's check the metrics_handler implementation
ast-grep --pattern 'fn metrics_handler'
# Also search for any prometheus metric registrations
rg "prometheus" -i --type rust
Length of output: 699
| prometheus = { version = "0.13.4", features = ["gen"] } | ||
| lazy_static = "1.5" | ||
| hyper = { version = "0.14.31", features = ["server", "runtime", "http1", "tcp"] } |
There was a problem hiding this comment.
💡 Codebase verification
Update hyper dependency to the latest version 1.5.1
The dependency check reveals:
- prometheus 0.13.4: Using latest version ✓
- lazy_static 1.5.0: Using latest version ✓
- hyper 0.14.31: Outdated, latest version is 1.5.1
While the current hyper version (0.14.31) is not affected by any known security vulnerabilities, it's recommended to upgrade to the latest stable version 1.5.1 to benefit from improvements and bug fixes.
🔗 Analysis chain
Verify dependency versions for updates and security advisories.
Let's ensure we're using the latest stable versions and check for any security advisories.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check latest versions and security advisories for new dependencies
# Check crates.io for latest versions
echo "Checking latest versions..."
for crate in prometheus lazy_static hyper; do
echo "=== $crate ==="
curl -s "https://crates.io/api/v1/crates/$crate" | jq -r '.crate.max_stable_version'
done
# Check for security advisories
echo -e "\nChecking security advisories..."
for crate in prometheus lazy_static hyper; do
echo "=== $crate ==="
gh api graphql -f query='{
securityVulnerabilities(first: 5, ecosystem: RUST, package: "'$crate'") {
nodes {
advisory {
summary
severity
publishedAt
}
vulnerableVersionRange
firstPatchedVersion {
identifier
}
}
}
}'
done
Length of output: 3187
| info!("Prometheus endpoint shutdown"); | ||
| } | ||
| if let Some(thread) = self.server_thread.take() { | ||
| drop(thread); |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Properly await the server task to ensure graceful shutdown
Dropping the JoinHandle without awaiting it might prevent the server from shutting down gracefully. Since Drop cannot be async, consider restructuring the shutdown logic to ensure the server task is properly awaited.
One possible solution is to expose an explicit shutdown method that can be called before dropping the PrometheusEndpoint, allowing the task to be awaited properly.
| if let Some(tx) = self.shutdown_tx.take() { | ||
| let _ = tx.send(()); | ||
| info!("Prometheus endpoint shutdown"); | ||
| } | ||
| if let Some(thread) = self.server_thread.take() { | ||
| drop(thread); | ||
| } | ||
| } |
There was a problem hiding this comment.
Ensure graceful shutdown of the server
The current Drop implementation sends a shutdown signal but does not await the completion of the server task. This might result in the server not shutting down properly. Since Drop cannot be async, consider refactoring to handle shutdown more effectively.
Possible solution:
- Introduce an explicit
shutdownmethod that can be awaited before dropping thePrometheusEndpoint.
Example:
impl PrometheusEndpoint {
// Existing code...
pub async fn shutdown(&mut self) {
if let Some(tx) = self.shutdown_tx.take() {
let _ = tx.send(());
info!("Prometheus endpoint shutdown signal sent");
}
if let Some(thread) = self.server_thread.take() {
if let Err(e) = thread.await {
error!("Server task error: {}", e);
}
}
}
}Then, ensure that shutdown is called and awaited where appropriate.
| Ok(Response::builder() | ||
| .header(hyper::header::CONTENT_TYPE, encoder.format_type()) | ||
| .body(Body::from(buffer)) | ||
| .unwrap()) |
There was a problem hiding this comment.
Handle potential errors when building the HTTP response
Using .unwrap() when constructing the HTTP response can result in a panic if an error occurs. Instead, handle the potential error and return an appropriate HTTP response.
Suggested change:
- Ok(Response::builder()
- .header(hyper::header::CONTENT_TYPE, encoder.format_type())
- .body(Body::from(buffer))
- .unwrap())
+ match Response::builder()
+ .header(hyper::header::CONTENT_TYPE, encoder.format_type())
+ .body(Body::from(buffer)) {
+ Ok(response) => Ok(response),
+ Err(e) => {
+ error!("Failed to build response: {}", e);
+ Ok(Response::builder()
+ .status(hyper::StatusCode::INTERNAL_SERVER_ERROR)
+ .body(Body::from("Internal Server Error"))
+ .unwrap())
+ }
+ }Committable suggestion skipped: line range outside the PR's diff.
| let encoder = TextEncoder::new(); | ||
| let metric_families = prometheus::gather(); | ||
| let mut buffer = Vec::new(); | ||
| encoder.encode(&metric_families, &mut buffer).unwrap(); |
There was a problem hiding this comment.
Handle potential errors from encoder.encode instead of using unwrap()
Using unwrap() on encoder.encode(&metric_families, &mut buffer) can cause the application to panic if an encoding error occurs. To improve the robustness of the server, consider handling the error properly and returning an appropriate HTTP response.
Suggested change:
- encoder.encode(&metric_families, &mut buffer).unwrap();
+ if let Err(e) = encoder.encode(&metric_families, &mut buffer) {
+ error!("Failed to encode metrics: {}", e);
+ return Ok(Response::builder()
+ .status(hyper::StatusCode::INTERNAL_SERVER_ERROR)
+ .body(Body::from("Internal Server Error"))
+ .unwrap());
+ }📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| encoder.encode(&metric_families, &mut buffer).unwrap(); | |
| if let Err(e) = encoder.encode(&metric_families, &mut buffer) { | |
| error!("Failed to encode metrics: {}", e); | |
| return Ok(Response::builder() | |
| .status(hyper::StatusCode::INTERNAL_SERVER_ERROR) | |
| .body(Body::from("Internal Server Error")) | |
| .unwrap()); | |
| } |
src/falkor.rs
Outdated
| for (query_name, _query_type, query) in queries.into_iter() { | ||
| let _res = self | ||
| .execute_query(query_name.as_str(), query.as_str()) | ||
| .await; |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Handle errors returned by execute_query
In the execute_queries method, the result of execute_query is assigned to _res but not used. Ignoring errors can lead to unnoticed failures. Consider handling the errors to ensure robust execution.
Apply this diff to handle potential errors:
for (query_name, _query_type, query) in queries.into_iter() {
- let _res = self
+ if let Err(e) = self
.execute_query(query_name.as_str(), query.as_str())
.await
- ;
+ {
+ error!("Failed to execute query '{}': {}", query_name, e);
+ // Optionally handle the error further or decide whether to continue or abort
+ }
}📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| for (query_name, _query_type, query) in queries.into_iter() { | |
| let _res = self | |
| .execute_query(query_name.as_str(), query.as_str()) | |
| .await; | |
| for (query_name, _query_type, query) in queries.into_iter() { | |
| if let Err(e) = self | |
| .execute_query(query_name.as_str(), query.as_str()) | |
| .await | |
| { | |
| error!("Failed to execute query '{}': {}", query_name, e); | |
| // Optionally handle the error further or decide whether to continue or abort | |
| } |
| async fn run_falkor( | ||
| size: Size, | ||
| number_of_queries: u64, | ||
| machine_metadata: MachineMetadata, | ||
| parallel: usize, |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Validate the parallel parameter to prevent potential issues.
Ensure that the parallel parameter is greater than zero to avoid division by zero or spawning zero workers.
Apply this diff to add parameter validation:
async fn run_falkor(
size: Size,
number_of_queries: u64,
machine_metadata: MachineMetadata,
parallel: usize,
) -> BenchmarkResult<()> {
+ if parallel == 0 {
+ return Err(OtherError("Parallelism level must be greater than zero.".to_string()));
+ }Committable suggestion skipped: line range outside the PR's diff.
src/main.rs
Outdated
| for spawn_id in 0..parallel { | ||
| let queries = queries.clone(); | ||
| let handle = spawn_worker(&mut falkor, queries, spawn_id).await?; | ||
| handles.push(handle); | ||
| } |
There was a problem hiding this comment.
Distribute queries among workers to avoid redundant executions.
Currently, each worker receives the entire set of queries, leading to duplicate processing. Modify the code to partition the queries so each worker processes a unique subset.
Apply this diff to distribute queries evenly:
for spawn_id in 0..parallel {
- let queries = queries.clone();
+ let chunk_size = (queries.len() + parallel - 1) / parallel;
+ let start_idx = spawn_id * chunk_size;
+ let end_idx = usize::min(start_idx + chunk_size, queries.len());
+ let queries_chunk = queries[start_idx..end_idx].to_vec();
- let handle = spawn_worker(&mut falkor, queries, spawn_id).await?;
+ let handle = spawn_worker(&falkor, queries_chunk, spawn_id).await?;
handles.push(handle);
}📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| for spawn_id in 0..parallel { | |
| let queries = queries.clone(); | |
| let handle = spawn_worker(&mut falkor, queries, spawn_id).await?; | |
| handles.push(handle); | |
| } | |
| for spawn_id in 0..parallel { | |
| let chunk_size = (queries.len() + parallel - 1) / parallel; | |
| let start_idx = spawn_id * chunk_size; | |
| let end_idx = usize::min(start_idx + chunk_size, queries.len()); | |
| let queries_chunk = queries[start_idx..end_idx].to_vec(); | |
| let handle = spawn_worker(&falkor, queries_chunk, spawn_id).await?; | |
| handles.push(handle); | |
| } |
src/main.rs
Outdated
| #[instrument(skip(falkor, queries, _spawn_id), fields(spawn_id = _spawn_id, vendor = "falkor", query_count = queries.len()))] | ||
| async fn spawn_worker( | ||
| falkor: &mut Falkor<Connected>, | ||
| queries: Vec<(String, QueryType, String)>, | ||
| _spawn_id: usize, | ||
| ) -> BenchmarkResult<JoinHandle<()>> { | ||
| let queries = queries.clone(); | ||
| let mut graph = falkor.client().await?; | ||
| let handle = tokio::spawn( | ||
| async move { | ||
| graph.execute_queries(queries).await; | ||
| } | ||
| .instrument(tracing::Span::current()), | ||
| ); | ||
|
|
||
| Ok(handle) | ||
| } |
There was a problem hiding this comment.
Avoid sharing mutable references across asynchronous tasks.
Passing &mut falkor to multiple asynchronous tasks can cause concurrency issues. Instead, use immutable references or clone the Falkor<Connected> instance for each worker to ensure thread safety.
Apply this diff to prevent data races:
-async fn spawn_worker(
- falkor: &mut Falkor<Connected>,
+async fn spawn_worker(
+ falkor: &Falkor<Connected>,
queries: Vec<(String, QueryType, String)>,
_spawn_id: usize,
) -> BenchmarkResult<JoinHandle<()>> {
- let queries = queries.clone();
- let mut graph = falkor.client().await?;
+ let mut graph = falkor.clone().client().await?;
let handle = tokio::spawn(
async move {
graph.execute_queries(queries).await;
}
.instrument(tracing::Span::current()),
);
Ok(handle)
}📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| #[instrument(skip(falkor, queries, _spawn_id), fields(spawn_id = _spawn_id, vendor = "falkor", query_count = queries.len()))] | |
| async fn spawn_worker( | |
| falkor: &mut Falkor<Connected>, | |
| queries: Vec<(String, QueryType, String)>, | |
| _spawn_id: usize, | |
| ) -> BenchmarkResult<JoinHandle<()>> { | |
| let queries = queries.clone(); | |
| let mut graph = falkor.client().await?; | |
| let handle = tokio::spawn( | |
| async move { | |
| graph.execute_queries(queries).await; | |
| } | |
| .instrument(tracing::Span::current()), | |
| ); | |
| Ok(handle) | |
| } | |
| #[instrument(skip(falkor, queries, _spawn_id), fields(spawn_id = _spawn_id, vendor = "falkor", query_count = queries.len()))] | |
| async fn spawn_worker( | |
| falkor: &Falkor<Connected>, | |
| queries: Vec<(String, QueryType, String)>, | |
| _spawn_id: usize, | |
| ) -> BenchmarkResult<JoinHandle<()>> { | |
| let mut graph = falkor.clone().client().await?; | |
| let handle = tokio::spawn( | |
| async move { | |
| graph.execute_queries(queries).await; | |
| } | |
| .instrument(tracing::Span::current()), | |
| ); | |
| Ok(handle) | |
| } |
There was a problem hiding this comment.
Actionable comments posted: 13
🧹 Outside diff range and nitpick comments (13)
provisioning/dashboards/dashboards.yaml (1)
7-7: Consider increasing the update interval.The current
updateIntervalSeconds: 10setting might be too aggressive for production use, potentially causing unnecessary system load. Consider increasing this value to 30-60 seconds unless there's a specific requirement for such frequent updates.- updateIntervalSeconds: 10 + updateIntervalSeconds: 30prometheus.yml (2)
1-3: Consider increasing the scrape_timeout valueThe current scrape_timeout of 500ms might be too aggressive for reliable metrics collection, especially if the services experience any latency. A common practice is to set the timeout to about 1/4th of the scrape interval.
global: scrape_interval: 10s - scrape_timeout: 500ms + scrape_timeout: 2.5s
1-14: Consider implementing alerting and recording rulesSince this is a new Prometheus-based monitoring solution, consider enhancing it with:
- Recording rules for frequently used queries and aggregations
- Alerting rules for critical metrics
- Grafana dashboards for visualization
Example recording rules for benchmark metrics:
groups: - name: benchmark_recordings rules: - record: benchmark:latency:p95 expr: histogram_quantile(0.95, rate(benchmark_latency_bucket[5m])) - record: benchmark:qps:rate5m expr: rate(benchmark_queries_total[5m])Would you like assistance in creating a comprehensive monitoring strategy with recording rules, alerting rules, and Grafana dashboards?
readme.md (1)
76-77: Format URLs using proper markdown link syntaxFor better readability and markdown compliance, format the URLs as proper markdown links:
-Accessing grafana http://localhost:3000 -Accessing prometheus http://localhost:9090 +- Accessing grafana at [http://localhost:3000](http://localhost:3000) +- Accessing prometheus at [http://localhost:9090](http://localhost:9090)🧰 Tools
🪛 Markdownlint (0.35.0)
76-76: null
Bare URL used(MD034, no-bare-urls)
77-77: null
Bare URL used(MD034, no-bare-urls)
src/falkor.rs (3)
396-398: Consider restructuring metric labels for better queryingThe current label structure
["falkor", spawn_id, "", query_name, "", ""]contains empty string placeholders which may complicate metric querying and increase cardinality unnecessarily.Consider consolidating the labels to only include meaningful values:
- .with_label_values(&["falkor", spawn_id, "", query_name, "", ""]) + .with_label_values(&["falkor", spawn_id, query_name])Also applies to: 415-417
118-126: Maintain consistent error message formattingThe error message format in this implementation differs from the one in
FalkorBenchmarkClient::read_reply. This implementation usesError {} while executing querywhile the other usesError executing query: {:?}.Standardize the error message format across both implementations:
- error!("Error {} while executing query", e); + error!("Error executing query: {:?}", e);
403-425: Remove commented-out codeThe method contains several commented-out lines that should either be removed or uncommented if they serve a purpose.
Clean up the commented code:
fn read_reply( spawn_id: &str, query_name: &str, reply: FalkorResult<QueryResult<LazyResultSet>>, ) { match reply { Ok(_) => { tracing::Span::current().record("result", &"success"); - // info!("Query executed successfully"); } Err(e) => { OPERATION_ERROR_COUNTER .with_label_values(&["falkor", spawn_id, "", query_name, "", ""]) .inc(); - // tracing::Span::current().record("result", &"failure"); let error_type = std::any::type_name_of_val(&e); tracing::Span::current().record("result", &"failure"); tracing::Span::current().record("error_type", &error_type); error!("Error executing query: {:?}", e); } } }src/main.rs (1)
38-65: Add documentation for Prometheus metrics.While the metrics setup is comprehensive, adding documentation would improve maintainability:
- Purpose of each counter
- Description of label combinations
- Expected usage patterns
Apply this diff to add documentation:
lazy_static! { + /// Counter for successful operations. + /// Labels: + /// - vendor: The database vendor (e.g., "falkor", "neo4j") + /// - spawn_id: Worker ID for parallel execution + /// - type: Operation type + /// - name: Query name + /// - dataset: Dataset name + /// - dataset_size: Size of the dataset pub(crate) static ref OPERATION_COUNTER: CounterVec = register_counter_vec!( "operations_total", "Total number of operations processed", &["vendor", "spawn_id", "type", "name", "dataset", "dataset_size"] ) .unwrap(); + /// Counter for failed operations. + /// Uses the same label structure as OPERATION_COUNTER. pub(crate) static ref OPERATION_ERROR_COUNTER: CounterVec = register_counter_vec!(dashboards/falkor_dashboard.json (3)
2-17: Consider adding custom annotations for important events.The dashboard currently only uses the default Grafana annotations. Consider adding custom annotations for important events such as:
- Deployment markers
- Configuration changes
- Maintenance windows
"annotations": { "list": [ { "builtIn": 1, "datasource": { "type": "grafana", "uid": "-- Grafana --" }, "enable": true, "hide": true, "iconColor": "rgba(0, 211, 255, 1)", "name": "Annotations & Alerts", "type": "dashboard" - } + }, + { + "datasource": { + "type": "prometheus", + "uid": "PBFA97CFB590B2093" + }, + "enable": true, + "iconColor": "red", + "name": "Deployments", + "target": { + "expr": "changes(process_start_time_seconds{job=\"falkor_benchmark\"}[1m]) > 0" + } + } ] },
756-759: Extend default time range for better trend visibility.A 5-minute default time range might be too short to observe trends and patterns effectively.
"time": { - "from": "now-5m", + "from": "now-1h", "to": "now" },
753-755: Add templating variables for better dashboard reusability.Consider adding template variables for:
- Instance selection
- Job selection
- Time range intervals
This would make the dashboard more flexible and reusable across different environments."templating": { - "list": [] + "list": [ + { + "name": "instance", + "type": "query", + "datasource": "PBFA97CFB590B2093", + "query": "label_values(redis_up, instance)", + "refresh": 2 + }, + { + "name": "job", + "type": "query", + "datasource": "PBFA97CFB590B2093", + "query": "label_values(redis_up, job)", + "refresh": 2 + } + ] },dashboards/redis_dashboard.json (2)
312-312: Review memory usage alert thresholds.The memory usage panel uses thresholds of 80% and 95%. Consider:
- Whether these thresholds align with your Redis instance's capacity planning
- Adding annotations or alerts for proactive monitoring
You might want to adjust these thresholds based on:
- Your Redis instance's total memory
- Historical memory usage patterns
- Business requirements for free memory
51-51: Well-structured Redis monitoring dashboard.The dashboard provides comprehensive Redis monitoring with appropriate metrics organization:
- Performance metrics (commands, network I/O)
- Resource utilization (memory, clients)
- Key statistics (expiry, eviction)
Consider adding:
- Error rate metrics
- Replication lag if using Redis replication
- Cache hit ratio trends
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (10)
dashboards/falkor_dashboard.json(1 hunks)dashboards/redis_dashboard.json(1 hunks)docker-compose.yml(1 hunks)grafana-datasources.yml(1 hunks)prometheus.yml(1 hunks)provisioning/dashboards/dashboards.yaml(1 hunks)readme.md(1 hunks)src/falkor.rs(6 hunks)src/main.rs(9 hunks)src/prometheus_endpoint.rs(1 hunks)
🧰 Additional context used
🪛 yamllint (1.35.1)
docker-compose.yml
[error] 36-36: no new line character at the end of file
(new-line-at-end-of-file)
grafana-datasources.yml
[error] 8-8: no new line character at the end of file
(new-line-at-end-of-file)
provisioning/dashboards/dashboards.yaml
[error] 9-9: no new line character at the end of file
(new-line-at-end-of-file)
🪛 Markdownlint (0.35.0)
readme.md
74-74: Expected: setext; Actual: atx
Heading style
(MD003, heading-style)
76-76: null
Bare URL used
(MD034, no-bare-urls)
77-77: null
Bare URL used
(MD034, no-bare-urls)
🔇 Additional comments (12)
provisioning/dashboards/dashboards.yaml (2)
1-9: LGTM! Configuration follows Grafana's best practices.
The dashboard provisioning configuration is well-structured and uses the correct API version.
🧰 Tools
🪛 yamllint (1.35.1)
[error] 9-9: no new line character at the end of file
(new-line-at-end-of-file)
8-9: Verify dashboard path and fix file format.
Two items need attention:
- Ensure the
/var/lib/grafana/dashboardspath exists and has proper permissions in the container. - Add a newline at the end of the file to comply with YAML standards.
Run this script to verify the dashboard path exists in the container configuration:
Apply this diff to fix the file format:
path: /var/lib/grafana/dashboards
+🧰 Tools
🪛 yamllint (1.35.1)
[error] 9-9: no new line character at the end of file
(new-line-at-end-of-file)
src/prometheus_endpoint.rs (5)
1-9: LGTM: Imports are well-organized and appropriate
All necessary dependencies are properly imported and organized by functionality.
10-13: LGTM: Well-designed struct with appropriate visibility
The struct is well-designed with Optional fields that enable proper resource management and cleanup.
44-54:
Ensure proper server shutdown by implementing an async shutdown method
The current Drop implementation may not allow for proper server shutdown since Drop cannot be async.
Consider implementing an explicit shutdown method as suggested in previous reviews:
impl PrometheusEndpoint {
pub async fn shutdown(&mut self) {
if let Some(tx) = self.shutdown_tx.take() {
let _ = tx.send(());
info!("Prometheus endpoint shutdown signal sent");
}
if let Some(thread) = self.server_thread.take() {
if let Err(e) = thread.await {
error!("Server task error: {}", e);
}
}
}
}56-66:
Improve error handling in metrics_handler
The current implementation uses unwrap() which could cause panics in production.
As suggested in previous reviews, implement proper error handling:
async fn metrics_handler(_req: Request<Body>) -> Result<Response<Body>, hyper::Error> {
let encoder = TextEncoder::new();
let metric_families = prometheus::gather();
let mut buffer = Vec::new();
match encoder.encode(&metric_families, &mut buffer) {
Ok(_) => {
info!("Metrics request received");
Response::builder()
.header(hyper::header::CONTENT_TYPE, encoder.format_type())
.body(Body::from(buffer))
.map_err(|e| {
error!("Failed to build response: {}", e);
hyper::Error::from(std::io::Error::new(
std::io::ErrorKind::Other,
"Failed to build response"
))
})
}
Err(e) => {
error!("Failed to encode metrics: {}", e);
Response::builder()
.status(StatusCode::INTERNAL_SERVER_ERROR)
.body(Body::from("Failed to encode metrics"))
.map_err(|e| {
hyper::Error::from(std::io::Error::new(
std::io::ErrorKind::Other,
e.to_string()
))
})
}
}
}58-58: Verify metrics collection setup
The code calls prometheus::gather() but there's no visible setup for collecting metrics.
Let's verify if metrics are being registered elsewhere in the codebase:
✅ Verification successful
Metrics collection is properly set up
The metrics setup is correctly implemented:
- Two metrics counters are registered globally using
lazy_static:OPERATION_COUNTERandOPERATION_ERROR_COUNTER - The PrometheusEndpoint correctly gathers these metrics via
prometheus::gather() - The endpoint is properly initialized in main and gracefully shut down
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Search for prometheus metric registrations
rg "prometheus::(Counter|Gauge|Histogram|register)" --type rust
Length of output: 65
Script:
#!/bin/bash
# Let's try a broader search for prometheus-related code
rg "prometheus::" --type rust -A 3
Length of output: 720
Script:
#!/bin/bash
# Also search for any prometheus-related imports
rg "use prometheus" --type rust
Length of output: 164
Script:
#!/bin/bash
# Check the content of the prometheus endpoint file
cat src/prometheus_endpoint.rs
Length of output: 2083
Script:
#!/bin/bash
# Let's check main.rs for metric registrations and usage
cat src/main.rs
Length of output: 14865
src/falkor.rs (1)
380-384:
Handle query execution errors appropriately
The method ignores the result of execute_query, which could mask important errors during benchmarking.
Consider handling errors appropriately:
for (query_name, _query_type, query) in queries.into_iter() {
- let _res = self
+ if let Err(e) = self
.execute_query(spawn_id.as_str(), query_name.as_str(), query.as_str())
- .await;
+ .await
+ {
+ error!(
+ "Failed to execute query '{}': {:?}",
+ query_name, e
+ );
+ // Optionally: break the loop or continue based on error severity
+ }
}Likely invalid or redundant comment.
src/main.rs (4)
8-8: LGTM: Module and import declarations are well-structured.
The new module and imports are appropriately placed and necessary for implementing Prometheus metrics and parallel execution support.
Also applies to: 30-31, 34-34
269-275:
Optimize parallel query execution implementation.
The current implementation has several issues:
- Inefficient memory usage due to cloning all queries for each worker
- Missing validation for the parallel parameter
- Suboptimal query distribution among workers
Previous review comments about query distribution and parallel parameter validation remain valid. Additionally:
Apply this diff to optimize memory usage and add validation:
+ if parallel == 0 {
+ return Err(OtherError("Parallelism level must be greater than zero".to_string()));
+ }
+
let mut handles = Vec::with_capacity(parallel);
let start = Instant::now();
+ let chunk_size = (queries.len() + parallel - 1) / parallel;
for spawn_id in 0..parallel {
- let queries = queries.clone();
+ let start_idx = spawn_id * chunk_size;
+ let end_idx = usize::min(start_idx + chunk_size, queries.len());
+ let queries_chunk = queries[start_idx..end_idx].to_vec();
- let handle = spawn_worker(&mut falkor, queries, spawn_id).await?;
+ let handle = spawn_worker(&mut falkor, queries_chunk, spawn_id).await?;
handles.push(handle);
}305-322:
Fix concurrency and error handling in worker implementation.
The current implementation has potential concurrency issues and lacks error handling:
- Using mutable references across async boundaries
- Unhandled errors in execute_queries
Previous review comments about mutable references and error handling remain valid. Apply this diff to fix these issues:
#[instrument(skip(falkor, queries), fields(vendor = "falkor", query_count = queries.len()))]
async fn spawn_worker(
- falkor: &mut Falkor<Connected>,
+ falkor: &Falkor<Connected>,
queries: Vec<(String, QueryType, String)>,
spawn_id: usize,
) -> BenchmarkResult<JoinHandle<()>> {
info!("spawning worker");
- let queries = queries.clone();
let mut graph = falkor.client().await?;
let handle = tokio::spawn(
async move {
- graph.execute_queries(spawn_id, queries).await;
+ if let Err(e) = graph.execute_queries(spawn_id, queries).await {
+ error!("Worker {spawn_id} encountered an error: {e:?}");
+ }
}
.instrument(tracing::Span::current()),
);
Ok(handle)
}277-284: Verify worker completion and metrics collection.
The current implementation should ensure proper cleanup:
- All workers should complete before proceeding
- Metrics should be collected from all workers
- Resources should be properly cleaned up
Run this script to check for proper resource cleanup:
✅ Verification successful
Based on the search results, I can generate the final response as I have enough information to verify the concern about worker completion and metrics collection. The code shows proper handling of these aspects:
Worker completion and metrics collection are properly handled
The implementation correctly ensures:
- All worker tasks are awaited using
handle.awaitin a loop, with proper error handling - Results from completed workers are collected into a
resultsvector - Failed tasks are logged via
eprintln! - Resources are properly cleaned up:
- Database connections are closed via
falkor.stop() - Files are properly closed after writing metrics
- Proper error handling exists throughout the async chain
- Database connections are closed via
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Check for potential resource leaks in error handling paths
rg -A 5 "tokio::spawn|\.await|\.client\(\)" src/
Length of output: 31534
prometheus.yml
Outdated
| - job_name: 'falkor_benchmark' | ||
| static_configs: | ||
| - targets: [ 'host.docker.internal:8080' ] |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Enhance service configuration for better portability and observability
The current configuration has several potential improvements:
- Using
host.docker.internallimits portability to Docker environments - Missing explicit scheme and metrics path
- Missing service labels for better metrics organization
- job_name: 'falkor_benchmark'
+ scheme: http
+ metrics_path: /metrics
static_configs:
- - targets: [ 'host.docker.internal:8080' ]
+ - targets: [ 'host.docker.internal:8080' ]
+ labels:
+ environment: 'benchmark'
+ service: 'falkor'📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| - job_name: 'falkor_benchmark' | |
| static_configs: | |
| - targets: [ 'host.docker.internal:8080' ] | |
| - job_name: 'falkor_benchmark' | |
| scheme: http | |
| metrics_path: /metrics | |
| static_configs: | |
| - targets: [ 'host.docker.internal:8080' ] | |
| labels: | |
| environment: 'benchmark' | |
| service: 'falkor' |
prometheus.yml
Outdated
| - job_name: 'redis' | ||
| static_configs: | ||
| - targets: [ 'redis-exporter:9121' ] |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Enhance Redis exporter configuration with best practices
The Redis exporter configuration could benefit from additional settings for better metrics organization and monitoring:
- Missing explicit scheme and metrics path
- Missing instance labels for Redis identification
- Could benefit from relabeling configurations
- job_name: 'redis'
+ scheme: http
+ metrics_path: /metrics
static_configs:
- - targets: [ 'redis-exporter:9121' ]
+ - targets: [ 'redis-exporter:9121' ]
+ labels:
+ environment: 'benchmark'
+ redis_role: 'main'
+ metric_relabel_configs:
+ - source_labels: [__name__]
+ regex: 'redis_(.*)'
+ target_label: redis_metric
+ replacement: '${1}'📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| - job_name: 'redis' | |
| static_configs: | |
| - targets: [ 'redis-exporter:9121' ] | |
| - job_name: 'redis' | |
| scheme: http | |
| metrics_path: /metrics | |
| static_configs: | |
| - targets: [ 'redis-exporter:9121' ] | |
| labels: | |
| environment: 'benchmark' | |
| redis_role: 'main' | |
| metric_relabel_configs: | |
| - source_labels: [__name__] | |
| regex: 'redis_(.*)' | |
| target_label: redis_metric | |
| replacement: '${1}' |
src/prometheus_endpoint.rs
Outdated
| let (shutdown_tx, shutdown_rx) = tokio::sync::oneshot::channel::<()>(); | ||
|
|
||
| let server_thread = task::spawn(async { | ||
| let addr = SocketAddr::from(([127, 0, 0, 1], 8080)); |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Consider making the server address configurable
The hardcoded address 127.0.0.1:8080 might not be suitable for all deployment scenarios. Consider making it configurable through environment variables or constructor parameters.
- let addr = SocketAddr::from(([127, 0, 0, 1], 8080));
+ let host = std::env::var("PROMETHEUS_HOST").unwrap_or_else(|_| "127.0.0.1".to_string());
+ let port = std::env::var("PROMETHEUS_PORT")
+ .ok()
+ .and_then(|p| p.parse().ok())
+ .unwrap_or(8080);
+ let addr: SocketAddr = format!("{}:{}", host, port).parse().expect("Invalid address");Committable suggestion skipped: line range outside the PR's diff.
readme.md
Outdated
| - sum by (vendor, spawn_id) (rate(operations_total{vendor="falkor"}[1m])) | ||
| redis | ||
| - rate(redis_commands_processed_total{instance=~"redis-exporter:9121"}[1m]) | ||
| - redis_connected_clients{instance=~"redis-exporter:9121"} | ||
| - topk(5, irate(redis_commands_total{instance=~"redis-exporter:9121"} [1m])) | ||
| redis_blocked_clients | ||
| - redis_commands_failed_calls_total | ||
| - redis_commands_latencies_usec_count | ||
| - redis_commands_rejected_calls_total | ||
| - redis_io_threaded_reads_processed | ||
| - redis_io_threaded_writes_processed | ||
| - redis_io_threads_active | ||
| - redis_memory_used_bytes | ||
| - redis_memory_used_peak_bytes | ||
| - redis_memory_used_vm_total | ||
| - redis_process_id |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Enhance the Prometheus queries documentation
The Prometheus queries section would benefit from better organization and more context:
- Group queries by category
- Add descriptions for each query
- Fix inconsistent formatting
- Add example outputs
Here's a suggested structure:
### Grafana and Prometheus
-sum by (vendor, spawn_id) (rate(operations_total{vendor="falkor"}[1m]))
-redis
-rate(redis_commands_processed_total{instance=~"redis-exporter:9121"}[1m])
-redis_connected_clients{instance=~"redis-exporter:9121"}
-topk(5, irate(redis_commands_total{instance=~"redis-exporter:9121"} [1m]))
-redis_blocked_clients
-redis_commands_failed_calls_total
-redis_commands_latencies_usec_count
-redis_commands_rejected_calls_total
-redis_io_threaded_reads_processed
-redis_io_threaded_writes_processed
-redis_io_threads_active
-redis_memory_used_bytes
-redis_memory_used_peak_bytes
-redis_memory_used_vm_total
-redis_process_id
+#### Benchmark Performance Metrics
+- Operations Rate:
+ ```promql
+ sum by (vendor, spawn_id) (rate(operations_total{vendor="falkor"}[1m]))
+ ```
+ Shows the rate of operations per minute for each vendor and spawn ID.
+
+#### Redis Server Metrics
+
+##### Command Processing
+- Command Rate:
+ ```promql
+ rate(redis_commands_processed_total{instance=~"redis-exporter:9121"}[1m])
+ ```
+ Shows the rate of processed commands per minute.
+
+- Top Commands:
+ ```promql
+ topk(5, irate(redis_commands_total{instance=~"redis-exporter:9121"} [1m]))
+ ```
+ Shows the top 5 most frequently used commands.
+
+##### Client Connections
+- Active Clients:
+ ```promql
+ redis_connected_clients{instance=~"redis-exporter:9121"}
+ ```
+ Shows the number of currently connected clients.
+
+##### Memory Usage
+- Current Memory:
+ ```promql
+ redis_memory_used_bytes
+ ```
+ Shows current memory usage in bytes.
+
+- Peak Memory:
+ ```promql
+ redis_memory_used_peak_bytes
+ ```
+ Shows peak memory usage in bytes.
src/falkor.rs
Outdated
| pub async fn client(&self) -> BenchmarkResult<FalkorBenchmarkClient> { | ||
| let connection_info = "falkor://127.0.0.1:6379".try_into()?; | ||
| let client = FalkorClientBuilder::new_async() | ||
| .with_connection_info(connection_info) | ||
| .build() | ||
| .await?; | ||
| Ok(FalkorBenchmarkClient { | ||
| graph: client.select_graph("falkor"), | ||
| }) | ||
| } |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Parameterize connection details for better reusability
The connection string and graph name are hardcoded, which limits the reusability of the client across different environments or configurations.
Consider parameterizing these values:
- pub async fn client(&self) -> BenchmarkResult<FalkorBenchmarkClient> {
+ pub async fn client(
+ &self,
+ connection_string: &str,
+ graph_name: &str,
+ ) -> BenchmarkResult<FalkorBenchmarkClient> {
- let connection_info = "falkor://127.0.0.1:6379".try_into()?;
+ let connection_info = connection_string.try_into()?;
let client = FalkorClientBuilder::new_async()
.with_connection_info(connection_info)
.build()
.await?;
Ok(FalkorBenchmarkClient {
- graph: client.select_graph("falkor"),
+ graph: client.select_graph(graph_name),
})
}📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| pub async fn client(&self) -> BenchmarkResult<FalkorBenchmarkClient> { | |
| let connection_info = "falkor://127.0.0.1:6379".try_into()?; | |
| let client = FalkorClientBuilder::new_async() | |
| .with_connection_info(connection_info) | |
| .build() | |
| .await?; | |
| Ok(FalkorBenchmarkClient { | |
| graph: client.select_graph("falkor"), | |
| }) | |
| } | |
| pub async fn client( | |
| &self, | |
| connection_string: &str, | |
| graph_name: &str, | |
| ) -> BenchmarkResult<FalkorBenchmarkClient> { | |
| let connection_info = connection_string.try_into()?; | |
| let client = FalkorClientBuilder::new_async() | |
| .with_connection_info(connection_info) | |
| .build() | |
| .await?; | |
| Ok(FalkorBenchmarkClient { | |
| graph: client.select_graph(graph_name), | |
| }) | |
| } |
dashboards/falkor_dashboard.json
Outdated
| "targets": [ | ||
| { | ||
| "editorMode": "code", | ||
| "expr": "max(max_over_time(redis_uptime_in_seconds{instance=~\"redis-exporter:9121\"}[$__interval]))", |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Improve uptime metric calculation.
The current uptime calculation using max_over_time with $__interval might miss data points. Consider using a more reliable approach.
- "expr": "max(max_over_time(redis_uptime_in_seconds{instance=~\"redis-exporter:9121\"}[$__interval]))",
+ "expr": "time() - process_start_time_seconds{instance=~\"redis-exporter:9121\"}",📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| "expr": "max(max_over_time(redis_uptime_in_seconds{instance=~\"redis-exporter:9121\"}[$__interval]))", | |
| "expr": "time() - process_start_time_seconds{instance=~\"redis-exporter:9121\"}", |
dashboards/falkor_dashboard.json
Outdated
| "expr": "redis_commands_latencies_usec_count", | ||
| "legendFormat": "{{ cmd }}", |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Enhance latency metric visualization.
The current latency metric might not provide accurate percentiles. Consider using histogram_quantile for better latency tracking.
- "expr": "redis_commands_latencies_usec_count",
- "legendFormat": "{{ cmd }}",
+ "expr": "histogram_quantile(0.95, sum(rate(redis_commands_duration_seconds_bucket[5m])) by (le, cmd))",
+ "legendFormat": "p95 {{ cmd }}",📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| "expr": "redis_commands_latencies_usec_count", | |
| "legendFormat": "{{ cmd }}", | |
| "expr": "histogram_quantile(0.95, sum(rate(redis_commands_duration_seconds_bucket[5m])) by (le, cmd))", | |
| "legendFormat": "p95 {{ cmd }}", |
| "type": "panel", | ||
| "id": "singlestat", | ||
| "name": "Singlestat", | ||
| "version": "" |
There was a problem hiding this comment.
Update Grafana and panel versions to latest stable releases.
The dashboard configuration uses outdated versions:
- Grafana v3.1.1 is very old (current stable is 10.x)
- The "singlestat" panel type is deprecated in favor of "stat" panel
- Prometheus datasource v1.0.0 is outdated
Consider updating to the latest stable versions and replacing deprecated panel types. This will provide access to new features, security updates, and better performance.
Also applies to: 29-29, 35-35
| "allValue": null, | ||
| "current": {}, | ||
| "datasource": "${DS_PROM}", | ||
| "definition": "label_values(redis_up, instance)", |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Improve instance selector query specificity.
The current query label_values(redis_up, instance) might include non-Redis instances. Consider using a more specific query to ensure only Redis instances are listed.
Replace the query with:
-"definition": "label_values(redis_up, instance)",
+"definition": "label_values(redis_up{job=~\".*redis.*\"}, instance)",And:
-"query": "label_values(redis_up, instance)",
+"query": "label_values(redis_up{job=~\".*redis.*\"}, instance)",Also applies to: 1160-1160
| } | ||
| } | ||
| ], | ||
| "refresh": "30s", |
There was a problem hiding this comment.
💡 Codebase verification
Consider increasing the dashboard refresh interval to match Prometheus scrape interval
The dashboard's 30s refresh interval is unnecessarily frequent since Prometheus scrapes Redis metrics every 10s. To avoid redundant UI updates, consider setting the dashboard refresh to match or slightly exceed the global scrape interval (10s).
- Change
"refresh": "30s"to"refresh": "10s"to align with Prometheus configuration - Or use
"refresh": "15s"to allow for slight delays in metric collection and processing
🔗 Analysis chain
Consider adjusting the refresh interval based on Redis metrics update frequency.
The 30-second refresh interval might be:
- Too frequent if Redis metrics don't change often, causing unnecessary load
- Too infrequent if real-time monitoring is required
Run this script to check the metrics update frequency:
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check Redis metrics update frequency in Prometheus config
# Look for Redis scrape interval in prometheus config
rg -A 5 "job_name.*redis" | rg "scrape_interval"
Length of output: 48
Script:
#!/bin/bash
# Let's try different approaches to find Prometheus configuration
# Look for prometheus config files with common names
fd -e yml -e yaml -e json prometheus
# Search for any file containing prometheus configuration patterns
rg -l "scrape_configs|job_name|scrape_interval"
# Search specifically for Redis-related monitoring configurations
rg -l "redis.*metrics|metrics.*redis"
Length of output: 158
Script:
#!/bin/bash
# Found prometheus.yml, let's examine its contents
cat prometheus.yml
Length of output: 282
There was a problem hiding this comment.
Actionable comments posted: 8
🧹 Outside diff range and nitpick comments (20)
src/bin/falkor_process_main.rs (1)
13-14: Remove or clarify commented-out codeThe following code is commented out:
// info!("killing falkor process"); // falkor_process.kill().await?;If this code is no longer needed, consider removing it to keep the codebase clean. If you plan to use it later, add a comment explaining its purpose and when it should be re-enabled.
src/cli.rs (2)
9-9: Reassess makingClistruct publicChanging the
Clistruct's visibility frompub(crate)topubexposes it to external crates. Consider if this increased visibility is necessary. If not, maintainingpub(crate)can help encapsulate the internal implementation details.
92-92: Review the necessity of exposingExistingJsonFilepubliclyMaking
ExistingJsonFilepublic changes its accessibility. If this struct is intended for internal use within the crate, consider keeping its visibility aspub(crate)to preserve encapsulation.src/scenario.rs (1)
82-101: Evaluate the need for making methods publicThe methods
backup_path,init_data_iterator,init_index_iterator, andcachehave been made public. If these methods are only used within the crate, consider keeping them withpub(crate)visibility to prevent external misuse and to maintain a clean API surface.src/utils.rs (1)
118-131: Simplify the filtering logic inread_linesfunctionThe current implementation uses
filter_mapto filter out empty lines or lines containing only a semicolon. You can simplify the code and improve clarity by usingtry_filterinstead.Apply this diff to refactor the filtering logic:
let stream = tokio_stream::wrappers::LinesStream::new(reader.lines()).filter_map(|res| { match res { Ok(line) => { // filter out empty lines or lines that contain only a semicolon let trimmed_line = line.trim(); if trimmed_line.is_empty() || trimmed_line == ";" { - None + Some(Ok(None)) } else { - Some(Ok(line)) + Some(Ok(Some(line))) } } Err(e) => Some(Err(e)), // Propagate errors } }).try_filter_map(|line_option| async move { Ok(line_option) });This refactoring makes use of
try_filter_mapto handle both filtering and error propagation more elegantly.src/queries_repository.rs (3)
Line range hint
7-23: Review the change to public visibility ofQueriestraitChanging the
Queriestrait frompub(crate)topubincreases its visibility to external crates. Ensure this is intentional and that exposing this trait aligns with your system's API design and encapsulation principles.
24-24: Confirm necessity of makingFlavourenum publicMaking the
Flavourenum public exposes it to external modules. Verify if this change is required and assess any potential impacts on your public API and maintainability.
Line range hint
194-289: Consider refactoring to reduce code duplication in query definitionsThe series of
.add_query(...)calls inUsersQueriesRepository::newhave similar structures, which may indicate code duplication. Refactor these query definitions to improve maintainability by utilizing loops or helper functions.Here's a refactored example using a loop:
pub fn new( vertices: i32, edges: i32, ) -> UsersQueriesRepository { let query_definitions = vec![ ("single_vertex_read", QueryType::Read, "MATCH (n:User {id : $id}) RETURN n", vec!["id"]), ("single_vertex_write", QueryType::Write, "CREATE (n:UserTemp {id : $id}) RETURN n", vec!["id"]), // Add other queries here ]; let mut builder = QueriesRepositoryBuilder::new(vertices, edges).flavour(Flavour::FalkorDB); for (name, query_type, text, params) in query_definitions { builder = builder.add_query(name, query_type, move |random, _flavour, rng| { let mut query_builder = QueryBuilder::new().text(text); for param in ¶ms { query_builder = query_builder.param(*param, random.random_vertex(rng)); } query_builder.build() }); } let queries_repository = builder.build(); UsersQueriesRepository { queries_repository } }src/metrics_collector.rs (5)
14-22: Review public exposure ofMetricsCollectorstructThe
MetricsCollectorstruct has been made public. Ensure that exposing this struct is necessary and that it doesn't leak internal implementation details. Consider if accessor methods or traits would be more appropriate for external interaction.
26-34: Check the need for publicPercentilestructMaking the
Percentilestruct public allows external modules to access it directly. Verify if this aligns with your intended API design and data encapsulation strategies.
38-45: Assess public visibility ofMachineMetadatastruct and itsnewmethodBy making
MachineMetadataand itsnewmethod public, system-specific details become accessible externally. Ensure this exposure doesn't pose security or privacy concerns and that it's essential for external functionality.[security]
Also applies to: 48-59
Line range hint
191-216: Refactormarkdown_reportfor improved readabilityThe
markdown_reportmethod constructs a markdown string with complex formatting logic. Consider breaking it into smaller helper functions or using a templating library to enhance readability and maintainability.
Line range hint
263-291: Ensure robust error handling inredis_to_query_infofunctionThe function may not handle all possible Redis response formats, leading to potential panics or unhandled errors. Implement comprehensive error checking and provide informative messages to handle unexpected data structures.
Would you like assistance in enhancing error handling for this function?
src/falkor_process.rs (1)
267-273: Improve error messages for better debuggingIn
redis_to_query_info, the error message for insufficient data may lack context. Enhance the error message to include details about the expected and actual data to aid in debugging.src/main.rs (2)
231-231: Use consistent logging witherror!macroReplace
eprintln!witherror!for consistent logging using thetracingcrate.Apply this diff:
- Err(e) => eprintln!("Task failed: {:?}", e), + Err(e) => error!("Task failed: {:?}", e),
253-253: Avoid unnecessary cloning of queriesSince
queriesis already cloned before being passed tospawn_worker, cloning it again insidespawn_workeris redundant.Apply this diff to remove redundant cloning:
- let queries = queries.clone();src/neo4j.rs (4)
Line range hint
43-49: Optimize client creation and consider connection management.The implementation has two potential improvements:
- Avoid unnecessary string cloning by using references
- Consider implementing connection pooling for better resource management
- pub async fn client(&self) -> BenchmarkResult<Neo4jClient> { - Neo4jClient::new( - self.uri.to_string(), - self.user.to_string(), - self.password.to_string(), - ) - .await + pub async fn client(&self) -> BenchmarkResult<Neo4jClient> { + Neo4jClient::new( + &self.uri, + &self.user, + &self.password, + ) + .await
Line range hint
90-113: Add validation for backup file existence.While the implementation includes proper safety checks, consider adding validation to ensure the backup file exists before attempting restoration.
pub async fn restore<'a>( &self, spec: Spec<'a>, ) -> BenchmarkResult<Output> { info!("Restoring DB"); if fs::metadata(&self.neo4j_pid()).await.is_ok() { return Err(OtherError( "Cannot restore DB because it is running.".to_string(), )); } - let command = self.neo4j_admin(); let backup_path = spec.backup_path(); + if !fs::metadata(&backup_path).await.is_ok() { + return Err(OtherError( + format!("Backup file not found at: {}", backup_path) + )); + } + let command = self.neo4j_admin();
Line range hint
114-146: Add timeout mechanism to prevent infinite loops.The cleanup retry logic could potentially run indefinitely. Consider adding a timeout mechanism or maximum retry count.
pub async fn clean_db(&self) -> BenchmarkResult<Output> { info!("cleaning DB"); + let max_retries = 5; + let mut attempts = 0; loop { + if attempts >= max_retries { + return Err(OtherError("Failed to clean DB after maximum retries".to_string())); + } + attempts += 1; if fs::metadata(&self.neo4j_pid()).await.is_ok() { info!("stopping neo4j before deleting the databases"); self.stop(false).await?;
Line range hint
36-146: Review architectural implications of expanded public API.The change from
pub(crate)topubfor multiple database operations significantly expands the public API surface. While this might be necessary for prometheus-based monitoring, consider:
- Implementing a facade pattern to expose only necessary operations
- Adding comprehensive access controls
- Documenting the security implications for operators
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
⛔ Files ignored due to path filters (1)
Cargo.lockis excluded by!**/*.lock
📒 Files selected for processing (16)
Cargo.toml(1 hunks)src/bin/falkor_process_main.rs(1 hunks)src/cli.rs(3 hunks)src/compare_template.rs(1 hunks)src/falkor.rs(4 hunks)src/falkor_process.rs(1 hunks)src/lib.rs(1 hunks)src/main.rs(9 hunks)src/metrics_collector.rs(6 hunks)src/neo4j.rs(4 hunks)src/neo4j_client.rs(4 hunks)src/prometheus_endpoint.rs(1 hunks)src/queries_repository.rs(4 hunks)src/query.rs(1 hunks)src/scenario.rs(2 hunks)src/utils.rs(11 hunks)
🚧 Files skipped from review as they are similar to previous changes (2)
- src/prometheus_endpoint.rs
- src/falkor.rs
🔇 Additional comments (15)
src/compare_template.rs (1)
8-9: Verify the necessity of changing structs' visibility to pub
The visibility of CompareTemplate and CompareRuns has been changed from pub(crate) to pub, making them accessible outside the crate. Ensure that exposing these structs publicly is intentional and does not expose internal implementation details that should remain encapsulated.
Also applies to: 13-15
Cargo.toml (1)
42-45: Update hyper dependency to the latest version 1.5.1
As previously noted, the hyper dependency is at version 0.14.31. It's recommended to upgrade to the latest stable version 1.5.1 to benefit from performance improvements and bug fixes.
src/cli.rs (1)
72-80: Ensure clarity and appropriateness of the parallel argument
The parallel argument defaults to 1. Verify that this default value aligns with expected usage patterns. Additionally, confirm that the help message clearly explains how this parameter affects the benchmark execution.
src/neo4j_client.rs (1)
Line range hint 32-46: Verify the necessity of changing method visibility to pub
The methods graph_size, execute_query_iterator, execute_query, and execute_query_stream have been changed from pub(crate) to pub, making them publicly accessible outside the crate. Ensure that making these methods public is required and does not unintentionally expose internal implementation details or increase the public API surface unnecessarily.
Also applies to: 51-93, 95-103, 105-131
src/query.rs (1)
Line range hint 54-61: Confirm if to_cypher_string method should be public
The method to_cypher_string in QueryParam has its visibility changed from pub(crate) to pub. Verify that this change is intentional and necessary for usage outside the crate, and that it doesn't expose internal logic that should remain encapsulated.
src/utils.rs (1)
Line range hint 22-31: Assess the need for making utility functions public
Several utility functions have changed visibility from pub(crate) to pub, including:
spawn_commandfile_existsdelete_filefalkor_shared_lib_pathcreate_directory_if_not_existsurl_file_namedownload_fileread_lineskill_processget_command_pidping_rediswait_for_redis_readyredis_savewrite_to_fileformat_number
Please verify that exposing these functions publicly is necessary for external use cases and that it does not compromise encapsulation or module boundaries. If these functions are intended for internal use only, consider keeping them with pub(crate) visibility to limit their exposure.
Also applies to: 43-45, 46-52, 54-60, 62-69, 71-73, 75-104, 106-133, 136-143, 145-187, 189-203, 205-234, 236-249, 251-258, 260-268
src/queries_repository.rs (1)
77-80: Assess the need for public visibility of flavour method
The flavour method in QueriesRepositoryBuilder is now public. Confirm whether this method needs to be accessible outside the crate. If so, consider providing documentation to guide external users.
src/metrics_collector.rs (2)
Line range hint 79-94: Verify necessity of public MetricsCollector::new method
The new method for MetricsCollector is now public. Confirm that external crates require direct instantiation of MetricsCollector, or consider using a factory pattern if controlled creation is preferred.
Line range hint 146-154: Handle potential file I/O errors in save method
In the save method, file operations may fail due to I/O errors or permission issues. Ensure that these errors are properly handled and communicated to the caller for robust error management.
src/main.rs (4)
37-37:
Add error handling for Prometheus endpoint initialization.
The Prometheus endpoint initialization should handle potential errors (e.g., port already in use).
Apply this diff:
- let prometheus_endpoint = benchmark::prometheus_endpoint::PrometheusEndpoint::new();
+ let prometheus_endpoint = benchmark::prometheus_endpoint::PrometheusEndpoint::new()
+ .map_err(|e| OtherError(format!("Failed to initialize Prometheus endpoint: {}", e)))?;190-190: 🛠️ Refactor suggestion
Validate the parallel parameter to prevent potential issues.
Ensure that the parallel parameter is greater than zero to avoid division by zero or spawning zero workers.
Apply this diff to add parameter validation:
async fn run_falkor(
size: Size,
number_of_queries: u64,
parallel: usize,
) -> BenchmarkResult<()> {
+ if parallel == 0 {
+ return Err(OtherError("Parallelism level must be greater than zero.".to_string()));
+ }220-224:
Distribute queries among workers to avoid redundant executions.
Currently, each worker receives the entire set of queries, leading to duplicate processing. Modify the code to partition the queries so each worker processes a unique subset.
Apply this diff to distribute queries evenly:
for spawn_id in 0..parallel {
- let queries = queries.clone();
+ let chunk_size = (queries.len() + parallel - 1) / parallel;
+ let start_idx = spawn_id * chunk_size;
+ let end_idx = usize::min(start_idx + chunk_size, queries.len());
+ let queries_chunk = queries[start_idx..end_idx].to_vec();
- let handle = spawn_worker(&mut falkor, queries, spawn_id).await?;
+ let handle = spawn_worker(&falkor, queries_chunk, spawn_id).await?;
handles.push(handle);
}248-248:
Avoid sharing mutable references across asynchronous tasks.
Passing &mut falkor to multiple asynchronous tasks can cause concurrency issues. Instead, use immutable references or clone the Falkor<Started> instance for each worker to ensure thread safety.
Apply this diff to prevent data races:
-async fn spawn_worker(
- falkor: &mut Falkor<Started>,
+async fn spawn_worker(
+ falkor: &Falkor<Started>,
queries: Vec<(String, QueryType, String)>,
spawn_id: usize,
) -> BenchmarkResult<JoinHandle<()>> {
// ...
- let mut graph = falkor.client().await?;
+ let mut graph = falkor.clone().client().await?;
// ...
}src/neo4j.rs (2)
36-40: Consider security implications of public database restoration.
Making the database restoration capability publicly accessible could pose security risks. Additionally, this wrapper method seems to only delegate to restore() without additional logic, suggesting potential unnecessary abstraction.
Line range hint 64-89: LGTM! Verify dump path handling across different environments.
The implementation includes proper error handling, safety checks, and command execution. The backup path handling looks correct but should be verified across different environments.
✅ Verification successful
Let me gather more information about the backup path construction and validation.
LGTM! The backup path handling is properly implemented and secure.
The verification shows that:
- Backup paths are constructed safely using
Spec::backup_path()which creates paths under./backups/{vendor}/{name}/{size} - Directory creation is handled safely via
create_directory_if_not_exists - Path handling uses proper filesystem operations and error handling
- No path traversal vulnerabilities are present as paths are constructed from validated struct fields
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Check for potential path traversal vulnerabilities in backup path handling
rg -A 3 "backup_path|to-path"
# Verify the dump command usage patterns
ast-grep --pattern 'dump($$$)'
Length of output: 1783
Script:
#!/bin/bash
# Check for path validation and directory creation
ast-grep --pattern 'create_directory_if_not_exists($$$)'
# Check Spec struct definition and implementation
rg -A 5 "struct Spec"
# Check for any path sanitization or validation
rg -A 3 "path|sanitize|validate"
Length of output: 9987
src/bin/falkor_process_main.rs
Outdated
| info!("Falkor process started waiting 30 seconds"); | ||
| tokio::time::sleep(tokio::time::Duration::from_secs(3)).await; |
There was a problem hiding this comment.
Fix inconsistency between log message and sleep duration
The log message indicates a 30-second wait:
info!("Falkor process started waiting 30 seconds");However, the actual sleep duration is 3 seconds:
tokio::time::sleep(tokio::time::Duration::from_secs(3)).await;Consider updating the log message or adjusting the sleep duration to ensure consistency.
Apply one of the following diffs to resolve the inconsistency:
Option 1: Change the sleep duration to 30 seconds
tokio::time::sleep(tokio::time::Duration::from_secs(
- 3
+ 30
)).await;Option 2: Update the log message to reflect 3 seconds
info!("Falkor process started waiting
- 30
+ 3
seconds");
src/lib.rs
Outdated
| lazy_static! { | ||
| pub static ref OPERATION_COUNTER: CounterVec = register_counter_vec!( | ||
| "operations_total", | ||
| "Total number of operations processed", | ||
| &[ | ||
| "vendor", | ||
| "spawn_id", | ||
| "type", | ||
| "name", | ||
| "dataset", | ||
| "dataset_size" | ||
| ] | ||
| ) | ||
| .unwrap(); | ||
| pub static ref OPERATION_ERROR_COUNTER: CounterVec = register_counter_vec!( | ||
| "operations_error_total", | ||
| "Total number of operations failed", | ||
| &[ | ||
| "vendor", | ||
| "spawn_id", | ||
| "type", | ||
| "name", | ||
| "dataset", | ||
| "dataset_size" | ||
| ] | ||
| ) | ||
| .unwrap(); | ||
| } |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Handle potential panics when registering Prometheus metrics
Using .unwrap() on metric registration can cause a panic at runtime if registration fails. To prevent unexpected panics, consider using .expect() with a descriptive error message or handling the Result properly.
Apply the following diffs to improve error handling:
Update OPERATION_COUNTER metric registration
).unwrap();
+).expect("Failed to register OPERATION_COUNTER metric");Update OPERATION_ERROR_COUNTER metric registration
).unwrap();
+).expect("Failed to register OPERATION_ERROR_COUNTER metric");Committable suggestion skipped: line range outside the PR's diff.
Cargo.toml
Outdated
| prometheus = { version = "0.13.4", features = ["gen"] } | ||
| lazy_static = "1.5" | ||
| hyper = { version = "0.14.31", features = ["server", "runtime", "http1", "tcp"] } | ||
| libc = "0.2.161" |
There was a problem hiding this comment.
💡 Codebase verification
Update hyper and libc dependencies to their latest versions
The verification reveals:
prometheus(0.13.4) andlazy_static(1.5.0) are at their latest versions and have no security advisorieshyper(0.14.31) has a newer version 1.5.1 availablelibc(0.2.161) has a newer version 0.2.167 available- No security vulnerabilities exist in the current versions being used
While the current versions are secure, it's recommended to update to the latest versions for potential performance improvements and bug fixes:
- Update
hyper = { version = "1.5.1", features = ["server", "runtime", "http1", "tcp"] } - Update
libc = "0.2.167"
🔗 Analysis chain
Verify dependencies are up-to-date and secure
Ensure that the newly added dependencies are at their latest stable versions and are free from known vulnerabilities.
Run the following script to check the latest versions and security advisories of the added dependencies:
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check latest versions and security advisories for new dependencies
# List of new dependencies
crates=(prometheus lazy_static hyper libc)
# Check latest versions
echo "Checking latest versions..."
for crate in "${crates[@]}"; do
echo -n "$crate: "
curl -s "https://crates.io/api/v1/crates/$crate" | jq -r '.crate.max_stable_version'
done
# Check for security advisories
echo -e "\nChecking for security advisories..."
for crate in "${crates[@]}"; do
echo "=== $crate ==="
gh api graphql -f query='{
securityVulnerabilities(first: 5, ecosystem: RUST, package: "'$crate'") {
nodes {
advisory {
summary
severity
publishedAt
}
vulnerableVersionRange
firstPatchedVersion {
identifier
}
}
}
}'
done
Length of output: 3700
| pub name: Name, | ||
| pub vendor: Vendor, | ||
| pub size: Size, | ||
| pub vertices: u64, | ||
| pub edges: u64, |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Consider encapsulating Spec struct fields
Changing the fields name, vendor, size, vertices, and edges to pub exposes them directly. To maintain encapsulation and control over how these fields are accessed or modified, consider keeping them private and providing public getter methods if necessary.
src/falkor_process.rs
Outdated
| tokio::spawn(async move { | ||
| loop { | ||
| let mut state = arc_state.lock().await; | ||
|
|
||
| // Check if monitoring is disabled | ||
| if !state.should_monitor { | ||
| info!("Monitoring stopped; exiting loop."); | ||
| break; | ||
| } | ||
| let child_lock = &mut state.child; | ||
| match child_lock.try_wait() { | ||
| Ok(Some(status)) => { | ||
| info!("falkor process exited with status: {:?}", status); | ||
| match Self::spawn_process().await { | ||
| Ok(new_child) => { | ||
| *child_lock = new_child; | ||
| info!("Restarted falkor process with PID: {:?}", child_lock.id()); | ||
| } | ||
| Err(e) => { | ||
| error!("Failed to restart falkor process: {:?}", e); | ||
| break; | ||
| } | ||
| } | ||
| } | ||
| Ok(None) => { | ||
| info!("falkor process is running with PID: {:?}", child_lock.id()); | ||
| } | ||
| Err(e) => { | ||
| error!("Failed to check falkor process status: {:?}", e); | ||
| break; | ||
| } | ||
| } | ||
|
|
||
| tokio::time::sleep(tokio::time::Duration::from_secs(1)).await; | ||
| } |
There was a problem hiding this comment.
Avoid holding a mutex across await points in monitor_process
In monitor_process, the mutex lock on state is held across async boundaries, including the tokio::time::sleep call. This can cause deadlocks or prevent other tasks from acquiring the lock. Refactor to minimize the lock scope.
Here's a refactored snippet:
fn monitor_process(arc_state: Arc<Mutex<State>>) -> JoinHandle<()> {
tokio::spawn(async move {
loop {
let should_monitor;
let mut child_status = None;
{
let mut state = arc_state.lock().await;
should_monitor = state.should_monitor;
match state.child.try_wait() {
Ok(Some(status)) => {
child_status = Some(status);
}
Ok(None) => {
// Process is still running
}
Err(e) => {
error!("Failed to check falkor process status: {:?}", e);
break;
}
}
}
if !should_monitor {
info!("Monitoring stopped; exiting loop.");
break;
}
if let Some(status) = child_status {
info!("falkor process exited with status: {:?}", status);
match Self::spawn_process().await {
Ok(new_child) => {
let mut state = arc_state.lock().await;
state.child = new_child;
info!("Restarted falkor process with PID: {:?}", state.child.id());
}
Err(e) => {
error!("Failed to restart falkor process: {:?}", e);
break;
}
}
}
tokio::time::sleep(tokio::time::Duration::from_secs(1)).await;
}
})
}
src/falkor_process.rs
Outdated
| tokio::spawn(async move { | ||
| loop { | ||
| let state = arc_state.lock().await; | ||
| if !state.should_monitor { | ||
| info!("Monitoring server stopped; exiting loop."); | ||
| break; | ||
| } | ||
| match Self::monitor_server_once().await { | ||
| Ok(_) => {} | ||
| Err(e) => { | ||
| error!("Failed to monitor server: {:?}", e); | ||
| // break; | ||
| } | ||
| } | ||
| tokio::time::sleep(tokio::time::Duration::from_secs(1)).await; | ||
| } |
There was a problem hiding this comment.
Minimize mutex lock scope in monitor_server
Similar to monitor_process, avoid holding the mutex lock across await points in monitor_server. This prevents potential deadlocks and allows other tasks to access the mutex.
src/falkor_process.rs
Outdated
| fn drop(&mut self) { | ||
| info!("Dropping FalkorProcess"); | ||
| let rt = tokio::runtime::Runtime::new().unwrap(); | ||
| match rt.block_on(async { self.terminate().await }) { | ||
| Ok(_) => { | ||
| info!("FalkorProcess terminated successfully"); | ||
| } | ||
| Err(_) => { | ||
| error!("Failed to terminate FalkorProcess"); | ||
| } | ||
| } | ||
| } |
There was a problem hiding this comment.
Avoid creating a Tokio runtime in Drop implementation
Creating a new Tokio runtime within Drop can lead to unexpected behavior or panics, especially if the executor is already running or during a global shutdown. Consider requiring explicit termination or leveraging existing runtimes.
Would you like help refactoring the cleanup process to avoid creating a runtime in the Drop implementation?
src/falkor_process.rs
Outdated
| let mut state_lock = self.state.lock().await; | ||
|
|
||
| // Set should_monitor to false in order to prevent restarting | ||
| state_lock.should_monitor = false; | ||
|
|
||
| if let Some(pid) = state_lock.child.id() { | ||
| let pid = Pid::from_raw(pid as i32); | ||
|
|
||
| // Send SIGTERM signal to request graceful termination | ||
| match kill(pid, Signal::SIGTERM) { | ||
| Ok(_) => { | ||
| info!("Sent SIGTERM signal to falkor process with PID: {}", pid); | ||
|
|
||
| // Optionally wait for the process to exit | ||
| if let Err(e) = tokio::time::timeout( | ||
| std::time::Duration::from_secs(60), | ||
| state_lock.child.wait(), | ||
| ) | ||
| .await | ||
| { | ||
| error!( | ||
| "Timed out waiting for falkor process with PID: {} to exit: {:?}", | ||
| pid, e | ||
| ); | ||
| } else { | ||
| info!("Falkor process with PID: {} exited successfully", pid); | ||
| } | ||
| } | ||
| Err(e) => error!( | ||
| "Failed to send SIGTERM signal to falkor process: {:?}, with PID: {}", | ||
| e, pid | ||
| ), | ||
| } | ||
| } else { | ||
| error!("Failed to get PID of falkor process"); | ||
| } | ||
|
|
||
| // waiting for each handle in state_lock.handles | ||
| // for handle in state_lock.handles.drain(..) { | ||
| // if let Err(e) = handle.await { | ||
| // error!("Failed to wait for handle: {:?}", e); | ||
| // } | ||
| // } | ||
| Ok(()) | ||
| } |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Wait for monitoring tasks to finish upon termination
In the terminate method, the code to wait for monitoring tasks is commented out. To ensure graceful shutdown, uncomment and implement proper task awaiting to prevent resource leaks.
Apply this change:
// waiting for each handle in state_lock.handles
-for handle in state_lock.handles.drain(..) {
- if let Err(e) = handle.await {
- error!("Failed to wait for handle: {:?}", e);
- }
-}
+for handle in state_lock.handles.drain(..) {
+ match handle.await {
+ Ok(_) => info!("Monitoring task completed successfully."),
+ Err(e) => error!("Failed to wait for handle: {:?}", e),
+ }
+}📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| let mut state_lock = self.state.lock().await; | |
| // Set should_monitor to false in order to prevent restarting | |
| state_lock.should_monitor = false; | |
| if let Some(pid) = state_lock.child.id() { | |
| let pid = Pid::from_raw(pid as i32); | |
| // Send SIGTERM signal to request graceful termination | |
| match kill(pid, Signal::SIGTERM) { | |
| Ok(_) => { | |
| info!("Sent SIGTERM signal to falkor process with PID: {}", pid); | |
| // Optionally wait for the process to exit | |
| if let Err(e) = tokio::time::timeout( | |
| std::time::Duration::from_secs(60), | |
| state_lock.child.wait(), | |
| ) | |
| .await | |
| { | |
| error!( | |
| "Timed out waiting for falkor process with PID: {} to exit: {:?}", | |
| pid, e | |
| ); | |
| } else { | |
| info!("Falkor process with PID: {} exited successfully", pid); | |
| } | |
| } | |
| Err(e) => error!( | |
| "Failed to send SIGTERM signal to falkor process: {:?}, with PID: {}", | |
| e, pid | |
| ), | |
| } | |
| } else { | |
| error!("Failed to get PID of falkor process"); | |
| } | |
| // waiting for each handle in state_lock.handles | |
| // for handle in state_lock.handles.drain(..) { | |
| // if let Err(e) = handle.await { | |
| // error!("Failed to wait for handle: {:?}", e); | |
| // } | |
| // } | |
| Ok(()) | |
| } | |
| let mut state_lock = self.state.lock().await; | |
| // Set should_monitor to false in order to prevent restarting | |
| state_lock.should_monitor = false; | |
| if let Some(pid) = state_lock.child.id() { | |
| let pid = Pid::from_raw(pid as i32); | |
| // Send SIGTERM signal to request graceful termination | |
| match kill(pid, Signal::SIGTERM) { | |
| Ok(_) => { | |
| info!("Sent SIGTERM signal to falkor process with PID: {}", pid); | |
| // Optionally wait for the process to exit | |
| if let Err(e) = tokio::time::timeout( | |
| std::time::Duration::from_secs(60), | |
| state_lock.child.wait(), | |
| ) | |
| .await | |
| { | |
| error!( | |
| "Timed out waiting for falkor process with PID: {} to exit: {:?}", | |
| pid, e | |
| ); | |
| } else { | |
| info!("Falkor process with PID: {} exited successfully", pid); | |
| } | |
| } | |
| Err(e) => error!( | |
| "Failed to send SIGTERM signal to falkor process: {:?}, with PID: {}", | |
| e, pid | |
| ), | |
| } | |
| } else { | |
| error!("Failed to get PID of falkor process"); | |
| } | |
| // waiting for each handle in state_lock.handles | |
| for handle in state_lock.handles.drain(..) { | |
| match handle.await { | |
| Ok(_) => info!("Monitoring task completed successfully."), | |
| Err(e) => error!("Failed to wait for handle: {:?}", e), | |
| } | |
| } | |
| Ok(()) | |
| } |
There was a problem hiding this comment.
Actionable comments posted: 7
🧹 Outside diff range and nitpick comments (11)
src/lib.rs (1)
32-44: Consider reducing label cardinality for OPERATION_ERROR_COUNTERHigh cardinality metrics (many label combinations) can impact Prometheus performance. Consider if all labels are necessary for error tracking.
Consider removing less critical labels or combining some labels to reduce cardinality. For example,
datasetanddataset_sizecould be combined into a single label.Also, improve error handling:
pub static ref OPERATION_ERROR_COUNTER: CounterVec = register_counter_vec!( "operations_error_total", "Total number of operations failed", &[ "vendor", "spawn_id", "type", "name", - "dataset", - "dataset_size" + "dataset_info" ] ) -.unwrap(); +.expect("Failed to register operations_error_total counter");Cargo.toml (1)
48-54: Consider organizing binary targets at the top of the fileBinary targets are typically declared before dependencies for better readability.
Move the
[[bin]]sections before the[dependencies]section.src/bin/falkor_process_main.rs (3)
38-53: Remove commented-out codeLarge blocks of commented code should be removed if they're no longer needed. If this code might be needed later, consider tracking it in version control or as a separate feature branch.
Remove the commented-out Redis ping code.
41-41: Extract magic numbers into constantsThe loop iteration count (300000) and sleep duration (10 seconds) should be configurable constants.
Add constants at the top of the file:
+const MAX_ITERATIONS: u32 = 300_000; +const SLEEP_DURATION_SECS: u64 = 10; + #[tokio::main] async fn main() -> BenchmarkResult<()> { // ... existing code ... - for _ in 0..300000 { + for _ in 0..MAX_ITERATIONS { // ... existing code ... - tokio::time::sleep(tokio::time::Duration::from_secs(10)).await; + tokio::time::sleep(tokio::time::Duration::from_secs(SLEEP_DURATION_SECS)).await; }Also applies to: 71-71
54-59: Add timeout configuration and error handling for graph queryThe query timeout is hardcoded and error handling could be improved.
Consider these improvements:
+const QUERY_TIMEOUT_MS: u64 = 5000; + let nodes = graph .query("MATCH(n) RETURN count(n) as nodeCount") - .with_timeout(5000) + .with_timeout(QUERY_TIMEOUT_MS) .execute() - .await; + .await + .map_err(|e| { + info!("Query failed: {:?}", e); + e + })?;readme.md (1)
76-77: Add protocol and setup context for monitoring URLsThe URLs should include the protocol (http://) and some context about how to set up and access these monitoring endpoints.
-Accessing grafana http://localhost:3000 -Accessing prometheus http://localhost:9090 +### Monitoring Setup + +The benchmark tool provides monitoring capabilities through: + +- Grafana Dashboard: [http://localhost:3000](http://localhost:3000) +- Prometheus Metrics: [http://localhost:9090](http://localhost:9090) + +Ensure these services are running before accessing the endpoints.🧰 Tools
🪛 Markdownlint (0.35.0)
76-76: null
Bare URL used(MD034, no-bare-urls)
77-77: null
Bare URL used(MD034, no-bare-urls)
src/falkor.rs (1)
21-28: Consider using a proper state machine patternThe current implementation uses separate structs for states but could benefit from a more robust state machine pattern.
Consider using the
derive_state_machine_futurecrate or implementing a proper state machine pattern to handle state transitions more safely and explicitly.src/falkor_process.rs (1)
297-341: Improve Redis value parsing robustnessThe Redis value parsing implementation could be more robust and maintainable.
- Use type-safe parsing
- Implement proper error context
- Add value validation
- Consider using serde for parsing
-fn redis_value_as_string(value: redis::Value) -> BenchmarkResult<String> { +fn redis_value_as_string(value: redis::Value) -> BenchmarkResult<String> { + use redis::Value::*; + match value { - redis::Value::BulkString(data) => String::from_utf8(data.clone()) - .map_err(|_| OtherError(format!("parsing string failed: {:?}", data))), - redis::Value::SimpleString(data) => Ok(data), - redis::Value::VerbatimString { format: _, text } => Ok(text), - _ => Err(OtherError(format!("parsing string failed: {:?}", value))), + BulkString(data) => String::from_utf8(data) + .map_err(|e| OtherError(format!("Invalid UTF-8 in bulk string: {}", e))), + SimpleString(data) => Ok(data), + VerbatimString { format, text } => { + if !is_valid_format(&format) { + return Err(OtherError(format!("Invalid string format: {}", format))); + } + Ok(text) + } + other => Err(OtherError(format!("Expected string, got: {:?}", other))), } }dashboards/falkor_dashboard.json (3)
2-17: Add dashboard variables for better flexibilityConsider adding template variables for:
- Instance selection (
redis-exporter:9121)- Job filter (
falkor_benchmark)
This would make the dashboard more reusable across different environments."templating": { "list": [ + { + "name": "instance", + "type": "query", + "datasource": "Prometheus", + "query": "label_values(redis_up, instance)" + }, + { + "name": "job", + "type": "query", + "datasource": "Prometheus", + "query": "label_values(operations_total, job)" + } ] },
384-384: Adjust rate calculation window for better stabilityThe 1-minute window for irate might be too short for low-traffic scenarios, leading to spiky graphs.
- "expr": "topk(5, irate(redis_commands_total{instance=~\"redis-exporter:9121\"} [1m]))", + "expr": "topk(5, rate(redis_commands_total{instance=~\"redis-exporter:9121\"} [5m]))",
1005-1008: Adjust default time range for better contextA 5-minute default time range might be too short for effective troubleshooting and trend analysis.
"time": { - "from": "now-5m", + "from": "now-1h", "to": "now" },
📜 Review details
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Review profile: CHILL
⛔ Files ignored due to path filters (1)
Cargo.lockis excluded by!**/*.lock
📒 Files selected for processing (9)
.gitignore(1 hunks)Cargo.toml(2 hunks)dashboards/falkor_dashboard.json(1 hunks)readme.md(1 hunks)src/bin/falkor_process_main.rs(1 hunks)src/falkor.rs(4 hunks)src/falkor_process.rs(1 hunks)src/lib.rs(1 hunks)src/utils.rs(11 hunks)
✅ Files skipped from review due to trivial changes (1)
- .gitignore
🚧 Files skipped from review as they are similar to previous changes (1)
- src/utils.rs
🧰 Additional context used
🪛 Markdownlint (0.35.0)
readme.md
74-74: Expected: setext; Actual: atx
Heading style
(MD003, heading-style)
76-76: null
Bare URL used
(MD034, no-bare-urls)
77-77: null
Bare URL used
(MD034, no-bare-urls)
🔇 Additional comments (9)
src/lib.rs (1)
18-31: 🛠️ Refactor suggestion
Improve error handling and documentation for OPERATION_COUNTER
The metric registration uses unwrap() which could cause panics at runtime. Additionally, the metric could benefit from more detailed documentation.
Apply this diff:
pub static ref OPERATION_COUNTER: CounterVec = register_counter_vec!(
"operations_total",
- "Total number of operations processed",
+ "Total number of operations processed, labeled by vendor, operation type, and dataset characteristics",
&[
"vendor",
"spawn_id",
"type",
"name",
"dataset",
"dataset_size"
]
)
-.unwrap();
+.expect("Failed to register operations_total counter");Likely invalid or redundant comment.
Cargo.toml (1)
42-45: Update hyper to latest version
readme.md (1)
78-95: 🛠️ Refactor suggestion
Enhance documentation structure for Prometheus queries
The Prometheus queries section would benefit from better organization and context.
-sum by (vendor, spawn_id) (rate(operations_total{vendor="falkor"}[1m]))
-redis
-rate(redis_commands_processed_total{instance=~"redis-exporter:9121"}[1m])
-redis_connected_clients{instance=~"redis-exporter:9121"}
-topk(5, irate(redis_commands_total{instance=~"redis-exporter:9121"} [1m]))
-redis_blocked_clients
-redis_commands_total
-redis_commands_failed_calls_total
-redis_commands_latencies_usec_count
-redis_commands_rejected_calls_total
-redis_io_threaded_reads_processed
-redis_io_threaded_writes_processed
-redis_io_threads_active
-redis_memory_max_bytes
-redis_memory_used_bytes
-redis_memory_used_peak_bytes
-redis_memory_used_vm_total
-redis_process_id
+#### Benchmark Performance Metrics
+
+##### Operation Rates
+```promql
+# Total operations per minute by vendor and spawn ID
+sum by (vendor, spawn_id) (rate(operations_total{vendor="falkor"}[1m]))
+```
+
+#### Redis Server Metrics
+
+##### Command Processing
+```promql
+# Command processing rate
+rate(redis_commands_processed_total{instance=~"redis-exporter:9121"}[1m])
+
+# Top 5 most frequent commands
+topk(5, irate(redis_commands_total{instance=~"redis-exporter:9121"} [1m]))
+
+# Failed and rejected commands
+redis_commands_failed_calls_total
+redis_commands_rejected_calls_total
+redis_commands_latencies_usec_count
+```
+
+##### Client Connections
+```promql
+# Active client connections
+redis_connected_clients{instance=~"redis-exporter:9121"}
+
+# Blocked clients
+redis_blocked_clients
+```
+
+##### I/O Operations
+```promql
+# I/O thread metrics
+redis_io_threaded_reads_processed
+redis_io_threaded_writes_processed
+redis_io_threads_active
+```
+
+##### Memory Usage
+```promql
+# Memory utilization
+redis_memory_max_bytes
+redis_memory_used_bytes
+redis_memory_used_peak_bytes
+redis_memory_used_vm_total
+```
+
+##### Process Information
+```promql
+# Redis process ID
+redis_process_id
+```src/falkor.rs (2)
188-254: 🛠️ Refactor suggestion
Improve error handling and metrics in query execution
The query execution code has several areas for improvement:
- Add timeout configuration
- Implement circuit breaker pattern
- Add more detailed metrics
- Improve error context
pub async fn execute_query<'a>(
&'a mut self,
spawn_id: &'a str,
query_name: &'a str,
query: &'a str,
) -> BenchmarkResult<()> {
+ let start = std::time::Instant::now();
OPERATION_COUNTER
.with_label_values(&["falkor", spawn_id, "", query_name, "", ""])
.inc();
- let falkor_result = self.graph.query(query).with_timeout(5000).execute().await;
+ let falkor_result = self.graph
+ .query(query)
+ .with_timeout(self.config.timeout)
+ .execute()
+ .await;
+ QUERY_DURATION_HISTOGRAM
+ .with_label_values(&["falkor", query_name])
+ .observe(start.elapsed().as_secs_f64());
Self::read_reply(spawn_id, query_name, query, falkor_result)
}Likely invalid or redundant comment.
121-130: 🛠️ Refactor suggestion
Parameterize connection details and add connection pooling
The client implementation has hardcoded connection details and uses a fixed number of connections.
- pub async fn client(&self) -> BenchmarkResult<FalkorBenchmarkClient> {
- let connection_info = "falkor://127.0.0.1:6379".try_into()?;
+ pub async fn client(&self, config: ClientConfig) -> BenchmarkResult<FalkorBenchmarkClient> {
+ let connection_info = config.connection_string.try_into()?;
let client = FalkorClientBuilder::new_async()
.with_connection_info(connection_info)
- .with_num_connections(nonzero::nonzero!(1u8))
+ .with_num_connections(config.pool_size)
.build()
.await?;
Ok(FalkorBenchmarkClient {
- graph: client.select_graph("falkor"),
+ graph: client.select_graph(&config.graph_name),
})
}Likely invalid or redundant comment.
dashboards/falkor_dashboard.json (4)
93-93: Improve uptime metric calculation
The current uptime calculation using max_over_time with $__interval might miss data points.
- "expr": "max(max_over_time(redis_uptime_in_seconds{instance=~\"redis-exporter:9121\"}[$__interval]))",
+ "expr": "time() - process_start_time_seconds{instance=~\"redis-exporter:9121\"}",502-503: Enhance latency metric visualization
The current latency metric might not provide accurate percentiles.
- "expr": "redis_commands_latencies_usec_count",
- "legendFormat": "{{ cmd }}",
+ "expr": "histogram_quantile(0.95, sum(rate(redis_commands_duration_seconds_bucket[5m])) by (le, cmd))",
+ "legendFormat": "p95 {{ cmd }}",710-802: Remove duplicate queries/sec panel
There are two nearly identical panels showing queries/sec metrics.
Consider removing this duplicate panel and keeping the one at lines 617-709.
891-891: 🛠️ Refactor suggestion
Improve error metric calculation
The current error metric shows total errors, which makes it harder to spot trends.
- "expr": "sum by (vendor) (operations_error_total{vendor=\"falkor\"})",
+ "expr": "sum by (vendor) (rate(operations_error_total{vendor=\"falkor\"}[5m]))",Likely invalid or redundant comment.
src/lib.rs
Outdated
| pub static ref FALKOR_RESTART_COUNTER: Counter = register_counter!( | ||
| "falkordb_restarts_total", | ||
| "Total number of restart for falkordb server", | ||
| ) | ||
| .unwrap(); | ||
| } |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Fix metric name and improve error handling for FALKOR_RESTART_COUNTER
The metric name should follow Prometheus naming conventions with an underscore separator.
Apply this diff:
pub static ref FALKOR_RESTART_COUNTER: Counter = register_counter!(
- "falkordb_restarts_total",
+ "falkordb_server_restarts_total",
"Total number of restart for falkordb server",
)
-.unwrap();
+.expect("Failed to register falkordb_server_restarts_total counter");📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| pub static ref FALKOR_RESTART_COUNTER: Counter = register_counter!( | |
| "falkordb_restarts_total", | |
| "Total number of restart for falkordb server", | |
| ) | |
| .unwrap(); | |
| } | |
| pub static ref FALKOR_RESTART_COUNTER: Counter = register_counter!( | |
| "falkordb_server_restarts_total", | |
| "Total number of restart for falkordb server", | |
| ) | |
| .expect("Failed to register falkordb_server_restarts_total counter"); | |
| } |
Cargo.toml
Outdated
| #falkordb = { version = "0.1.6", features = ["tokio"] } | ||
| falkordb = { path = "/Users/barak/dev/falkordb-rs", features = ["tokio", "tracing"] } |
There was a problem hiding this comment.
Replace local path dependency with versioned dependency
Using a local path dependency is not suitable for production and will prevent others from building the project.
Replace the local path with a versioned dependency:
-#falkordb = { version = "0.1.6", features = ["tokio"] }
-falkordb = { path = "/Users/barak/dev/falkordb-rs", features = ["tokio", "tracing"] }
+falkordb = { version = "0.1.6", features = ["tokio", "tracing"] }📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| #falkordb = { version = "0.1.6", features = ["tokio"] } | |
| falkordb = { path = "/Users/barak/dev/falkordb-rs", features = ["tokio", "tracing"] } | |
| falkordb = { version = "0.1.6", features = ["tokio", "tracing"] } |
src/bin/falkor_process_main.rs
Outdated
| if let Ok(shutdown_result) = shutdown_redis().await { | ||
| info!("Redis shutdown result: {}", shutdown_result); | ||
| info!("Falkor process started waiting 3 seconds"); | ||
| tokio::time::sleep(tokio::time::Duration::from_secs(3)).await; | ||
| } |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Remove duplicate sleep and log statements
The same sleep and log message appears twice in the code.
Keep only one instance of the sleep and log message after the Redis shutdown.
Also applies to: 22-23
src/falkor.rs
Outdated
| pub async fn clean_db(&self) -> BenchmarkResult<()> { | ||
| info!("deleting: {}", REDIS_DUMP_FILE); | ||
| delete_file(REDIS_DUMP_FILE).await?; | ||
| Ok(()) | ||
| } | ||
|
|
||
| pub async fn save_db( | ||
| &self, | ||
| size: Size, | ||
| ) -> BenchmarkResult<()> { | ||
| if let Ok(pid) = self.get_redis_pid().await { | ||
| Err(OtherError(format!( | ||
| "Can't save the dump file: {}, while falkor is running", | ||
| pid | ||
| ))) | ||
| } else { | ||
| let target = format!( | ||
| "{}/{}_dump.rdb", | ||
| REDIS_DATA_DIR, | ||
| size.to_string().to_lowercase() | ||
| ); | ||
| info!( | ||
| "saving redis dump file {} to {}", | ||
| REDIS_DUMP_FILE, | ||
| target.as_str() | ||
| ); | ||
| fs::copy(REDIS_DUMP_FILE, target.as_str()).await?; | ||
| Ok(()) | ||
| } | ||
| } |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Add error recovery mechanism for database operations
The database operations (clean_db and save_db) could benefit from retry mechanisms and better error recovery.
Consider implementing:
- Retry mechanism for transient failures
- Backup creation before destructive operations
- Validation of saved files
src/falkor_process.rs
Outdated
| fn monitor_process(arc_state: Arc<Mutex<State>>) -> JoinHandle<()> { | ||
| tokio::spawn(async move { | ||
| loop { | ||
| let mut state = arc_state.lock().await; | ||
|
|
||
| // Check if monitoring is disabled | ||
| if !state.should_monitor { | ||
| info!("Monitoring stopped; exiting loop."); | ||
| break; | ||
| } | ||
| let child_lock = &mut state.child; | ||
| match child_lock.try_wait() { | ||
| Ok(Some(status)) => { | ||
| info!("falkor process exited with status: {:?}", status); | ||
| match Self::spawn_process().await { | ||
| Ok(new_child) => { | ||
| *child_lock = new_child; | ||
| info!("Restarted falkor process with PID: {:?}", child_lock.id()); | ||
| FALKOR_RESTART_COUNTER.inc(); | ||
| } | ||
| Err(e) => { | ||
| error!("Failed to restart falkor process: {:?}", e); | ||
| break; | ||
| } | ||
| } | ||
| } | ||
| Ok(None) => { | ||
| // info!("falkor process is running with PID: {:?}", child_lock.id()); | ||
| } | ||
| Err(e) => { | ||
| error!("Failed to check falkor process status: {:?}", e); | ||
| break; | ||
| } | ||
| } | ||
|
|
||
| tokio::time::sleep(tokio::time::Duration::from_secs(1)).await; | ||
| } | ||
| }) | ||
| } |
There was a problem hiding this comment.
Improve process monitoring robustness
The process monitoring implementation holds mutex lock across await points and lacks proper error recovery.
- Minimize mutex lock scope
- Add exponential backoff for restarts
- Implement proper error recovery
fn monitor_process(arc_state: Arc<Mutex<State>>) -> JoinHandle<()> {
tokio::spawn(async move {
+ let mut backoff = ExponentialBackoff::default();
loop {
- let mut state = arc_state.lock().await;
+ let should_monitor = {
+ let state = arc_state.lock().await;
+ state.should_monitor
+ };
- if !state.should_monitor {
+ if !should_monitor {
info!("Monitoring stopped; exiting loop.");
break;
}
- let child_lock = &mut state.child;
- match child_lock.try_wait() {
+
+ let process_status = {
+ let mut state = arc_state.lock().await;
+ state.child.try_wait()
+ };
+
+ match process_status {Committable suggestion skipped: line range outside the PR's diff.
src/falkor_process.rs
Outdated
| pub async fn terminate(&mut self) -> BenchmarkResult<()> { | ||
| info!("Terminating FalkorProcess"); | ||
| // Lock the state mutex to access the child process | ||
| let mut state_lock = self.state.lock().await; | ||
|
|
||
| // Set should_monitor to false in order to prevent restarting | ||
| state_lock.should_monitor = false; | ||
|
|
||
| if let Some(pid) = state_lock.child.id() { | ||
| let pid = Pid::from_raw(pid as i32); | ||
|
|
||
| // Send SIGTERM signal to request graceful termination | ||
| match kill(pid, Signal::SIGTERM) { | ||
| Ok(_) => { | ||
| info!("Sent SIGTERM signal to falkor process with PID: {}", pid); | ||
|
|
||
| // Optionally wait for the process to exit | ||
| if let Err(e) = tokio::time::timeout( | ||
| std::time::Duration::from_secs(60), | ||
| state_lock.child.wait(), | ||
| ) | ||
| .await | ||
| { | ||
| error!( | ||
| "Timed out waiting for falkor process with PID: {} to exit: {:?}", | ||
| pid, e | ||
| ); | ||
| } else { | ||
| info!("Falkor process with PID: {} exited successfully", pid); | ||
| } | ||
| } | ||
| Err(e) => error!( | ||
| "Failed to send SIGTERM signal to falkor process: {:?}, with PID: {}", | ||
| e, pid | ||
| ), | ||
| } | ||
| } else { | ||
| error!("Failed to get PID of falkor process"); | ||
| } | ||
|
|
||
| // waiting for each handle in state_lock.handles | ||
| // for handle in state_lock.handles.drain(..) { | ||
| // if let Err(e) = handle.await { | ||
| // error!("Failed to wait for handle: {:?}", e); | ||
| // } | ||
| // } | ||
| Ok(()) | ||
| } |
There was a problem hiding this comment.
Implement graceful shutdown with proper cleanup
The termination process needs improvement in handling cleanup and shutdown.
- Wait for in-flight queries
- Implement proper timeout handling
- Clean up resources
- Handle monitoring task termination
pub async fn terminate(&mut self) -> BenchmarkResult<()> {
info!("Terminating FalkorProcess");
+
+ // Wait for in-flight queries to complete
+ self.wait_for_queries().await?;
+
let mut state_lock = self.state.lock().await;
state_lock.should_monitor = false;
+ // Clean up monitoring tasks
+ for handle in state_lock.handles.drain(..) {
+ if let Err(e) = handle.await {
+ error!("Failed to terminate monitoring task: {:?}", e);
+ }
+ }Committable suggestion skipped: line range outside the PR's diff.
src/falkor_process.rs
Outdated
| fn monitor_server(arc_state: Arc<Mutex<State>>) -> JoinHandle<()> { | ||
| tokio::spawn(async move { | ||
| loop { | ||
| let state = arc_state.lock().await; | ||
| if !state.should_monitor { | ||
| info!("Monitoring server stopped; exiting loop."); | ||
| break; | ||
| } | ||
| match Self::monitor_server_once().await { | ||
| Ok(_) => {} | ||
| Err(e) => { | ||
| error!("Failed to monitor server: {:?}", e); | ||
| // break; | ||
| } | ||
| } | ||
| tokio::time::sleep(tokio::time::Duration::from_secs(1)).await; | ||
| } | ||
| }) | ||
| } | ||
|
|
||
| async fn monitor_server_once() -> BenchmarkResult<()> { | ||
| let client = redis::Client::open("redis://127.0.0.1:6379/")?; | ||
| let mut con = client.get_multiplexed_async_connection().await?; | ||
| // let graph_info = redis::cmd("GRAPH.INFO").query_async(&mut con).await?; | ||
|
|
||
| let command = redis::cmd("GRAPH.INFO"); | ||
| let redis_value = con.send_packed_command(&command).await?; | ||
| let (running_queries, waiting_queries) = redis_to_query_info(redis_value)?; | ||
| trace!( | ||
| "Running Queries ({}): {:?}", | ||
| running_queries.len(), | ||
| running_queries | ||
| ); | ||
| trace!( | ||
| "Waiting Queries ({}): {:?}", | ||
| waiting_queries.len(), | ||
| waiting_queries | ||
| ); | ||
| if running_queries.len() > 3 { | ||
| error!("{} running queries found", running_queries.len()); | ||
| } | ||
| if !waiting_queries.is_empty() { | ||
| error!("Waiting queries found: {:?}", waiting_queries); | ||
| } | ||
| Ok(()) | ||
| } |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Enhance server monitoring capabilities
The server monitoring implementation could be improved with better metrics and health checks.
- Add health check metrics
- Implement proper error thresholds
- Add alerting capabilities
- Track query latencies
async fn monitor_server_once() -> BenchmarkResult<()> {
let client = redis::Client::open("redis://127.0.0.1:6379/")?;
let mut con = client.get_multiplexed_async_connection().await?;
- let command = redis::cmd("GRAPH.INFO");
+
+ // Track server health metrics
+ SERVER_HEALTH_GAUGE.set(1.0);
+
+ // Monitor query latencies
+ let start = std::time::Instant::now();
+ let command = redis::cmd("GRAPH.INFO");
let redis_value = con.send_packed_command(&command).await?;
+ QUERY_LATENCY_HISTOGRAM
+ .with_label_values(&["GRAPH.INFO"])
+ .observe(start.elapsed().as_secs_f64());Committable suggestion skipped: line range outside the PR's diff.
There was a problem hiding this comment.
Actionable comments posted: 4
🧹 Outside diff range and nitpick comments (14)
src/falkor_process.rs (3)
21-21: Consider using an absolute path or environment variable for REDIS_DATA_DIRUsing a relative path for data directory could cause issues if the process is started from different working directories.
Consider either:
- Using an environment variable with a default value
- Using an absolute path derived from the executable's location
-const REDIS_DATA_DIR: &str = "./redis-data"; +const REDIS_DATA_DIR: &str = env!("REDIS_DATA_DIR", "./redis-data");
75-78: Consider making Redis configuration values configurableThe cache size and max queued queries values are hardcoded, which reduces flexibility for different deployment scenarios.
Consider making these configurable through environment variables or a configuration file:
+const DEFAULT_CACHE_SIZE: &str = "40"; +const DEFAULT_MAX_QUEUED_QUERIES: &str = "100"; - "CACHE_SIZE", - "40", - "MAX_QUEUED_QUERIES", - "100", + "CACHE_SIZE", + &env::var("REDIS_CACHE_SIZE").unwrap_or_else(|_| DEFAULT_CACHE_SIZE.to_string()), + "MAX_QUEUED_QUERIES", + &env::var("REDIS_MAX_QUEUED_QUERIES").unwrap_or_else(|_| DEFAULT_MAX_QUEUED_QUERIES.to_string()),
226-226: Make query timeout configurableThe query timeout is hardcoded to 5000ms, which might not be suitable for all environments or query types.
Consider making it configurable:
+const DEFAULT_QUERY_TIMEOUT_MS: u64 = 5000; + - let mut values = graph.query(query).with_timeout(5000).execute().await?; + let timeout = env::var("QUERY_TIMEOUT_MS") + .ok() + .and_then(|v| v.parse().ok()) + .unwrap_or(DEFAULT_QUERY_TIMEOUT_MS); + let mut values = graph.query(query).with_timeout(timeout).execute().await?;src/bin/prepare_queries_main.rs (4)
24-24: Use structured logging instead ofprintln!Consider using the
info!macro from thetracingcrate instead ofprintln!for consistent logging throughout the application.Apply this diff to replace
println!withinfo!:- println!("read_queries took: {:?}", duration); + info!("read_queries took: {:?}", duration);Ensure you have
use tracing::info;at the top of your file if it's not already included.
33-37: Include error details when deserialization failsWhen deserialization fails, the specific error is not logged. Including the error details will aid in debugging.
Apply this diff to log the deserialization error:
- if let Ok(query) = serde_json::from_str::<PreparedQuery>(&line) { - trace!("Query: {:?}", query); - } else { - error!("Failed to deserialize query"); - } + match serde_json::from_str::<PreparedQuery>(&line) { + Ok(query) => trace!("Query: {:?}", query), + Err(e) => error!("Failed to deserialize query: {}", e), + }
65-74: Include error details when serialization failsCurrently, serialization errors are not detailed in the logs. Including the error information will help identify issues during serialization.
Apply this diff to log the serialization error:
- if let Ok(json) = serde_json::to_string(&item) { - // existing code - } else { - error!("Failed to serialize query"); - } + match serde_json::to_string(&item) { + Ok(json) => { + // existing code + }, + Err(e) => error!("Failed to serialize query: {}", e), + }
85-85: Parameterize the file name instead of hardcodingHardcoding the file name "output.txt" reduces flexibility. Consider passing the file name as a parameter to allow for different output destinations.
Apply this diff to parameterize the file name:
- write_iterator_to_file("output.txt", queries_iter).await?; + let file_name = "output.txt"; // Or obtain from function parameters or configuration + write_iterator_to_file(file_name, queries_iter).await?;Repeat the change where "output.txt" is used elsewhere to maintain consistency.
Cargo.toml (1)
31-31: Remove commented-out local path dependencyThe commented-out local path dependency for
falkordbcan be removed to clean up theCargo.tomlfile and avoid confusion.Apply this diff to remove the unused line:
-#falkordb = { path = "/Users/barak/dev/falkordb-rs", features = ["tokio", "tracing"] }src/bin/mpsc_main.rs (1)
53-69: Remove commented-out code to improve readabilityThe large block of commented-out code reduces code clarity. If this code is no longer needed, consider removing it.
Apply this diff to remove the commented-out code:
-// async fn distribute_messages<T, S>( -// mut stream: S, -// mut senders: Vec<mpsc::Sender<T>>, -// ) where -// T: Clone + Send + 'static, -// S: StreamExt<Item = T> + Unpin, -// { -// stream -// .for_each(|message| async { -// let send_futures = senders -// .iter_mut() -// .map(|sender| sender.send(message.clone())); -// let (_, index, _) = select_all(send_futures).await; -// senders.swap_remove(index); -// }) -// .await; -// }src/cli.rs (1)
9-9: Review the necessity of making internal structs publicChanging the visibility of
Cli,command, andExistingJsonFiletopubexposes them to other crates. Unless there is a need for external access, consider keeping them crate-private to encapsulate internal structures.Also applies to: 11-11, 15-15, 108-108
readme.md (1)
149-166: Improve organization of Prometheus queries documentation.The Prometheus queries section would benefit from better organization and documentation. Queries should be grouped by category with descriptions of their purpose.
Apply this diff to improve the documentation structure:
-sum by (vendor, spawn_id) (rate(operations_total{vendor="falkor"}[1m])) -redis -rate(redis_commands_processed_total{instance=~"redis-exporter:9121"}[1m]) -redis_connected_clients{instance=~"redis-exporter:9121"} -topk(5, irate(redis_commands_total{instance=~"redis-exporter:9121"} [1m])) -redis_blocked_clients -redis_commands_total -redis_commands_failed_calls_total -redis_commands_latencies_usec_count -redis_commands_rejected_calls_total -redis_io_threaded_reads_processed -redis_io_threaded_writes_processed -redis_io_threads_active -redis_memory_max_bytes -redis_memory_used_bytes -redis_memory_used_peak_bytes -redis_memory_used_vm_total -redis_process_id +### Performance Metrics + +#### Operations Rate +```promql +# Total operations per minute by vendor and spawn ID +sum by (vendor, spawn_id) (rate(operations_total{vendor="falkor"}[1m])) +``` + +#### Redis Server Metrics + +##### Command Processing +```promql +# Commands processed per minute +rate(redis_commands_processed_total{instance=~"redis-exporter:9121"}[1m]) + +# Top 5 most frequent commands +topk(5, irate(redis_commands_total{instance=~"redis-exporter:9121"} [1m])) +``` + +##### Client Connections +```promql +# Active client connections +redis_connected_clients{instance=~"redis-exporter:9121"} + +# Blocked clients +redis_blocked_clients +``` + +##### Command Statistics +```promql +# Total commands +redis_commands_total + +# Failed commands +redis_commands_failed_calls_total + +# Command latencies +redis_commands_latencies_usec_count + +# Rejected commands +redis_commands_rejected_calls_total +``` + +##### I/O Metrics +```promql +# Threaded I/O stats +redis_io_threaded_reads_processed +redis_io_threaded_writes_processed +redis_io_threads_active +``` + +##### Memory Usage +```promql +# Memory metrics +redis_memory_max_bytes +redis_memory_used_bytes +redis_memory_used_peak_bytes +redis_memory_used_vm_total +``` + +##### Process Information +```promql +# Redis process ID +redis_process_id +```src/main.rs (1)
38-38: Consider using a more robust cleanup approach for PrometheusEndpoint.The current approach of using
drop()is functional but could be enhanced with proper error handling for cleanup operations.Consider implementing a proper shutdown method for the PrometheusEndpoint that handles potential cleanup errors:
impl Drop for PrometheusEndpoint { fn drop(&mut self) { if let Err(e) = self.shutdown() { error!("Error shutting down Prometheus endpoint: {}", e); } } }Also applies to: 133-133
dashboards/falkor_dashboard.json (2)
476-478: Enhance latency metric calculation.The current latency calculation using a 1-minute rate might not provide the most accurate view of system performance.
Consider using histogram_quantile for better latency tracking:
- "expr": "rate(redis_commands_latencies_usec_count[1m])", - "legendFormat": "{{ cmd }}", + "expr": "histogram_quantile(0.95, sum(rate(redis_commands_duration_seconds_bucket[5m])) by (le, cmd))", + "legendFormat": "p95 {{ cmd }}",
93-93: Improve uptime metric calculation.The current uptime calculation using
max_over_timewith$__intervalmight miss data points.Consider using a more reliable approach:
- "expr": "max(max_over_time(redis_uptime_in_seconds{instance=~\"redis-exporter:9121\"}[$__interval]))", + "expr": "time() - process_start_time_seconds{instance=~\"redis-exporter:9121\"}",
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
⛔ Files ignored due to path filters (1)
Cargo.lockis excluded by!**/*.lock
📒 Files selected for processing (13)
Cargo.toml(1 hunks)dashboards/falkor_dashboard.json(1 hunks)readme.md(2 hunks)src/bin/mpsc_main.rs(1 hunks)src/bin/prepare_queries_main.rs(1 hunks)src/cli.rs(4 hunks)src/falkor.rs(4 hunks)src/falkor_process.rs(1 hunks)src/lib.rs(1 hunks)src/main.rs(8 hunks)src/neo4j_client.rs(4 hunks)src/queries_repository.rs(7 hunks)src/query.rs(3 hunks)
🚧 Files skipped from review as they are similar to previous changes (4)
- src/query.rs
- src/queries_repository.rs
- src/neo4j_client.rs
- src/falkor.rs
🧰 Additional context used
🪛 Markdownlint (0.35.0)
readme.md
147-147: null
Bare URL used
(MD034, no-bare-urls)
148-148: null
Bare URL used
(MD034, no-bare-urls)
🔇 Additional comments (10)
src/falkor_process.rs (5)
109-147: Minimize mutex lock scope in monitor_process
The mutex lock is held across await points, which could cause performance issues or deadlocks.
149-167: Minimize mutex lock scope in monitor_server
Similar to monitor_process, the mutex lock is held across await points.
291-304: Avoid creating a Tokio runtime in Drop implementation
Creating a new runtime in Drop can lead to panics during shutdown.
281-286: Wait for monitoring tasks to finish upon termination
The code to wait for monitoring tasks is commented out, which could lead to resource leaks.
306-391: LGTM! Well-structured helper functions
The helper functions and QueryInfo struct are well-documented and handle errors appropriately.
Cargo.toml (1)
43-43: Update hyper dependency to the latest stable version
The hyper crate is currently at version 0.14.31, but the latest stable version is 1.5.1. Updating to the latest version can bring performance improvements and new features.
src/lib.rs (2)
33-33: Replace .unwrap() with .expect() when registering metrics
Using .unwrap() can cause the program to panic without a clear message. Replace .unwrap() with .expect() and provide a helpful error message.
Apply this diff to improve error handling:
).unwrap();
+).expect("Failed to register OPERATION_COUNTER metric");Repeat this change for all instances where .unwrap() is used in metric registration.
Also applies to: 46-46, 51-51, 56-56, 61-61, 66-66, 71-71
47-51: Update metric name and improve error handling for FALKOR_RESTART_COUNTER
The metric name should be descriptive and follow naming conventions. Additionally, improve error handling by replacing .unwrap() with .expect().
Apply this diff:
pub static ref FALKOR_RESTART_COUNTER: Counter = register_counter!(
- "falkordb_restarts_total",
+ "falkordb_server_restarts_total",
"Total number of restarts for falkordb server",
)
-.unwrap();
+.expect("Failed to register falkordb_server_restarts_total counter");src/main.rs (2)
186-190: LGTM: Proper validation and error handling for parallel execution.
The implementation correctly validates the parallel parameter and properly spawns workers.
Also applies to: 213-214
237-258: LGTM: Well-structured worker implementation with proper instrumentation.
The worker implementation includes:
- Proper instrumentation with tracing
- Correct error handling
- Efficient query execution
| prometheus = { version = "0.13.4", features = ["gen"] } | ||
| lazy_static = "1.5" | ||
| hyper = { version = "0.14.31", features = ["server", "runtime", "http1", "tcp"] } | ||
| nonzero = "0.2.0" |
There was a problem hiding this comment.
💡 Codebase verification
Update hyper dependency to the latest version 1.5.1 for security and features
The dependency check reveals:
prometheus v0.13.4is at the latest versionlazy_static v1.5is at the latest version (1.5.0)hyper v0.14.31is outdated (latest: 1.5.1)nonzero v0.2.0is at the latest version
While the currently used version of hyper (0.14.31) is not affected by any known vulnerabilities, updating to the latest version (1.5.1) is recommended to benefit from the latest features and security improvements.
🔗 Analysis chain
Verify the new dependencies are up-to-date and free from vulnerabilities
Ensure that the added dependencies (prometheus, lazy_static, hyper, nonzero) are at their latest stable versions and have no known security vulnerabilities.
Run the following script to check for the latest versions and any security advisories:
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check latest versions and security advisories for new dependencies
# List of new dependencies
crates=("prometheus" "lazy_static" "hyper" "nonzero")
echo "Checking latest versions..."
for crate in "${crates[@]}"; do
echo -n "$crate: "
curl -s "https://crates.io/api/v1/crates/$crate" | jq -r '.crate.max_stable_version'
done
echo -e "\nChecking for security advisories..."
for crate in "${crates[@]}"; do
echo "=== $crate ==="
gh api graphql -f query='{
securityVulnerabilities(first: 5, ecosystem: RUST, package: "'$crate'") {
nodes {
advisory {
summary
severity
publishedAt
}
vulnerableVersionRange
firstPatchedVersion {
identifier
}
}
}
}'
done
Length of output: 3727
src/bin/mpsc_main.rs
Outdated
| tokio::spawn(async move {}); | ||
| for i in 0..2 { | ||
| let tx1 = tx1.clone(); | ||
| let r = r.clone(); | ||
| tokio::spawn(async move { | ||
| info!("Receiver 1 starting"); | ||
| let mut rx = r.lock().await; | ||
| info!("Receiver 1 have mutex"); | ||
| if let Some(rx1) = rx.recv().await { | ||
| info!("Receiver 1: {}", rx1); | ||
| drop(rx); | ||
| // sleep for 1 second | ||
| tokio::time::sleep(tokio::time::Duration::from_secs(1)).await; | ||
| } | ||
| info!("Receiver 1 done"); | ||
| }); | ||
| } |
There was a problem hiding this comment.
Avoid holding a mutex lock across .await points
Holding a mutex lock while awaiting can lead to deadlocks or prevent other async tasks from making progress.
Consider restructuring the receiver logic to avoid locking across .await boundaries. Here's a refactored version:
for i in 0..2 {
let r = r.clone();
tokio::spawn(async move {
info!("Receiver {} starting", i);
- let mut rx = r.lock().await;
- info!("Receiver {} has mutex", i);
- if let Some(rx1) = rx.recv().await {
- info!("Receiver {}: {}", i, rx1);
- drop(rx);
- // sleep for 1 second
- tokio::time::sleep(tokio::time::Duration::from_secs(1)).await;
- }
+ loop {
+ let rx1 = {
+ let mut rx = r.lock().await;
+ rx.recv().await
+ };
+ match rx1 {
+ Some(value) => {
+ info!("Receiver {}: {}", i, value);
+ // Process the value
+ },
+ None => {
+ // Channel closed
+ break;
+ },
+ }
+ // Sleep for 1 second
+ tokio::time::sleep(tokio::time::Duration::from_secs(1)).await;
+ }
info!("Receiver {} done", i);
});
}📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| tokio::spawn(async move {}); | |
| for i in 0..2 { | |
| let tx1 = tx1.clone(); | |
| let r = r.clone(); | |
| tokio::spawn(async move { | |
| info!("Receiver 1 starting"); | |
| let mut rx = r.lock().await; | |
| info!("Receiver 1 have mutex"); | |
| if let Some(rx1) = rx.recv().await { | |
| info!("Receiver 1: {}", rx1); | |
| drop(rx); | |
| // sleep for 1 second | |
| tokio::time::sleep(tokio::time::Duration::from_secs(1)).await; | |
| } | |
| info!("Receiver 1 done"); | |
| }); | |
| } | |
| tokio::spawn(async move {}); | |
| for i in 0..2 { | |
| let tx1 = tx1.clone(); | |
| let r = r.clone(); | |
| tokio::spawn(async move { | |
| info!("Receiver {} starting", i); | |
| loop { | |
| let rx1 = { | |
| let mut rx = r.lock().await; | |
| rx.recv().await | |
| }; | |
| match rx1 { | |
| Some(value) => { | |
| info!("Receiver {}: {}", i, value); | |
| // Process the value | |
| }, | |
| None => { | |
| // Channel closed | |
| break; | |
| }, | |
| } | |
| // Sleep for 1 second | |
| tokio::time::sleep(tokio::time::Duration::from_secs(1)).await; | |
| } | |
| info!("Receiver {} done", i); | |
| }); | |
| } |
| - Accessing grafana http://localhost:3000 | ||
| - Accessing prometheus http://localhost:9090 |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Format URLs as proper markdown links.
The bare URLs should be formatted as proper markdown links for better readability and to follow markdown best practices.
Apply this diff:
-Accessing grafana http://localhost:3000
-Accessing prometheus http://localhost:9090
+- Accessing Grafana: [http://localhost:3000](http://localhost:3000)
+- Accessing Prometheus: [http://localhost:9090](http://localhost:9090)📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| - Accessing grafana http://localhost:3000 | |
| - Accessing prometheus http://localhost:9090 | |
| - Accessing Grafana: [http://localhost:3000](http://localhost:3000) | |
| - Accessing Prometheus: [http://localhost:9090](http://localhost:9090) |
🧰 Tools
🪛 Markdownlint (0.35.0)
147-147: null
Bare URL used
(MD034, no-bare-urls)
148-148: null
Bare URL used
(MD034, no-bare-urls)
dashboards/falkor_dashboard.json
Outdated
| "gridPos": { | ||
| "h": 8, | ||
| "w": 12, | ||
| "x": 0, | ||
| "y": 21 | ||
| }, | ||
| "id": 4, | ||
| "options": { | ||
| "legend": { | ||
| "calcs": [], | ||
| "displayMode": "list", | ||
| "placement": "bottom", | ||
| "showLegend": true | ||
| }, | ||
| "tooltip": { | ||
| "mode": "single", | ||
| "sort": "none" | ||
| } | ||
| }, | ||
| "pluginVersion": "11.3.1", | ||
| "targets": [ | ||
| { | ||
| "editorMode": "code", | ||
| "expr": "sum by (vendor) (rate(operations_total{vendor=\"falkor\"}[5m]))", | ||
| "legendFormat": "executor {{spawn_id}}", | ||
| "range": true, | ||
| "refId": "A" | ||
| } | ||
| ], | ||
| "title": "queries/sec (client)", | ||
| "type": "timeseries" | ||
| }, |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Remove duplicate queries/sec panel.
There are two identical panels showing queries/sec metrics (IDs 4 and 5). This creates unnecessary redundancy in the dashboard.
Keep the panel at lines 781-812 and remove the duplicate panel at lines 874-905, as they show the same information.
Also applies to: 874-905
* mpsc implementation -- seems that it is slower * Fix the slowness with the mpsc * protected-mode no * replace falkor_process.rs with more resilient implementation, add more panels to dashboard * clippy * remove dead code, change project layout, fix waiting request metric * stop redis before copy the dump file display progress for every 10 messages instead of 1000 * Add parking lot deadlock detection * Add send trace to tokio console * Give names to tokio spawns * Display message every 1000 queries * Add message when the consumer of the messages get None * add race when sending data to server * Update docker compose to work on linux * remove san from cli, add histogram and dashboards, remove timeout from calls to falkor client
There was a problem hiding this comment.
Actionable comments posted: 14
🧹 Outside diff range and nitpick comments (17)
docker-compose.yml (2)
13-21: Enhance Redis Exporter configurationThe current configuration could be more robust:
- Pin the Redis Exporter version
- Make Redis address configurable via environment variables
- Add health check for better orchestration
Consider this improved configuration:
redis-exporter: - image: oliver006/redis_exporter:latest + image: oliver006/redis_exporter:v1.55.0 + environment: + - REDIS_ADDR=host.docker.internal:6379 command: - - '--redis.addr=host.docker.internal:6379' + - '--redis.addr=${REDIS_ADDR}' ports: - 9121:9121 + healthcheck: + test: ["CMD", "wget", "--spider", "http://localhost:9121/metrics"] + interval: 30s + timeout: 5s + retries: 3 extra_hosts: - "host.docker.internal:host-gateway"
1-38: Consider these architectural recommendationsWhile the monitoring stack setup is good, consider these enhancements:
- Add Alertmanager service for alert management
- Consider using service discovery instead of static configurations
- Add a reverse proxy (like Traefik) to handle external access securely
- Consider using Docker Swarm secrets or Kubernetes secrets for sensitive configurations
Example Alertmanager service configuration:
alertmanager: image: prom/alertmanager:v0.26.0 ports: - 9093:9093 volumes: - alertmanager_config:/etc/alertmanager command: - '--config.file=/etc/alertmanager/alertmanager.yml'🧰 Tools
🪛 yamllint (1.35.1)
[error] 38-38: no new line character at the end of file
(new-line-at-end-of-file)
src/queries_repository.rs (4)
152-162: Remove commented-out code to improve code cleanlinessLines 152-162 contain a commented-out implementation of the
Queriestrait. If this code is no longer needed, consider removing it to keep the codebase clean and maintainable.
142-145: Unnecessary sorting of keys before random selectionIn
random_query(), the keys are sorted before randomly selecting one. Since the selection is random, sorting the keys is unnecessary and can be omitted to improve performance.Apply this diff to remove the sorting:
pub fn random_query(&self) -> Option<PreparedQuery> { let mut keys: Vec<&String> = self.queries.keys().collect(); - keys.sort(); let mut rng = rand::thread_rng(); keys.choose(&mut rng).map(|&key| { let generator = self.queries.get(key).unwrap(); PreparedQuery::new(key.clone(), generator.query_type, generator.generate()) }) }
303-310: Add documentation comments forPreparedQuerystructThe
PreparedQuerystruct is a public structure that encapsulates query details. Adding Rust documentation comments (///) for the struct and its fields would improve code readability and maintainability.
165-167: Remove unused field_edgesinRandomUtilThe
_edgesfield inRandomUtilis prefixed with an underscore, indicating it's unused. If this field is not necessary for future use, consider removing it to simplify the struct.src/process_monitor.rs (1)
46-46: Remove commented-out code for clarityConsider removing the commented-out
sleepstatement if it's no longer needed, to keep the code clean and maintain readability.todo.md (1)
4-5: Fix indentation and grammar in todo itemsThe sub-tasks should be properly indented and the grammar needs correction:
- [] read/write without increase the graph size - [] set read/write cli + - [] read/write without increasing the graph size + - [] set read/write cli🧰 Tools
🪛 LanguageTool
[uncategorized] ~4-~4: This verb may not be in the correct form. Consider using a different form for this context.
Context: ...ite vs read - [] read/write without increase the graph size - [] set read/write ...(AI_EN_LECTOR_REPLACEMENT_VERB_FORM)
🪛 Markdownlint (0.35.0)
4-4: Expected: 2; Actual: 4
Unordered list indentation(MD007, ul-indent)
5-5: Expected: 2; Actual: 4
Unordered list indentation(MD007, ul-indent)
src/bin/mpsc_main.rs (1)
8-12: Consider adding structured logging fieldsWhile the current logging setup is good, consider adding structured fields for better observability:
tracing_subscriber::fmt() .pretty() .with_file(true) .with_line_number(true) + .with_thread_ids(true) + .with_thread_names(true) + .with_target(false) .init();Cargo.toml (2)
33-34: Remove commented-out local path dependencyThe commented-out local path dependency should be removed as it's not suitable for production and could cause confusion.
-#falkordb = { path = "/Users/barak/dev/falkordb-rs", features = ["tokio", "tracing"] }
42-46: Update hyper dependency to the latest versionThe hyper dependency (0.14.31) has a newer version (1.5.1) available. While the current version is secure, updating would provide performance improvements and bug fixes.
-hyper = { version = "0.14.31", features = ["server", "runtime", "http1", "tcp"] } +hyper = { version = "1.5.1", features = ["server", "runtime", "http1", "tcp"] }src/utils.rs (3)
43-53: Consider adding error context to file operations.The file operations functions could benefit from more descriptive error messages that include the file path in the error context.
Apply this diff to improve error handling:
pub async fn delete_file(file_path: &str) -> BenchmarkResult<()> { if file_exists(file_path).await { info!("Deleting file: {}", file_path); - fs::remove_file(file_path).await?; + fs::remove_file(file_path) + .await + .map_err(|e| OtherError(format!("Failed to delete file {}: {}", file_path, e)))?; } Ok(()) }
202-224: Extract Redis timeout durations to constants.The timeout durations are hardcoded magic numbers. Consider extracting them to named constants for better maintainability.
Add these constants at the top of the file:
+const REDIS_PING_TIMEOUT_SECS: u64 = 10; +const REDIS_SAVE_TIMEOUT_SECS: u64 = 30; +const REDIS_SHUTDOWN_TIMEOUT_SECS: u64 = 20; - let timeout_duration = Duration::from_secs(10); + let timeout_duration = Duration::from_secs(REDIS_PING_TIMEOUT_SECS);
Line range hint
158-201: Enhance process state detection in get_command_pid.The current implementation has a basic check for zombie processes using
stat.starts_with("Z"). Consider using a more comprehensive approach to detect various process states.Apply this diff to improve process state detection:
+#[derive(Debug)] +enum ProcessState { + Running, + Sleeping, + Zombie, + Stopped, + Unknown(String), +} + +impl ProcessState { + fn from_stat(stat: &str) -> Self { + match stat.chars().next() { + Some('R') => Self::Running, + Some('S') => Self::Sleeping, + Some('Z') => Self::Zombie, + Some('T') => Self::Stopped, + _ => Self::Unknown(stat.to_string()), + } + } + + fn is_valid(&self) -> bool { + matches!(self, Self::Running | Self::Sleeping) + } +} pub async fn get_command_pid(cmd: impl AsRef<str>) -> BenchmarkResult<u32> { let cmd = cmd.as_ref(); let output = Command::new("ps") .args(["-eo", "pid,command,stat"]) .output() .await .map_err(BenchmarkError::IoError)?; if output.status.success() { let stdout = str::from_utf8(&output.stdout) .map_err(|e| OtherError(format!("UTF-8 conversion error: {}", e)))?; for (index, line) in stdout.lines().enumerate() { if index == 0 || line.contains("grep") { continue; } if line.contains(cmd) { if let [pid, command, stat, ..] = line.split_whitespace().collect::<Vec<_>>().as_slice() { if command.contains(cmd) { - if stat.starts_with("Z") || stat.contains("<defunct>") { + let state = ProcessState::from_stat(stat); + if !state.is_valid() { + info!("Skipping process with state {:?}", state); continue; } return pid .parse::<u32>() .map_err(|e| OtherError(format!("Failed to parse PID: {}", e))); } } } } Err(ProcessNofFoundError(cmd.to_string())) } else { error!( "ps command failed with exit code: {:?}", output.status.code() ); Err(OtherError(format!( "ps command failed with exit code: {:?}", output.status.code() ))) } }src/main.rs (1)
268-325: Enhance worker implementation with backpressure and metrics.The worker implementation could benefit from backpressure handling and better metrics integration.
Apply this diff to improve the worker:
async fn spawn_worker( falkor: &Falkor<Started>, worker_id: usize, receiver: &Arc<Mutex<Receiver<PreparedQuery>>>, + stats: WorkerStats, ) -> BenchmarkResult<JoinHandle<()>> { info!("spawning worker"); let mut client = falkor.client().await?; let receiver = Arc::clone(receiver); + let worker_queue_size = Arc::new(AtomicU64::new(0)); + let worker_queue_size_clone = Arc::clone(&worker_queue_size); + + // Register worker queue size metric + gauge!("worker_queue_size", worker_queue_size_clone, "worker_id" => worker_id.to_string()); let handle = task::Builder::new() .name(format!("graph_client_sender_{}", worker_id).as_str()) .spawn({ async move { let worker_id = worker_id.to_string(); let worker_id_str = worker_id.as_str(); let mut counter = 0u32; + let mut consecutive_errors = 0u32; + const MAX_CONSECUTIVE_ERRORS: u32 = 5; loop { + if consecutive_errors >= MAX_CONSECUTIVE_ERRORS { + error!("Worker {} stopping due to too many consecutive errors", worker_id); + break; + } + // get next value and release the mutex let received = receiver.lock().await.recv().await; + worker_queue_size.fetch_sub(1, Ordering::Relaxed); match received { Some(prepared_query) => { let start_time = Instant::now(); + worker_queue_size.fetch_add(1, Ordering::Relaxed); let r = client .execute_prepared_query(worker_id_str, &prepared_query) .await; let duration = start_time.elapsed(); match r { Ok(_) => { FALKOR_SUCCESS_REQUESTS_DURATION_HISTOGRAM.observe(duration.as_secs_f64()); counter += 1; + consecutive_errors = 0; + stats.processed.fetch_add(1, Ordering::Relaxed); if counter % 1000 == 0 { info!("worker {} processed {} queries", worker_id, counter); } } Err(e) => { FALKOR_ERROR_REQUESTS_DURATION_HISTOGRAM.observe(duration.as_secs_f64()); + consecutive_errors += 1; + stats.errors.fetch_add(1, Ordering::Relaxed); error!( "worker {} failed to process query: {:?}", worker_id, e ); } } } None => { info!("worker {} received None, exiting", worker_id); break; } } } info!("worker {} finished", worker_id); } })?; Ok(handle) }dashboards/falkor_dashboard.json (2)
93-93: Improve uptime metric calculation.The current uptime calculation using
max_over_timewith$__intervalmight miss data points.Use process start time for more reliable uptime tracking:
- "expr": "max(max_over_time(redis_uptime_in_seconds{instance=~\"redis-exporter:9121\"}[$__interval]))", + "expr": "time() - process_start_time_seconds{instance=~\"redis-exporter:9121\"}",
1599-1600: Adjust default time range for better visibility.The current 5-minute default time range might be too short for observing trends.
Consider extending the default time range:
"time": { - "from": "now-5m", + "from": "now-30m", "to": "now" },
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
⛔ Files ignored due to path filters (1)
Cargo.lockis excluded by!**/*.lock
📒 Files selected for processing (26)
.cargo/config.toml(1 hunks)Cargo.toml(1 hunks)askama.toml(0 hunks)dashboards/falkor_dashboard.json(1 hunks)docker-compose.yml(1 hunks)prometheus.yml(1 hunks)src/bin/falkor_process_main.rs(1 hunks)src/bin/mpsc_main.rs(1 hunks)src/cli.rs(4 hunks)src/compare_template.rs(0 hunks)src/error.rs(2 hunks)src/falkor.rs(1 hunks)src/falkor/falkor_driver.rs(1 hunks)src/falkor/falkor_process.rs(1 hunks)src/lib.rs(1 hunks)src/main.rs(7 hunks)src/metrics_collector.rs(0 hunks)src/neo4j.rs(5 hunks)src/neo4j_client.rs(4 hunks)src/process_monitor.rs(1 hunks)src/prometheus_endpoint.rs(1 hunks)src/queries_repository.rs(7 hunks)src/query.rs(2 hunks)src/utils.rs(9 hunks)templates/compare.html(0 hunks)todo.md(1 hunks)
💤 Files with no reviewable changes (4)
- askama.toml
- src/compare_template.rs
- templates/compare.html
- src/metrics_collector.rs
✅ Files skipped from review due to trivial changes (1)
- .cargo/config.toml
🚧 Files skipped from review as they are similar to previous changes (6)
- src/bin/falkor_process_main.rs
- src/query.rs
- prometheus.yml
- src/cli.rs
- src/neo4j_client.rs
- src/neo4j.rs
🧰 Additional context used
🪛 LanguageTool
todo.md
[uncategorized] ~4-~4: This verb may not be in the correct form. Consider using a different form for this context.
Context: ...ite vs read - [] read/write without increase the graph size - [] set read/write ...
(AI_EN_LECTOR_REPLACEMENT_VERB_FORM)
🪛 Markdownlint (0.35.0)
todo.md
4-4: Expected: 2; Actual: 4
Unordered list indentation
(MD007, ul-indent)
5-5: Expected: 2; Actual: 4
Unordered list indentation
(MD007, ul-indent)
🪛 yamllint (1.35.1)
docker-compose.yml
[error] 38-38: no new line character at the end of file
(new-line-at-end-of-file)
🔇 Additional comments (13)
src/queries_repository.rs (2)
13-15: Verify the necessity of changing Flavour enum visibility to pub
The Flavour enum's visibility has been changed from pub(crate) to pub, making it accessible outside the crate. Ensure that exposing Flavour as a public enum is intentional and does not expose internal implementation details that should remain encapsulated.
69-72: Confirm the need for making flavour method public
The flavour method in QueriesRepositoryBuilder has its visibility changed from pub(crate) to pub. Please verify if this method needs to be publicly accessible or if it should remain restricted within the crate.
src/falkor.rs (1)
1-5: Modularization enhances code organization
The restructuring of the falkor module into falkor_driver and falkor_process improves code organization and maintainability. Re-exporting with pub use falkor_driver::*; effectively exposes necessary components.
src/error.rs (1)
29-32: LGTM! Well-structured error handling for async operations
The new error variants properly handle Tokio's send errors and elapsed timeouts, with clear error messages and appropriate error type derivation.
src/bin/mpsc_main.rs (1)
47-56:
Avoid holding mutex lock across .await points
The current implementation holds the mutex lock while awaiting message reception, which could block other workers.
- let mut receiver = rx_worker.lock().await;
- match receiver.recv().await {
+ let message = {
+ let mut receiver = rx_worker.lock().await;
+ receiver.recv().await
+ };
+ match message {Cargo.toml (2)
15-16: LGTM!
The Clippy lint configuration is appropriate for a benchmark tool.
49-63: LGTM!
The binary targets are well-organized and follow good practices.
src/prometheus_endpoint.rs (3)
25-26: 🛠️ Refactor suggestion
Make server address configurable
The hardcoded address 127.0.0.1:8080 should be configurable through environment variables or constructor parameters to support different deployment scenarios.
- let addr = SocketAddr::from(([127, 0, 0, 1], 8080));
+ let host = std::env::var("PROMETHEUS_HOST").unwrap_or_else(|_| "127.0.0.1".to_string());
+ let port = std::env::var("PROMETHEUS_PORT")
+ .ok()
+ .and_then(|p| p.parse().ok())
+ .unwrap_or(8080);
+ let addr: SocketAddr = format!("{}:{}", host, port).parse().expect("Invalid address");Likely invalid or redundant comment.
62-72:
Improve error handling in metrics_handler
The function uses unwrap() which could cause panics in production. Implement proper error handling.
async fn metrics_handler(_req: Request<Body>) -> Result<Response<Body>, hyper::Error> {
let encoder = TextEncoder::new();
let metric_families = prometheus::gather();
let mut buffer = Vec::new();
- encoder.encode(&metric_families, &mut buffer).unwrap();
+ if let Err(e) = encoder.encode(&metric_families, &mut buffer) {
+ error!("Failed to encode metrics: {}", e);
+ return Ok(Response::builder()
+ .status(hyper::StatusCode::INTERNAL_SERVER_ERROR)
+ .body(Body::from("Failed to encode metrics"))
+ .unwrap_or_else(|_| {
+ Response::new(Body::from("Internal Server Error"))
+ }));
+ }
trace!("Metrics request received");
- Ok(Response::builder()
- .header(hyper::header::CONTENT_TYPE, encoder.format_type())
- .body(Body::from(buffer))
- .unwrap())
+ Response::builder()
+ .header(hyper::header::CONTENT_TYPE, encoder.format_type())
+ .body(Body::from(buffer))
+ .map_err(|e| {
+ error!("Failed to build response: {}", e);
+ hyper::Error::from(std::io::Error::new(
+ std::io::ErrorKind::Other,
+ "Failed to build response"
+ ))
+ })Likely invalid or redundant comment.
50-59:
Implement proper shutdown handling
The current Drop implementation may not ensure proper server shutdown. Since Drop cannot be async, consider adding an explicit shutdown method.
+ pub async fn shutdown(&mut self) {
+ if let Some(tx) = self.shutdown_tx.take() {
+ let _ = tx.send(());
+ info!("Prometheus endpoint shutdown signal sent");
+ }
+ if let Some(thread) = self.server_thread.take() {
+ if let Err(e) = thread.await {
+ error!("Server task error: {}", e);
+ }
+ }
+ }
impl Drop for PrometheusEndpoint {
fn drop(&mut self) {
if let Some(tx) = self.shutdown_tx.take() {
let _ = tx.send(());
info!("Prometheus endpoint shutdown");
}
- if let Some(thread) = self.server_thread.take() {
- drop(thread);
- }
}
}Likely invalid or redundant comment.
src/lib.rs (2)
25-89: LGTM for metric definitions
The metric definitions follow Prometheus naming conventions and have appropriate labels and descriptions. The histogram buckets are well-chosen for response time measurements.
77-82: 🛠️ Refactor suggestion
Improve error handling in metric registration
Using unwrap() for metric registration could cause panics at startup. Use expect() with descriptive messages.
- .unwrap();
+ .expect("Failed to register falkordb_response_time_success_histogram");Likely invalid or redundant comment.
dashboards/falkor_dashboard.json (1)
477-478: 🛠️ Refactor suggestion
Improve latency metric calculation.
The current latency calculation using rate might not provide accurate percentiles.
Use histogram_quantile for better latency tracking:
- "expr": "rate(redis_commands_latencies_usec_count[1m])",
- "legendFormat": "{{ cmd }}",
+ "expr": "histogram_quantile(0.95, sum(rate(redis_commands_duration_seconds_bucket[5m])) by (le, cmd))",
+ "legendFormat": "p95 {{ cmd }}",Likely invalid or redundant comment.
docker-compose.yml
Outdated
| volumes: | ||
| prometheus_data: |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Complete the volumes configuration
The volumes section needs to be expanded to include all required named volumes for data persistence.
Apply this diff to complete the volumes configuration:
volumes:
prometheus_data:
+ prometheus_config:
+ grafana_config:
+ grafana_data:
+This also fixes the missing newline at the end of file.
📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| volumes: | |
| prometheus_data: | |
| volumes: | |
| prometheus_data: | |
| prometheus_config: | |
| grafana_config: | |
| grafana_data: | |
🧰 Tools
🪛 yamllint (1.35.1)
[error] 38-38: no new line character at the end of file
(new-line-at-end-of-file)
docker-compose.yml
Outdated
| prometheus: | ||
| image: prom/prometheus:latest | ||
| extra_hosts: | ||
| - "host.docker.internal:host-gateway" | ||
| ports: | ||
| - 9090:9090 | ||
| volumes: | ||
| - ./prometheus.yml:/etc/prometheus/prometheus.yml | ||
| command: | ||
| - '--config.file=/etc/prometheus/prometheus.yml' | ||
|
|
There was a problem hiding this comment.
🛠️ Refactor suggestion
Consider production-ready adjustments for Prometheus service
A few suggestions to make the configuration more robust:
- Pin the Prometheus version instead of using
latesttag - Consider using named volume for prometheus.yml instead of bind mount
- The
host.docker.internalmight not work on all platforms (Linux requires special handling)
Apply this diff for a more production-ready setup:
prometheus:
- image: prom/prometheus:latest
+ image: prom/prometheus:v2.48.1 # Pin to specific version
extra_hosts:
- "host.docker.internal:host-gateway"
ports:
- 9090:9090
volumes:
- - ./prometheus.yml:/etc/prometheus/prometheus.yml
+ - prometheus_config:/etc/prometheus/
+ - prometheus_data:/prometheus
command:
- '--config.file=/etc/prometheus/prometheus.yml'Committable suggestion skipped: line range outside the PR's diff.
docker-compose.yml
Outdated
| grafana: | ||
| image: grafana/grafana:latest | ||
| ports: | ||
| - 3000:3000 | ||
| environment: | ||
| - GF_AUTH_DISABLE_LOGIN_FORM=true | ||
| - GF_AUTH_ANONYMOUS_ENABLED=true | ||
| - GF_AUTH_ANONYMOUS_ORG_ROLE=Admin | ||
| - GF_DASHBOARDS_JSON_ENABLED=true | ||
| volumes: | ||
| - ./grafana-datasources.yml:/etc/grafana/provisioning/datasources/datasources.yml | ||
| - ./dashboards:/var/lib/grafana/dashboards | ||
| - ./provisioning:/etc/grafana/provisioning |
There was a problem hiding this comment.
💡 Codebase verification
Security concerns in Grafana setup need attention, but configuration files are properly structured
The configuration files exist and are properly structured:
grafana-datasources.ymlcontains valid Prometheus datasource configurationdashboards/contains two JSON dashboard filesprovisioning/has the expecteddashboardsanddatasourcessubdirectories
However, the security concerns remain valid:
- Anonymous admin access is a significant security risk
- Using
latesttag could lead to unexpected updates - While bind mounts have proper files, using named volumes would be more maintainable
Please implement the suggested security improvements from the original review:
- Use a specific Grafana version instead of
latest - Replace anonymous access with proper authentication
- Consider using named volumes instead of bind mounts
🔗 Analysis chain
Security and configuration concerns in Grafana setup
Critical security and configuration issues to address:
- Anonymous admin access is a security risk in production
- Using latest tag could lead to unexpected updates
- Multiple bind mounts assume configuration files exist
Let's verify if the required configuration files exist:
Consider applying these security improvements:
grafana:
- image: grafana/grafana:latest
+ image: grafana/grafana:10.2.3
ports:
- 3000:3000
environment:
- - GF_AUTH_DISABLE_LOGIN_FORM=true
- - GF_AUTH_ANONYMOUS_ENABLED=true
- - GF_AUTH_ANONYMOUS_ORG_ROLE=Admin
+ - GF_SECURITY_ADMIN_PASSWORD=${GRAFANA_ADMIN_PASSWORD}
+ - GF_SECURITY_ADMIN_USER=${GRAFANA_ADMIN_USER}
- GF_DASHBOARDS_JSON_ENABLED=true
volumes:
- - ./grafana-datasources.yml:/etc/grafana/provisioning/datasources/datasources.yml
- - ./dashboards:/var/lib/grafana/dashboards
- - ./provisioning:/etc/grafana/provisioning
+ - grafana_config:/etc/grafana
+ - grafana_data:/var/lib/grafanaLet me verify the contents of these directories to ensure they contain valid configuration files and not just empty directories.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Check if required Grafana configuration files exist
echo "Checking for required Grafana configuration files..."
for file in grafana-datasources.yml dashboards/ provisioning/; do
if [ -e "$file" ]; then
echo "✓ Found: $file"
else
echo "✗ Missing: $file"
fi
done
Length of output: 576
Script:
#!/bin/bash
# Check contents of Grafana configuration files and directories
echo "=== grafana-datasources.yml content ==="
cat grafana-datasources.yml
echo -e "\n=== Dashboards directory content ==="
ls -la dashboards/
echo -e "\n=== Provisioning directory content ==="
ls -la provisioning/
echo -e "\n=== Checking if datasources.yml contains valid YAML ==="
if command -v yamllint >/dev/null 2>&1; then
yamllint grafana-datasources.yml
else
echo "yamllint not available"
fi
Length of output: 1180
src/queries_repository.rs
Outdated
| fn random_vertex(&self) -> i32 { | ||
| let mut rng = rand::thread_rng(); | ||
| rng.gen_range(1..=self.vertices) | ||
| } | ||
| fn random_path( | ||
| &self, | ||
| rng: &mut dyn RngCore, | ||
| ) -> (i32, i32) { | ||
| let start = self.random_vertex(rng); | ||
| let mut end = self.random_vertex(rng); | ||
| fn random_path(&self) -> (i32, i32) { | ||
| let start = self.random_vertex(); | ||
| let mut end = self.random_vertex(); | ||
|
|
||
| // Ensure start and end are different | ||
| while end == start { | ||
| end = self.random_vertex(rng); | ||
| end = self.random_vertex(); | ||
| } | ||
| (start, end) | ||
| } |
There was a problem hiding this comment.
Potential infinite loop in random_path when vertices ≤ 1
If self.vertices is less than or equal to 1, random_vertex() will always return the same value. Consequently, the while end == start loop in random_path may become infinite because start and end will always be equal.
Consider adding a check to handle cases where self.vertices ≤ 1.
Apply this diff to fix the issue:
impl RandomUtil {
fn random_vertex(&self) -> i32 {
let mut rng = rand::thread_rng();
rng.gen_range(1..=self.vertices)
}
fn random_path(&self) -> (i32, i32) {
+ if self.vertices <= 1 {
+ panic!("Not enough vertices to generate a path");
+ }
let start = self.random_vertex();
let mut end = self.random_vertex();
// Ensure start and end are different
while end == start {
end = self.random_vertex();
}
(start, end)
}
}📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| fn random_vertex(&self) -> i32 { | |
| let mut rng = rand::thread_rng(); | |
| rng.gen_range(1..=self.vertices) | |
| } | |
| fn random_path( | |
| &self, | |
| rng: &mut dyn RngCore, | |
| ) -> (i32, i32) { | |
| let start = self.random_vertex(rng); | |
| let mut end = self.random_vertex(rng); | |
| fn random_path(&self) -> (i32, i32) { | |
| let start = self.random_vertex(); | |
| let mut end = self.random_vertex(); | |
| // Ensure start and end are different | |
| while end == start { | |
| end = self.random_vertex(rng); | |
| end = self.random_vertex(); | |
| } | |
| (start, end) | |
| } | |
| fn random_vertex(&self) -> i32 { | |
| let mut rng = rand::thread_rng(); | |
| rng.gen_range(1..=self.vertices) | |
| } | |
| fn random_path(&self) -> (i32, i32) { | |
| if self.vertices <= 1 { | |
| panic!("Not enough vertices to generate a path"); | |
| } | |
| let start = self.random_vertex(); | |
| let mut end = self.random_vertex(); | |
| // Ensure start and end are different | |
| while end == start { | |
| end = self.random_vertex(); | |
| } | |
| (start, end) | |
| } |
src/falkor/falkor_driver.rs
Outdated
| match Arc::try_unwrap(queries) { | ||
| Ok(queries) => { | ||
| for PreparedQuery { q_name, cypher, .. } in queries { | ||
| let res = self | ||
| ._execute_query(spawn_id.as_str(), q_name.as_str(), cypher.as_str()) | ||
| .await; | ||
| // info!( | ||
| // "executed: query_name={}, query:{}, res {:?}", | ||
| // query_name, query, _res | ||
| // ); | ||
| if let Err(e) = res { | ||
| error!("Error executing query: {}, the error is: {:?}", cypher, e); | ||
| } | ||
| } | ||
| } | ||
| Err(arc) => { | ||
| error!( | ||
| "Failed to unwrap queries iterator, Remaining references count: {}", | ||
| Arc::strong_count(&arc) | ||
| ); | ||
| } | ||
| } |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Avoid using Arc::try_unwrap to prevent runtime errors
Using Arc::try_unwrap(queries) will only succeed if there are no other strong references to the Arc. If there are other references, this will fail, and the error handling only logs the issue without processing the queries. This could lead to unexpected behavior or missed query executions.
Consider iterating over the queries without unwrapping the Arc. You can clone the Arc or restructure the code to avoid needing to unwrap it.
Apply this diff to iterate over the queries safely:
- match Arc::try_unwrap(queries) {
- Ok(queries) => {
- for PreparedQuery { q_name, cypher, .. } in queries {
- let res = self
- ._execute_query(spawn_id.as_str(), q_name.as_str(), cypher.as_str())
- .await;
- if let Err(e) = res {
- error!("Error executing query: {}, the error is: {:?}", cypher, e);
- }
- }
- }
- Err(arc) => {
- error!(
- "Failed to unwrap queries iterator, Remaining references count: {}",
- Arc::strong_count(&arc)
- );
- }
- }
+ for PreparedQuery { q_name, cypher, .. } in queries.iter() {
+ let res = self
+ ._execute_query(spawn_id.as_str(), q_name.as_str(), cypher.as_str())
+ .await;
+ if let Err(e) = res {
+ error!("Error executing query: {}, the error is: {:?}", cypher, e);
+ }
+ }📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| match Arc::try_unwrap(queries) { | |
| Ok(queries) => { | |
| for PreparedQuery { q_name, cypher, .. } in queries { | |
| let res = self | |
| ._execute_query(spawn_id.as_str(), q_name.as_str(), cypher.as_str()) | |
| .await; | |
| // info!( | |
| // "executed: query_name={}, query:{}, res {:?}", | |
| // query_name, query, _res | |
| // ); | |
| if let Err(e) = res { | |
| error!("Error executing query: {}, the error is: {:?}", cypher, e); | |
| } | |
| } | |
| } | |
| Err(arc) => { | |
| error!( | |
| "Failed to unwrap queries iterator, Remaining references count: {}", | |
| Arc::strong_count(&arc) | |
| ); | |
| } | |
| } | |
| for PreparedQuery { q_name, cypher, .. } in queries.iter() { | |
| let res = self | |
| ._execute_query(spawn_id.as_str(), q_name.as_str(), cypher.as_str()) | |
| .await; | |
| if let Err(e) = res { | |
| error!("Error executing query: {}, the error is: {:?}", cypher, e); | |
| } | |
| } |
| pub mod scenario; | ||
| pub mod utils; | ||
|
|
||
| pub(crate) const REDIS_DATA_DIR: &str = "./redis-data"; |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Make REDIS_DATA_DIR configurable
Using a hardcoded relative path for the Redis data directory might cause issues in different deployment environments.
-pub(crate) const REDIS_DATA_DIR: &str = "./redis-data";
+pub(crate) const REDIS_DATA_DIR: &str = option_env!("REDIS_DATA_DIR").unwrap_or("./redis-data");📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| pub(crate) const REDIS_DATA_DIR: &str = "./redis-data"; | |
| pub(crate) const REDIS_DATA_DIR: &str = option_env!("REDIS_DATA_DIR").unwrap_or("./redis-data"); |
| pub async fn redis_shutdown() -> BenchmarkResult<()> { | ||
| info!("Shutting down Redis"); | ||
|
|
||
| // Set a timeout of 20 seconds | ||
| let timeout_duration = Duration::from_secs(20); | ||
|
|
||
| // Attempt to open the Redis client and connection with a timeout | ||
| let result = tokio::time::timeout(timeout_duration, async { | ||
| let client = redis::Client::open("redis://127.0.0.1:6379/")?; | ||
| let mut con = client.get_multiplexed_async_connection().await?; | ||
|
|
||
| // Send the SHUTDOWN command | ||
| let response: String = redis::cmd("SHUTDOWN").query_async(&mut con).await?; | ||
| info!("Redis shutdown command response: {}", response); | ||
|
|
||
| Ok::<(), BenchmarkError>(()) | ||
| }) | ||
| .await; | ||
|
|
||
| match result { | ||
| Ok(Ok(())) => { | ||
| info!("Redis shutdown command executed successfully."); | ||
| Ok(()) | ||
| } | ||
| Ok(Err(_)) => Ok(()), | ||
| Err(e) => { | ||
| error!( | ||
| "Failed to shutdown Redis within {} seconds: {}. Attempting to forcefully kill the process.", | ||
| timeout_duration.as_secs(), | ||
| e | ||
| ); | ||
| let redis_pid = get_command_pid("redis-server").await?; | ||
| error!("Killing Redis process with PID: {}", redis_pid); | ||
| kill_process(redis_pid).await?; | ||
| Ok::<(), BenchmarkError>(()) | ||
| } |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Consider retrying Redis shutdown before force kill.
The Redis shutdown implementation immediately falls back to force kill on timeout. Consider adding a retry mechanism before resorting to force kill.
Apply this diff to add retries:
+const REDIS_SHUTDOWN_RETRY_COUNT: u32 = 3;
+const REDIS_SHUTDOWN_RETRY_DELAY_SECS: u64 = 5;
pub async fn redis_shutdown() -> BenchmarkResult<()> {
info!("Shutting down Redis");
- let timeout_duration = Duration::from_secs(20);
+ let timeout_duration = Duration::from_secs(REDIS_SHUTDOWN_TIMEOUT_SECS);
+
+ for retry in 0..REDIS_SHUTDOWN_RETRY_COUNT {
+ info!("Attempting graceful shutdown (attempt {})", retry + 1);
let result = tokio::time::timeout(timeout_duration, async {
let client = redis::Client::open("redis://127.0.0.1:6379/")?;
let mut con = client.get_multiplexed_async_connection().await?;
let response: String = redis::cmd("SHUTDOWN").query_async(&mut con).await?;
info!("Redis shutdown command response: {}", response);
Ok::<(), BenchmarkError>(())
})
.await;
match result {
Ok(Ok(())) => {
info!("Redis shutdown command executed successfully.");
return Ok(());
}
Ok(Err(_)) => return Ok(()),
Err(e) => {
error!(
"Shutdown attempt {} failed: {}",
retry + 1,
e
);
if retry < REDIS_SHUTDOWN_RETRY_COUNT - 1 {
sleep(Duration::from_secs(REDIS_SHUTDOWN_RETRY_DELAY_SECS)).await;
continue;
}
}
}
}
error!("Graceful shutdown failed after {} attempts. Forcing kill.", REDIS_SHUTDOWN_RETRY_COUNT);
let redis_pid = get_command_pid("redis-server").await?;
error!("Killing Redis process with PID: {}", redis_pid);
kill_process(redis_pid).await?;
Ok(())Committable suggestion skipped: line range outside the PR's diff.
| // Set the combined subscriber as the global default | ||
| subscriber.init(); | ||
|
|
||
| let prometheus_endpoint = benchmark::prometheus_endpoint::PrometheusEndpoint::default(); |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Improve Prometheus endpoint configuration and shutdown.
The Prometheus endpoint initialization uses default settings and lacks proper shutdown handling.
Consider these improvements:
+use std::net::SocketAddr;
+
+#[derive(Debug)]
+struct PrometheusConfig {
+ addr: SocketAddr,
+ shutdown_timeout: Duration,
+}
+
+impl Default for PrometheusConfig {
+ fn default() -> Self {
+ Self {
+ addr: "127.0.0.1:9091".parse().unwrap(),
+ shutdown_timeout: Duration::from_secs(10),
+ }
+ }
+}
- let prometheus_endpoint = benchmark::prometheus_endpoint::PrometheusEndpoint::default();
+ let prometheus_config = PrometheusConfig::default();
+ let prometheus_endpoint = benchmark::prometheus_endpoint::PrometheusEndpoint::new(
+ prometheus_config.addr,
+ ).map_err(|e| OtherError(format!("Failed to initialize Prometheus endpoint: {}", e)))?;
// ... rest of the main function ...
- drop(prometheus_endpoint);
+ if let Err(e) = tokio::time::timeout(
+ prometheus_config.shutdown_timeout,
+ prometheus_endpoint.shutdown(),
+ ).await {
+ error!("Prometheus endpoint shutdown timed out: {}", e);
+ }Also applies to: 126-126
src/main.rs
Outdated
| // prepare the mpsc channel | ||
| let (tx, rx) = tokio::sync::mpsc::channel::<PreparedQuery>(20 * parallel); | ||
| let rx: Arc<Mutex<Receiver<PreparedQuery>>> = Arc::new(Mutex::new(rx)); | ||
|
|
||
| // iterate over queries and send them to the workers | ||
|
|
||
| let filler_handles = vec![ | ||
| // fill_queries(number_of_queries, tx.clone())?, | ||
| fill_queries(number_of_queries, tx.clone())?, | ||
| ]; | ||
|
|
||
| let mut workers_handles = Vec::with_capacity(parallel); | ||
| // start workers | ||
| let start = Instant::now(); | ||
| falkor | ||
| .execute_query_iterator(queries, &mut metric_collector) | ||
| .await?; | ||
| for spawn_id in 0..parallel { | ||
| let handle = spawn_worker(&falkor, spawn_id, &rx).await?; | ||
| workers_handles.push(handle); | ||
| } | ||
|
|
||
| // wait for the filler to finish drop the transmission side | ||
| // to let the workers know that they should stop | ||
| for handle in filler_handles { | ||
| let _ = handle.await; | ||
| } | ||
| drop(tx); | ||
|
|
||
| for handle in workers_handles { | ||
| let _ = handle.await; | ||
| } |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Improve worker coordination and error handling.
The current implementation of parallel workers could be enhanced with better coordination and error handling.
Consider these improvements:
- Use a shared atomic counter for tracking total processed queries
- Add error aggregation from workers
- Implement graceful shutdown on worker errors
+use std::sync::atomic::{AtomicU64, Ordering};
+use tokio::sync::mpsc::error::SendError;
+#[derive(Debug)]
+struct WorkerStats {
+ processed: Arc<AtomicU64>,
+ errors: Arc<AtomicU64>,
+}
+impl WorkerStats {
+ fn new() -> Self {
+ Self {
+ processed: Arc::new(AtomicU64::new(0)),
+ errors: Arc::new(AtomicU64::new(0)),
+ }
+ }
+}
async fn run_falkor(
size: Size,
number_of_queries: u64,
parallel: usize,
) -> BenchmarkResult<()> {
if parallel == 0 {
return Err(OtherError(
"Parallelism level must be greater than zero.".to_string(),
));
}
+ let stats = WorkerStats::new();
let falkor: Falkor<Stopped> = benchmark::falkor::Falkor::default();
// prepare the mpsc channel
let (tx, rx) = tokio::sync::mpsc::channel::<PreparedQuery>(20 * parallel);
let rx: Arc<Mutex<Receiver<PreparedQuery>>> = Arc::new(Mutex::new(rx));
- let filler_handles = vec![fill_queries(number_of_queries, tx.clone())?];
+ let filler_handle = fill_queries(number_of_queries, tx)?;
let mut workers_handles = Vec::with_capacity(parallel);
let start = Instant::now();
for spawn_id in 0..parallel {
- let handle = spawn_worker(&falkor, spawn_id, &rx).await?;
+ let handle = spawn_worker(
+ &falkor,
+ spawn_id,
+ &rx,
+ WorkerStats {
+ processed: Arc::clone(&stats.processed),
+ errors: Arc::clone(&stats.errors),
+ },
+ ).await?;
workers_handles.push(handle);
}
- for handle in filler_handles {
- let _ = handle.await;
- }
+ if let Err(e) = filler_handle.await {
+ error!("Query filler failed: {:?}", e);
+ return Err(OtherError("Query filler failed".to_string()));
+ }
drop(tx);
+ let mut worker_errors = Vec::new();
for handle in workers_handles {
- let _ = handle.await;
+ if let Err(e) = handle.await {
+ error!("Worker failed: {:?}", e);
+ worker_errors.push(e);
+ }
}
+
+ if !worker_errors.is_empty() {
+ return Err(OtherError(format!(
+ "{} workers failed during execution",
+ worker_errors.len()
+ )));
+ }
let elapsed = start.elapsed();
+ let total_processed = stats.processed.load(Ordering::Relaxed);
+ let total_errors = stats.errors.load(Ordering::Relaxed);
+
info!(
- "running {} queries took {:?}",
+ "Processed {} queries ({} errors) in {:?}",
format_number(number_of_queries),
+ format_number(total_errors),
elapsed
);Committable suggestion skipped: line range outside the PR's diff.
| "expr": "sum by (vendor) (rate(operations_total{vendor=\"falkor\"}[1m]))", | ||
| "legendFormat": "executor {{spawn_id}}", |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Consolidate duplicate queries/sec panels.
There are two panels (IDs 4 and 5) showing the same queries/sec metrics with slightly different visualizations.
Merge these panels into a single, more comprehensive view:
- "expr": "sum by (vendor) (rate(operations_total{vendor=\"falkor\"}[1m]))",
- "legendFormat": "executor {{spawn_id}}",
+ "expr": "sum by (vendor) (rate(operations_total{vendor=\"falkor\"}[1m]))",
+ "legendFormat": "Total",
+ "refId": "A"
+ },
+ {
+ "expr": "sum by (vendor, spawn_id) (rate(operations_total{vendor=\"falkor\"}[1m]))",
+ "legendFormat": "Worker {{spawn_id}}",Also applies to: 962-963
Use ro_exec on read query (should work with local falkordb-rs from branch https://github.com/FalkorDB/falkordb-rs/tree/fix_ro_query_builder
There was a problem hiding this comment.
Actionable comments posted: 3
🧹 Outside diff range and nitpick comments (9)
src/process_monitor.rs (3)
42-59: Consider implementing exponential backoff on process restartsCurrently, when the process exits unexpectedly, the
ProcessMonitorrestarts it after a 1-second sleep. If the process is failing rapidly, this can lead to tight restart loops consuming resources. Consider implementing an exponential backoff strategy to prevent rapid restart cycles.Possible implementation:
sleep(Duration::from_secs(1)).await; + // Implement exponential backoff + let restart_count = restarts_counter.get(); + let backoff_duration = std::cmp::min(64, 2_u64.pow(restart_count as u32)); + sleep(Duration::from_secs(backoff_duration)).await;
88-110: Enhance logging and error handling in process terminationWhen forcefully killing the process after a timeout, it's important to log whether the process was successfully killed. Currently, only errors are logged if the kill operation fails. Consider adding a success message to confirm that the process was killed, and handle any potential errors accordingly.
Apply this diff to improve logging:
error!("Process didn't terminate within grace period, forcing kill"); if let Err(e) = child.kill().await { error!("Failed to kill process: {:?}", e); + } else { + info!("Process forcefully killed after exceeding grace period."); }
70-86: Consider capturing or redirecting subprocess outputCurrently, the subprocess's
stdoutandstderrare not captured or redirected. If the subprocess outputs important logs or error messages, capturing its output can be valuable for debugging or logging purposes. Consider redirecting the child'sstdoutandstderrto log files or to the parent process's output.Possible code modification:
let mut command = Command::new(&self.command); command.args(&self.args); + command.stdout(std::process::Stdio::inherit()); + command.stderr(std::process::Stdio::inherit());todo.md (2)
4-7: Adjust indentation to comply with Markdown standardsThe nested list items are indented by 4 spaces, but Markdown standards (and markdownlint rule MD007) suggest using 2 spaces for indentation to ensure consistent rendering across different Markdown parsers.
Apply this diff to fix the indentation:
- - [ ] read/write without increase the graph size - - [ ] set read/write cli - - [x] read using GRAPH.RO_QUERY - - [ ] delete data when update + - [ ] read/write without increase the graph size + - [ ] set read/write cli + - [x] read using GRAPH.RO_QUERY + - [ ] delete data when update🧰 Tools
🪛 LanguageTool
[uncategorized] ~4-~4: This verb may not be in the correct form. Consider using a different form for this context.
Context: ...te vs read - [ ] read/write without increase the graph size - [ ] set read/write...(AI_EN_LECTOR_REPLACEMENT_VERB_FORM)
🪛 Markdownlint (0.35.0)
4-4: Expected: 2; Actual: 4
Unordered list indentation(MD007, ul-indent)
5-5: Expected: 2; Actual: 4
Unordered list indentation(MD007, ul-indent)
6-6: Expected: 2; Actual: 4
Unordered list indentation(MD007, ul-indent)
7-7: Expected: 2; Actual: 4
Unordered list indentation(MD007, ul-indent)
4-4: Correct verb forms for clarityThe subtask descriptions on lines 4 and 7 contain verb form errors that may affect readability.
- Line 4: Change "increase" to "increasing" for proper verb form.
- Line 7: Change "update" to "updating" for consistency.
Apply this diff to correct the verb forms:
- - [ ] read/write without increase the graph size + - [ ] read/write without increasing the graph size ... - - [ ] delete data when update + - [ ] delete data when updatingAlso applies to: 7-7
🧰 Tools
🪛 LanguageTool
[uncategorized] ~4-~4: This verb may not be in the correct form. Consider using a different form for this context.
Context: ...te vs read - [ ] read/write without increase the graph size - [ ] set read/write...(AI_EN_LECTOR_REPLACEMENT_VERB_FORM)
🪛 Markdownlint (0.35.0)
4-4: Expected: 2; Actual: 4
Unordered list indentation(MD007, ul-indent)
src/utils.rs (1)
Line range hint
29-29: Correct the error message to reflect the actual commandIn the
spawn_commandfunction, the error message refers to "Failed to spawn Neo4j process," but the command being executed may not be Neo4j. This could be misleading. Consider updating the error message to reflect the actual command.Apply this diff to fix the error message:
return Err(FailedToSpawnProcessError( io::Error::new(std::io::ErrorKind::Other, "Process failed"), format!( - "Failed to spawn Neo4j process, path: {} with args: {}, Error: {}", + "Failed to spawn process, command: {} with args: {}, Error: {}", command, args_str, stderr ), ));src/main.rs (3)
33-40: Consider extracting tracing setup to a separate function.The tracing setup logic could be moved to a dedicated function for better maintainability and reusability.
+fn setup_tracing() -> BenchmarkResult<()> { + let filter = EnvFilter::from_default_env().add_directive(LevelFilter::INFO.into()); + let subscriber = fmt() + .pretty() + .with_file(true) + .with_line_number(true) + .with_env_filter(filter); + subscriber.init(); + Ok(()) +} + async fn main() -> BenchmarkResult<()> { let mut cmd = Cli::command(); let cli = Cli::parse(); - let filter = EnvFilter::from_default_env().add_directive(LevelFilter::INFO.into()); - let subscriber = fmt() - .pretty() - .with_file(true) - .with_line_number(true) - .with_env_filter(filter); - subscriber.init(); + setup_tracing()?;
109-109: Consider implementing graceful shutdown for Prometheus endpoint.Simply dropping the Prometheus endpoint might not allow enough time for pending operations to complete.
- drop(prometheus_endpoint); + if let Err(e) = prometheus_endpoint.shutdown().await { + error!("Failed to shutdown Prometheus endpoint: {}", e); + }
328-341: Add progress reporting for data initialization.Consider adding progress reporting to track the initialization status.
+ let mut processed = 0; + let report_interval = 1000; while let Some(result) = data_iterator.next().await { match result { Ok(query) => { falkor_client ._execute_query("loader", "", query.as_str()) .await?; + processed += 1; + if processed % report_interval == 0 { + info!("Processed {} records", processed); + } } Err(e) => { error!("error {}", e); + processed += 1; } } }
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Review profile: CHILL
⛔ Files ignored due to path filters (1)
Cargo.lockis excluded by!**/*.lock
📒 Files selected for processing (9)
Cargo.toml(1 hunks)src/cli.rs(3 hunks)src/falkor/falkor_driver.rs(1 hunks)src/falkor/falkor_process.rs(1 hunks)src/main.rs(7 hunks)src/process_monitor.rs(1 hunks)src/queries_repository.rs(8 hunks)src/utils.rs(9 hunks)todo.md(1 hunks)
🚧 Files skipped from review as they are similar to previous changes (4)
- src/queries_repository.rs
- src/falkor/falkor_process.rs
- Cargo.toml
- src/falkor/falkor_driver.rs
🧰 Additional context used
🪛 LanguageTool
todo.md
[uncategorized] ~4-~4: This verb may not be in the correct form. Consider using a different form for this context.
Context: ...te vs read - [ ] read/write without increase the graph size - [ ] set read/write...
(AI_EN_LECTOR_REPLACEMENT_VERB_FORM)
🪛 Markdownlint (0.35.0)
todo.md
4-4: Expected: 2; Actual: 4
Unordered list indentation
(MD007, ul-indent)
5-5: Expected: 2; Actual: 4
Unordered list indentation
(MD007, ul-indent)
6-6: Expected: 2; Actual: 4
Unordered list indentation
(MD007, ul-indent)
7-7: Expected: 2; Actual: 4
Unordered list indentation
(MD007, ul-indent)
🔇 Additional comments (4)
src/cli.rs (2)
7-7: Verify the necessity of making Cli and command public
The Cli struct and its command field have been changed from pub(crate) to pub, making them publicly accessible outside the crate. Please verify if exposing these elements publicly is necessary, as it can affect encapsulation and module boundaries.
Also applies to: 9-9
90-93: Review the use of default_missing_value with default_value_t
The parallel argument specifies both default_value_t = 1 and default_missing_value = "1". When default_value_t is set, specifying default_missing_value may be redundant unless there's a specific need for it. Please verify if both are necessary.
src/utils.rs (1)
281-316: Consider retrying Redis shutdown before forceful termination
The redis_shutdown function attempts a graceful shutdown of Redis but immediately proceeds to forcefully kill the process if the shutdown does not complete within the timeout. Consider adding a retry mechanism to attempt graceful shutdown multiple times before resorting to forceful termination.
Refer to previous suggestion:
+const REDIS_SHUTDOWN_RETRY_COUNT: u32 = 3;
+const REDIS_SHUTDOWN_RETRY_DELAY_SECS: u64 = 5;
pub async fn redis_shutdown() -> BenchmarkResult<()> {
info!("Shutting down Redis");
let timeout_duration = Duration::from_secs(20);
+ for retry in 0..REDIS_SHUTDOWN_RETRY_COUNT {
+ info!("Attempting graceful shutdown (attempt {})", retry + 1);
let result = tokio::time::timeout(timeout_duration, async {
// Existing shutdown logic...
})
.await;
match result {
Ok(Ok(())) => {
info!("Redis shutdown command executed successfully.");
return Ok(());
}
Ok(Err(_)) => return Ok(()),
Err(e) => {
error!(
"Shutdown attempt {} failed: {}",
retry + 1,
e
);
if retry < REDIS_SHUTDOWN_RETRY_COUNT - 1 {
sleep(Duration::from_secs(REDIS_SHUTDOWN_RETRY_DELAY_SECS)).await;
continue;
}
}
}
}
error!("Graceful shutdown failed after {} attempts. Forcing kill.", REDIS_SHUTDOWN_RETRY_COUNT);
let redis_pid = get_command_pid("redis-server").await?;
error!("Killing Redis process with PID: {}", redis_pid);
kill_process(redis_pid).await?;
Ok(())src/main.rs (1)
207-214:
Improve worker error handling and progress tracking.
The current implementation silently ignores worker errors and doesn't track overall progress.
+#[derive(Debug)]
+struct WorkerError {
+ worker_id: usize,
+ error: Box<dyn std::error::Error + Send + Sync>,
+}
+
+let mut worker_errors = Vec::new();
for handle in workers_handles {
- let _ = handle.await;
+ if let Err(e) = handle.await {
+ error!("Worker failed: {:?}", e);
+ worker_errors.push(e);
+ }
}
+
+if !worker_errors.is_empty() {
+ return Err(OtherError(format!(
+ "{} workers failed during execution",
+ worker_errors.len()
+ )));
+}Likely invalid or redundant comment.
src/cli.rs
Outdated
| short = 'w', | ||
| long, | ||
| alias = "workers", | ||
| alias = "parallel", | ||
| default_value_t = 1 | ||
| )] |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Correct the usage of multiple alias attributes
In the number_of_workers argument definition for PrepareQueries, multiple alias attributes are specified separately. The Clap library expects multiple aliases to be provided as a list to a single aliases attribute.
Apply this diff to correct the aliases:
#[arg(
short = 'w',
long,
- alias = "workers",
- alias = "parallel",
+ aliases = ["workers", "parallel"],
default_value_t = 1
)]📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| short = 'w', | |
| long, | |
| alias = "workers", | |
| alias = "parallel", | |
| default_value_t = 1 | |
| )] | |
| short = 'w', | |
| long, | |
| aliases = ["workers", "parallel"], | |
| default_value_t = 1 | |
| )] |
src/main.rs
Outdated
| let queries_repository = | ||
| benchmark::queries_repository::UsersQueriesRepository::new(9998, 121716); | ||
| let queries = Box::new(queries_repository.random_queries(number_of_queries)); |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Avoid hard-coding query repository parameters.
The values 9998 and 121716 should be configurable parameters or derived from the actual data.
+const DEFAULT_NODE_COUNT: u64 = 9998;
+const DEFAULT_RELATION_COUNT: u64 = 121716;
+
let queries_repository =
- benchmark::queries_repository::UsersQueriesRepository::new(9998, 121716);
+ benchmark::queries_repository::UsersQueriesRepository::new(
+ node_count.try_into().unwrap_or(DEFAULT_NODE_COUNT),
+ relation_count.try_into().unwrap_or(DEFAULT_RELATION_COUNT),
+ );Committable suggestion skipped: line range outside the PR's diff.
src/main.rs
Outdated
| match received { | ||
| Some(prepared_query) => { | ||
| let start_time = Instant::now(); | ||
|
|
||
| let r = client | ||
| .execute_prepared_query(worker_id_str, &prepared_query) | ||
| .await; | ||
| let duration = start_time.elapsed(); | ||
| match r { | ||
| Ok(_) => { | ||
| FALKOR_SUCCESS_REQUESTS_DURATION_HISTOGRAM | ||
| .observe(duration.as_secs_f64()); | ||
| counter += 1; | ||
| if counter % 1000 == 0 { | ||
| info!("worker {} processed {} queries", worker_id, counter); | ||
| } | ||
| } | ||
| Err(e) => { | ||
| FALKOR_ERROR_REQUESTS_DURATION_HISTOGRAM | ||
| .observe(duration.as_secs_f64()); | ||
| let seconds_wait = 3u64; | ||
| info!( | ||
| "worker {} failed to process query, not sleeping for {} seconds {:?}", | ||
| worker_id, seconds_wait, e | ||
| ); | ||
| } | ||
| } | ||
| } |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Enhance worker error handling and resource management.
The worker error handling could be improved with better error reporting and resource cleanup.
match received {
Some(prepared_query) => {
let start_time = Instant::now();
+ let query_id = prepared_query.id().to_string();
let r = client
.execute_prepared_query(worker_id_str, &prepared_query)
.await;
let duration = start_time.elapsed();
match r {
Ok(_) => {
FALKOR_SUCCESS_REQUESTS_DURATION_HISTOGRAM
.observe(duration.as_secs_f64());
counter += 1;
if counter % 1000 == 0 {
info!("worker {} processed {} queries", worker_id, counter);
}
}
Err(e) => {
FALKOR_ERROR_REQUESTS_DURATION_HISTOGRAM
.observe(duration.as_secs_f64());
- let seconds_wait = 3u64;
- info!(
+ error!(
- "worker {} failed to process query, not sleeping for {} seconds {:?}",
- worker_id, seconds_wait, e
+ "worker {} failed to process query {}: {:?}",
+ worker_id, query_id, e
);
+ // Consider implementing retry logic or error reporting
}
}
}📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| match received { | |
| Some(prepared_query) => { | |
| let start_time = Instant::now(); | |
| let r = client | |
| .execute_prepared_query(worker_id_str, &prepared_query) | |
| .await; | |
| let duration = start_time.elapsed(); | |
| match r { | |
| Ok(_) => { | |
| FALKOR_SUCCESS_REQUESTS_DURATION_HISTOGRAM | |
| .observe(duration.as_secs_f64()); | |
| counter += 1; | |
| if counter % 1000 == 0 { | |
| info!("worker {} processed {} queries", worker_id, counter); | |
| } | |
| } | |
| Err(e) => { | |
| FALKOR_ERROR_REQUESTS_DURATION_HISTOGRAM | |
| .observe(duration.as_secs_f64()); | |
| let seconds_wait = 3u64; | |
| info!( | |
| "worker {} failed to process query, not sleeping for {} seconds {:?}", | |
| worker_id, seconds_wait, e | |
| ); | |
| } | |
| } | |
| } | |
| match received { | |
| Some(prepared_query) => { | |
| let start_time = Instant::now(); | |
| let query_id = prepared_query.id().to_string(); | |
| let r = client | |
| .execute_prepared_query(worker_id_str, &prepared_query) | |
| .await; | |
| let duration = start_time.elapsed(); | |
| match r { | |
| Ok(_) => { | |
| FALKOR_SUCCESS_REQUESTS_DURATION_HISTOGRAM | |
| .observe(duration.as_secs_f64()); | |
| counter += 1; | |
| if counter % 1000 == 0 { | |
| info!("worker {} processed {} queries", worker_id, counter); | |
| } | |
| } | |
| Err(e) => { | |
| FALKOR_ERROR_REQUESTS_DURATION_HISTOGRAM | |
| .observe(duration.as_secs_f64()); | |
| error!( | |
| "worker {} failed to process query {}: {:?}", | |
| worker_id, query_id, e | |
| ); | |
| // Consider implementing retry logic or error reporting | |
| } | |
| } | |
| } |
There was a problem hiding this comment.
Actionable comments posted: 0
🧹 Outside diff range and nitpick comments (3)
Cargo.toml (1)
51-54: Remove extra blank linesMultiple consecutive blank lines can be reduced to a single blank line for better file organization.
src/queries_repository.rs (2)
226-294: Consider refactoring aggregate expansion queriesThe aggregate expansion queries follow a similar pattern with increasing path lengths. Consider generating these queries programmatically to reduce code duplication.
Example refactor:
fn add_aggregate_expansion_queries(builder: QueriesRepositoryBuilder<Flavour>, max_depth: usize) -> QueriesRepositoryBuilder<Flavour> { (1..=max_depth).fold(builder, |b, depth| { let path = "-->".repeat(depth); b.add_query( format!("aggregate_expansion_{}", depth), QueryType::Read, move |random, _flavour| { QueryBuilder::new() .text(format!("MATCH (s:User {{id: $id}}){path}(n:User) RETURN DISTINCT n.id")) .param("id", random.random_vertex()) .build() } ).add_query( format!("aggregate_expansion_{}_with_filter", depth), QueryType::Read, move |random, _flavour| { QueryBuilder::new() .text(format!("MATCH (s:User {{id: $id}}){path}(n:User) WHERE n.age >= 18 RETURN DISTINCT n.id")) .param("id", random.random_vertex()) .build() } ) }) }
331-346: Add tests for critical functionalityThe test coverage appears limited. Consider adding tests for:
- PreparedQuery creation and serialization
- Random query generation
- Edge cases in RandomUtil
- Aggregate expansion queries
Would you like me to help generate additional test cases?
📜 Review details
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Review profile: CHILL
⛔ Files ignored due to path filters (1)
Cargo.lockis excluded by!**/*.lock
📒 Files selected for processing (4)
.github/workflows/ci.yml(1 hunks)Cargo.toml(1 hunks)src/queries_repository.rs(8 hunks)src/query.rs(4 hunks)
🚧 Files skipped from review as they are similar to previous changes (1)
- src/query.rs
🔇 Additional comments (11)
.github/workflows/ci.yml (1)
32-35: LGTM! Enhanced build configuration and code quality checks
The changes improve the CI pipeline by:
- Building all targets with all features enabled
- Adding Clippy checks with warnings treated as errors
This ensures comprehensive testing and maintains high code quality standards.
Cargo.toml (4)
15-16: LGTM! Clippy configuration for benchmark tool
The result_large_err allowance is appropriate for a benchmark tool where error types might need to carry detailed information.
34-34: Remove commented-out local path dependency
The commented-out local path dependency should be removed as it's no longer needed and was only used for testing.
42-45: Verify Prometheus integration dependencies
The new dependencies for Prometheus monitoring need version verification:
prometheus v0.13.4is at latest versionlazy_static v1.5is at latest versionhyper v0.14.31has a newer version available (1.5.1)
47-49: Document the binary target in README
The binary target configuration should be documented in the README to help users understand the project structure and available commands.
src/queries_repository.rs (6)
44-48: LGTM: Type aliases improve code clarity
The introduction of type aliases QueryFn and QueryEntry improves code readability and maintainability by providing clear, descriptive names for complex types.
179-184: LGTM: Efficient implementation of random_queries
The implementation efficiently uses filter_map to generate an iterator of random queries, which is memory-efficient for large counts.
304-329: LGTM: Well-structured PreparedQuery implementation
The PreparedQuery struct provides good encapsulation of query details with proper serialization support. The implementation follows Rust best practices.
163-171:
Potential infinite loop in random_path when vertices ≤ 1
If self.vertices is less than or equal to 1, random_vertex() will always return the same value. Consequently, the while end == start loop may become infinite because start and end will always be equal.
Apply this diff to fix the issue:
fn random_path(&self) -> (i32, i32) {
+ if self.vertices <= 1 {
+ panic!("Not enough vertices to generate a path");
+ }
let start = self.random_vertex();
let mut end = self.random_vertex();
// Ensure start and end are different
while end == start {
end = self.random_vertex();
}
(start, end)
}13-13: Breaking change: Flavour enum is now public
The visibility of Flavour enum has been changed from pub(crate) to pub. This is a breaking change that could affect API consumers.
200-205: Verify if commented-out queries are intentionally disabled
Several query definitions are commented out. Please verify if this is intentional or if these queries should be implemented.
Also applies to: 218-225
✅ Verification successful
Let me try a different approach to verify the commented-out queries.
Let me check for any patterns or related code to understand if this is part of a larger testing strategy.
Commented queries appear to be intentionally disabled test cases
The commented queries are write operations that create temporary test entities (UserTemp), which are intentionally disabled while other related queries (read and update operations on User) remain active. This appears to be a deliberate testing strategy where temporary test data creation is disabled.
- Two write operations are consistently commented out:
single_vertex_write: Creates temporary user nodessingle_edge_write: Related to edge creation
- Active queries operate on the main
Usernodes instead of temporary ones
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Check commit history for these queries
git log -S "single_vertex_write" --patch -- src/queries_repository.rs
git log -S "single_edge_write" --patch -- src/queries_repository.rs
Length of output: 0
Script:
#!/bin/bash
# Check the current state of queries in the file
rg -A 5 "add_query.*single_vertex" src/queries_repository.rs
# Look for any related test files or documentation
fd -e rs -e md "single_vertex"
Length of output: 1056
Script:
#!/bin/bash
# Check for UserTemp references to understand if it's an intentional testing pattern
rg "UserTemp" -A 3 -B 3
# Look for other commented queries to see if this is a pattern
rg "^[\s]*//[\s]*\.add_query" src/queries_repository.rs
Length of output: 829
There was a problem hiding this comment.
Actionable comments posted: 3
🧹 Outside diff range and nitpick comments (3)
src/bin/scheduler.rs (2)
100-119: Simplifycompute_offset_mslogicThe
compute_offset_msfunction can be simplified for clarity and efficiency.Refactored function:
fn compute_offset_ms(msg: &Msg) -> i64 { let current_time = Instant::now(); let target_time = msg.start_time + Duration::from_millis(msg.offset); let offset = target_time.duration_since(current_time).as_millis() as i64; offset }This eliminates unnecessary conditional logic and directly computes the offset in milliseconds.
63-64: Implement metrics recording for late messagesThere's a TODO to record metrics for late messages. Implementing this will provide valuable insights into system performance and message processing delays.
Would you like assistance in implementing metrics collection for late messages using Prometheus?
Cargo.toml (1)
15-17: Review Clippy lint allowance forresult_large_errAllowing the
clippy::result_large_errlint may hide potential issues with error handling and result types that are too large.Consider addressing the underlying issues that trigger this lint instead of allowing it globally. If necessary, suppress the lint at specific locations.
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (2)
Cargo.toml(1 hunks)src/bin/scheduler.rs(1 hunks)
🔇 Additional comments (3)
Cargo.toml (3)
44-44: Update hyper dependency to the latest version
The current hyper version 0.14.31 is outdated. The latest version is 1.5.1. Updating ensures access to the latest features and security patches.
Apply this diff to update hyper:
-hyper = { version = "0.14.31", features = ["server", "runtime", "http1", "tcp"] }
+hyper = { version = "1.5.1", features = ["server", "runtime", "http1", "tcp"] }33-33:
Replace local path dependency with versioned dependency
The falkordb dependency is commented out with a local path, which is not suitable for production use.
Replace the local path dependency with a versioned dependency from crates.io:
-#falkordb = { path = "/Users/barak/dev/falkordb-rs", features = ["tokio"] }
+falkordb = { version = "0.1.10", features = ["tokio"] }Ensure that the falkordb crate version specified is available on crates.io.
21-44:
Correct invalid dependency version numbers
Several dependencies have version numbers that do not correspond to valid releases on crates.io. This could cause build failures or unexpected behavior.
Please update the dependencies with the correct latest stable versions:
thiserror = "1.0.64"tokio = { version = "1.29.1", features = ["full", "tracing"] }tokio-stream = { version = "0.1.16", features = ["io-util"] }clap = { version = "4.3.10", features = ["cargo", "derive", "env"] }serde = { version = "1.0.166", features = ["derive"] }serde_json = "1.0.104"tracing = "0.1.38"tracing-subscriber = { version = "0.3.17", features = ["env-filter"] }lazy_static = "1.4.0"hyper = { version = "1.5.1", features = ["server", "runtime", "http1", "tcp"] }(See note below)
Apply this diff to correct the versions:
thiserror = "1.0.64"
-tokio = { version = "1.42.0", features = ["full", "tracing"] }
+tokio = { version = "1.29.1", features = ["full", "tracing"] }
-tokio-stream = { version = "0.1.17", features = ["io-util"] }
+tokio-stream = { version = "0.1.16", features = ["io-util"] }
-clap = { version = "4.5.23", features = ["cargo", "derive", "env"] }
+clap = { version = "4.3.10", features = ["cargo", "derive", "env"] }
-serde = { version = "1.0.215", features = ["derive"] }
+serde = { version = "1.0.166", features = ["derive"] }
-serde_json = "1.0.133"
+serde_json = "1.0.104"
-tracing = "0.1.41"
+tracing = "0.1.38"
-tracing-subscriber = { version = "0.3.19", features = ["env-filter"] }
+tracing-subscriber = { version = "0.3.17", features = ["env-filter"] }
-lazy_static = "1.5"
+lazy_static = "1.4.0"
-hyper = { version = "0.14.31", features = ["server", "runtime", "http1", "tcp"] }
+hyper = { version = "1.5.1", features = ["server", "runtime", "http1", "tcp"] }Please verify all dependency versions against crates.io to ensure they are correct.
Likely invalid or redundant comment.
src/bin/scheduler.rs
Outdated
| fn spawn_processor(receiver: &Arc<Mutex<Receiver<Msg>>>) -> JoinHandle<()> { | ||
| let receiver = Arc::clone(receiver); | ||
| tokio::spawn(async move { | ||
| let mut offset = 0; | ||
| loop { | ||
| let received = receiver.lock().await.recv().await; | ||
| match received { | ||
| None => { | ||
| info!("Received None, exiting, last offset was {:?}", offset); | ||
| return; | ||
| } | ||
| Some(received_msg) => { | ||
| offset = compute_offset_ms(&received_msg); | ||
| if offset > 0 { | ||
| // sleep offset millis | ||
| tokio::time::sleep(Duration::from_millis(offset as u64)).await; | ||
| } else { | ||
| // todo record metrics for late messages | ||
| } | ||
| // todo execute call | ||
| } | ||
| } | ||
| } | ||
| }) | ||
| } |
There was a problem hiding this comment.
Avoid holding a Mutex lock across .await points
In spawn_processor, acquiring a lock on the Receiver and holding it across an .await can lead to deadlocks and performance bottlenecks since it prevents other processors from receiving messages concurrently.
Consider restructuring to eliminate the need for a Mutex. One approach is to use a tokio::sync::mpsc::UnboundedReceiver for each processor. Alternatively, use a tokio::sync::broadcast channel, which allows multiple receivers to receive the same messages independently.
Example using broadcast:
// In main:
let (tx, _) = tokio::sync::broadcast::channel::<Msg>(16);
// ...
for _ in 0..n_processors {
spawn_processor(tx.subscribe());
}
// Modify spawn_processor:
fn spawn_processor(mut receiver: tokio::sync::broadcast::Receiver<Msg>) -> JoinHandle<()> {
tokio::spawn(async move {
let mut offset = 0;
loop {
match receiver.recv().await {
Ok(received_msg) => {
offset = compute_offset_ms(&received_msg);
// Process message...
}
Err(err) => {
info!("Receiver error: {:?}", err);
return;
}
}
}
})
}This allows processors to consume messages without needing to synchronize access.
src/bin/scheduler.rs
Outdated
| } else { | ||
| // todo record metrics for late messages | ||
| } | ||
| // todo execute call |
There was a problem hiding this comment.
Implement the execution logic for message processing
The TODO comment indicates that the core execution logic is yet to be implemented. This is essential for the scheduler to function correctly.
Do you need help implementing the message processing logic? I can assist in writing the code to execute the desired operations upon message receipt.
src/bin/scheduler.rs
Outdated
| let interval = 1000 / msg_per_sec as u64; | ||
| // anchor the start time to 200 ms from now | ||
| let start_time = Instant::now().add(Duration::from_millis(200)); | ||
| for count in 0..number_of_messages { | ||
| let offset = count as u64 * interval; | ||
| match sender.send(Msg { start_time, offset }).await { |
There was a problem hiding this comment.
Fix integer division causing zero interval in spawn_scheduler
The calculation of interval in line 83 results in zero when msg_per_sec exceeds 1000 due to integer division, leading to all messages having an offset of zero. This likely causes messages to be scheduled incorrectly.
Apply this diff to fix the calculation by using floating-point division and converting to nanoseconds for higher precision:
fn spawn_scheduler(
msg_per_sec: u32,
sender: Sender<Msg>,
number_of_messages: u32,
) -> JoinHandle<()> {
tokio::spawn(async move {
- let interval = 1000 / msg_per_sec as u64;
+ let interval = (1_000_000_000.0 / msg_per_sec as f64) as u64; // interval in nanoseconds
// anchor the start time to 200 ms from now
let start_time = Instant::now().add(Duration::from_millis(200));
for count in 0..number_of_messages {
let offset = count as u64 * interval;
match sender.send(Msg { start_time, offset }).await {
Ok(_) => {}
Err(e) => {
info!("Error sending message: {}, exiting", e);
return;
}
}
}
info!("All messages sent");
})
}Also, update the offset handling to use Duration::from_nanos(offset) for accurate scheduling.
Committable suggestion skipped: line range outside the PR's diff.
There was a problem hiding this comment.
Actionable comments posted: 7
🧹 Nitpick comments (10)
src/lib.rs (1)
78-83: Add unit suffixes to histogram metric namesThe histogram metrics measure response time but don't indicate the unit in their names. Following Prometheus naming best practices, metric names should include the unit suffix.
-"falkordb_response_time_success_histogram" +"falkordb_response_time_success_seconds" -"falkordb_response_time_error_histogram" +"falkordb_response_time_error_seconds" -"neo4j_response_time_success_histogram" +"neo4j_response_time_success_seconds" -"neo4j_response_time_error_histogram" +"neo4j_response_time_error_seconds"Also applies to: 84-89, 95-100, 101-106
readme.md (1)
186-203: Improve organization of Prometheus queries.The Prometheus queries section would benefit from better organization and documentation.
Consider organizing the queries into categories with descriptions:
### Benchmark Metrics - Operations Rate: ```promql sum by (vendor, spawn_id) (rate(operations_total{vendor="falkor"}[1m]))Shows the rate of operations per minute for each vendor and spawn ID.
Redis Metrics
Performance
- Command Processing Rate:
Shows the rate of processed commands per minute.rate(redis_commands_processed_total{instance=~"redis-exporter:9121"}[1m])Client Connections
- Active Clients:
Shows the number of currently connected clients.redis_connected_clients{instance=~"redis-exporter:9121"}<details> <summary>🧰 Tools</summary> <details> <summary>🪛 Markdownlint (0.37.0)</summary> 203-203: Expected: atx; Actual: setext Heading style (MD003, heading-style) </details> </details> </blockquote></details> <details> <summary>src/falkor/falkor_driver.rs (1)</summary><blockquote> `267-283`: **Add retry mechanism for transient failures.** The `_execute_query` method should implement retries for transient failures to improve reliability. ```diff + const MAX_RETRIES: u32 = 3; + const RETRY_DELAY_MS: u64 = 100; + pub async fn _execute_query<'a>( &'a mut self, spawn_id: &'a str, query_name: &'a str, query: &'a str, ) -> BenchmarkResult<()> { - OPERATION_COUNTER - .with_label_values(&["falkor", spawn_id, "", query_name, "", ""]) - .inc(); - - let falkor_result = self.graph.query(query).with_timeout(5000).execute(); - let timeout = Duration::from_secs(5); - let falkor_result = tokio::time::timeout(timeout, falkor_result).await; - Self::read_reply(spawn_id, query_name, query, falkor_result) + let mut attempts = 0; + loop { + OPERATION_COUNTER + .with_label_values(&["falkor", spawn_id, "", query_name, "", ""]) + .inc(); + + let falkor_result = self.graph.query(query).with_timeout(5000).execute(); + let timeout = Duration::from_secs(5); + let falkor_result = tokio::time::timeout(timeout, falkor_result).await; + match Self::read_reply(spawn_id, query_name, query, falkor_result) { + Ok(result) => return Ok(result), + Err(e) if attempts < Self::MAX_RETRIES => { + attempts += 1; + tokio::time::sleep(Duration::from_millis(Self::RETRY_DELAY_MS)).await; + continue; + } + Err(e) => return Err(e), + } + } }src/queries_repository.rs (4)
119-120: Consider using a single HashMap with QueryType as part of the key.The current implementation uses two separate HashMaps for read and write queries. This could lead to code duplication and make it harder to maintain.
Consider using a single HashMap with a composite key:
- read_queries: HashMap<String, QueryGenerator>, - write_queries: HashMap<String, QueryGenerator>, + queries: HashMap<(String, QueryType), QueryGenerator>,Also applies to: 126-127
174-177: Add documentation for RandomUtil methods.The
random_vertexandrandom_pathmethods lack documentation explaining their purpose and usage.Add documentation comments:
impl RandomUtil { + /// Generates a random vertex ID within the range [1, self.vertices] fn random_vertex(&self) -> i32 { let mut rng = rand::thread_rng(); rng.gen_range(1..=self.vertices) }
225-230: Consider removing commented-out code.The code contains commented-out query implementations that should either be implemented or removed.
Remove or implement the commented-out queries:
- // .add_query("single_vertex_write", QueryType::Write, |random, _flavour| { - // QueryBuilder::new() - // .text("CREATE (n:UserTemp {id : $id}) RETURN n") - // .param("id", random.random_vertex()) - // .build()
329-336: Add validation for PreparedQuery fields.The
PreparedQuerystruct should validate its fields during construction.Add validation in the
newmethod:pub fn new( q_name: String, q_type: QueryType, query: Query, ) -> Self { + if q_name.is_empty() { + panic!("Query name cannot be empty"); + } let cypher = query.to_cypher(); let bolt = query.to_bolt_struct(); Self { q_name, q_type, query, cypher, bolt, } }dashboards/neo4j_dashboard.json (2)
107-108: Simplify the query expression for successful queries.The current expression is overly complex and could be simplified.
Consider using:
- "expr": "sum by (vendor) (operations_total{vendor=\"neo4j\"}) - sum by (vendor) (operations_error_total{job=\"falkor_benchmark\"}) or (sum by (vendor) (operations_total{vendor=\"neo4j\"}) )", + "expr": "sum by (vendor) (operations_total{vendor=\"neo4j\"} - operations_error_total{job=\"falkor_benchmark\"} or operations_total{vendor=\"neo4j\"})",
625-628: Consider increasing the default time range.The current time range of 5 minutes might be too short for meaningful analysis.
"time": { - "from": "now-5m", + "from": "now-1h", "to": "now" },src/main.rs (1)
41-48: Consider using structured logging configuration.The logging configuration could be moved to a separate function or configuration file.
Extract logging setup to a dedicated function:
+fn setup_logging() -> BenchmarkResult<()> { let filter = EnvFilter::from_default_env().add_directive(LevelFilter::INFO.into()); let subscriber = fmt() .pretty() .with_file(true) .with_line_number(true) .with_env_filter(filter); - subscriber.init(); + subscriber.init().map_err(|e| OtherError(format!("Failed to initialize logging: {}", e))) +}
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📒 Files selected for processing (9)
dashboards/neo4j_dashboard.json(1 hunks)prometheus.yml(1 hunks)readme.md(2 hunks)src/cli.rs(2 hunks)src/falkor/falkor_driver.rs(1 hunks)src/lib.rs(1 hunks)src/main.rs(7 hunks)src/neo4j_client.rs(5 hunks)src/queries_repository.rs(9 hunks)
🚧 Files skipped from review as they are similar to previous changes (2)
- prometheus.yml
- src/neo4j_client.rs
🧰 Additional context used
🪛 Markdownlint (0.37.0)
readme.md
203-203: Expected: atx; Actual: setext
Heading style
(MD003, heading-style)
131-131: null
Bare URL used
(MD034, no-bare-urls)
132-132: null
Bare URL used
(MD034, no-bare-urls)
184-184: null
Bare URL used
(MD034, no-bare-urls)
185-185: null
Bare URL used
(MD034, no-bare-urls)
🔇 Additional comments (8)
src/lib.rs (2)
1-22: LGTM! Well-organized imports and clear module structure.
The imports are specific and the module structure provides a clear separation of concerns for the benchmarking framework.
24-24: Make REDIS_DATA_DIR configurable
Using a hardcoded relative path for the Redis data directory might cause issues in different deployment environments.
src/cli.rs (2)
7-9: LGTM! Visibility changes look good.
The struct visibility changes from pub(crate) to pub are appropriate for exposing the CLI interface.
58-65: LGTM! Write ratio validation looks good.
The parse_write_ratio function properly validates that the write ratio is between 0.0 and 1.0.
readme.md (1)
184-185: Format URLs as proper markdown links.
The bare URLs should be formatted as proper markdown links for better readability.
-Accessing grafana http://localhost:3000
-Accessing prometheus http://localhost:9090
+- Accessing Grafana: [http://localhost:3000](http://localhost:3000)
+- Accessing Prometheus: [http://localhost:9090](http://localhost:9090)🧰 Tools
🪛 Markdownlint (0.37.0)
184-184: null
Bare URL used
(MD034, no-bare-urls)
185-185: null
Bare URL used
(MD034, no-bare-urls)
src/falkor/falkor_driver.rs (1)
193-217: Avoid using Arc::try_unwrap to prevent runtime errors.
Using Arc::try_unwrap(queries) will only succeed if there are no other strong references to the Arc. This could lead to missed query executions.
- match Arc::try_unwrap(queries) {
- Ok(queries) => {
- for PreparedQuery { q_name, cypher, .. } in queries {
- let res = self
- ._execute_query(spawn_id.as_str(), q_name.as_str(), cypher.as_str())
- .await;
- if let Err(e) = res {
- error!("Error executing query: {}, the error is: {:?}", cypher, e);
- }
- }
- }
- Err(arc) => {
- error!(
- "Failed to unwrap queries iterator, Remaining references count: {}",
- Arc::strong_count(&arc)
- );
- }
- }
+ for PreparedQuery { q_name, cypher, .. } in queries.iter() {
+ let res = self
+ ._execute_query(spawn_id.as_str(), q_name.as_str(), cypher.as_str())
+ .await;
+ if let Err(e) = res {
+ error!("Error executing query: {}, the error is: {:?}", cypher, e);
+ }
+ }src/queries_repository.rs (1)
179-187: Add validation for vertex range in random_path.
The random_path method should validate that there are enough vertices to generate a path.
This is a duplicate of a previously identified issue regarding validation in the random_path method.
src/main.rs (1)
543-544:
Avoid hardcoding magic numbers.
The values 9998 and 121716 should be configurable or derived from actual data.
Extract these values to constants or configuration:
+const DEFAULT_VERTICES: i32 = 9998;
+const DEFAULT_EDGES: i32 = 121716;
+
let queries_repository =
- benchmark::queries_repository::UsersQueriesRepository::new(9998, 121716);
+ benchmark::queries_repository::UsersQueriesRepository::new(
+ DEFAULT_VERTICES,
+ DEFAULT_EDGES,
+ );Likely invalid or redundant comment.
| pub static ref FALKOR_SUCCESS_REQUESTS_DURATION_HISTOGRAM: Histogram = register_histogram!( | ||
| "falkordb_response_time_success_histogram", | ||
| "Response time histogram of the successful requests", | ||
| vec![0.0005, 0.001, 0.005, 0.01, 0.025, 0.05, 0.1, 0.25, 0.5, 1.0, 2.5, 5.0, 10.0,] | ||
| ) | ||
| .unwrap(); |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Extract histogram buckets to a constant to avoid duplication
The same bucket values are duplicated across all histogram metrics. This violates the DRY principle and makes maintenance harder.
Create a constant for the bucket values:
+const DURATION_BUCKETS: &[f64] = &[
+ 0.0005, 0.001, 0.005, 0.01, 0.025,
+ 0.05, 0.1, 0.25, 0.5, 1.0, 2.5, 5.0, 10.0
+];
pub static ref FALKOR_SUCCESS_REQUESTS_DURATION_HISTOGRAM: Histogram = register_histogram!(
"falkordb_response_time_success_histogram",
"Response time histogram of the successful requests",
- vec![0.0005, 0.001, 0.005, 0.01, 0.025, 0.05, 0.1, 0.25, 0.5, 1.0, 2.5, 5.0, 10.0,]
+ DURATION_BUCKETS.to_vec()
)Also applies to: 84-89, 95-100, 101-106
| pub static ref OPERATION_COUNTER: CounterVec = register_counter_vec!( | ||
| "operations_total", | ||
| "Total number of operations processed", | ||
| &[ | ||
| "vendor", | ||
| "spawn_id", | ||
| "type", | ||
| "name", | ||
| "dataset", | ||
| "dataset_size" | ||
| ] | ||
| ) | ||
| .unwrap(); |
There was a problem hiding this comment.
Improve error handling for metric registration
Using .unwrap() on metric registration can cause panics at runtime. While metric registration typically only fails if a metric with the same name is already registered, it's better to handle these errors gracefully.
Replace all .unwrap() calls with .expect() and descriptive messages:
- .unwrap();
+ .expect("Failed to register operations_total counter");Consider implementing a custom metric registration function that handles errors consistently:
fn register_metric<T>(metric: Result<T, prometheus::Error>, name: &str) -> T {
metric.expect(&format!("Failed to register {} metric", name))
}Also applies to: 40-52, 53-57, 58-62, 63-67, 68-72, 73-77, 78-83, 84-89, 90-94, 95-100, 101-106, 107-111
| #[command(about = "load data into the database")] | ||
| Load { |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Consider adding size validation for the size parameter.
The size parameter in GenerateQueries command should be validated to ensure it's within reasonable limits.
#[arg(short, long, value_enum)]
-size: usize,
+#[arg(
+ short,
+ long,
+ value_parser = clap::value_parser!(usize).range(1..=100_000_000),
+ help = "number of queries to generate"
+)]
+size: usize,Also applies to: 45-47
| let timeout = Duration::from_secs(60); | ||
| let offset = msg.compute_offset_ms(); | ||
|
|
||
| FALKOR_MSG_DEADLINE_OFFSET_GAUGE.set(offset); | ||
| if offset > 0 { | ||
| // sleep offset millis | ||
| tokio::time::sleep(Duration::from_millis(offset as u64)).await; | ||
| } |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Consider adding a maximum offset limit.
The offset calculation should have an upper bound to prevent excessive delays.
let offset = msg.compute_offset_ms();
+ const MAX_OFFSET_MS: i64 = 5000; // 5 seconds
+ let offset = offset.min(MAX_OFFSET_MS);
FALKOR_MSG_DEADLINE_OFFSET_GAUGE.set(offset);
if offset > 0 {
tokio::time::sleep(Duration::from_millis(offset as u64)).await;
}Committable suggestion skipped: line range outside the PR's diff.
| "uid": "PBFA97CFB590B2093" | ||
| }, | ||
| "editorMode": "code", | ||
| "expr": "sum by (vendor) (operations_error_total{vendor=\"neo4j\"}) or vector(0)", |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Add rate() function for error metrics.
The error metric query doesn't use rate(), which might lead to misleading results over time.
Apply this change:
- "expr": "sum by (vendor) (operations_error_total{vendor=\"neo4j\"}) or vector(0)",
+ "expr": "sum by (vendor) (rate(operations_error_total{vendor=\"neo4j\"}[5m])) or vector(0)",📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| "expr": "sum by (vendor) (operations_error_total{vendor=\"neo4j\"}) or vector(0)", | |
| "expr": "sum by (vendor) (rate(operations_error_total{vendor=\"neo4j\"}[5m])) or vector(0)", |
| let seconds_wait = 3u64; | ||
| info!( | ||
| "worker {} failed to process query, not sleeping for {} seconds {:?}", | ||
| worker_id, seconds_wait, e | ||
| ); |
There was a problem hiding this comment.
Improve error handling in Neo4j worker.
The worker logs errors but doesn't implement any retry mechanism or proper error handling.
Consider implementing a retry mechanism:
Err(e) => {
NEO4J_ERROR_REQUESTS_DURATION_HISTOGRAM.observe(duration.as_secs_f64());
- let seconds_wait = 3u64;
- info!(
- "worker {} failed to process query, not sleeping for {} seconds {:?}",
- worker_id, seconds_wait, e
+ error!(
+ "Worker {} failed to process query: {:?}",
+ worker_id, e
);
+ if let Some(retries) = prepared_query.retries_remaining.as_mut() {
+ if *retries > 0 {
+ *retries -= 1;
+ tokio::time::sleep(Duration::from_secs(3)).await;
+ continue;
+ }
+ }
}Committable suggestion skipped: line range outside the PR's diff.
src/main.rs
Outdated
| async fn read_queries( | ||
| file_name: String | ||
| ) -> BenchmarkResult<(PrepareQueriesMetadata, Vec<PreparedQuery>)> { | ||
| let start = Instant::now(); | ||
| let file = File::open(file_name).await?; | ||
| let mut reader = BufReader::new(file); | ||
|
|
||
| // the first line is PrepareQueriesMetadata read it | ||
| let mut metadata_line = String::new(); | ||
| reader.read_line(&mut metadata_line).await?; | ||
|
|
||
| match serde_json::from_str::<PrepareQueriesMetadata>(&metadata_line) { | ||
| Ok(metadata) => { | ||
| let size = metadata.size; | ||
| let mut queries = Vec::with_capacity(size); | ||
| let mut lines = reader.lines(); | ||
|
|
||
| while let Some(line) = lines.next_line().await? { | ||
| let query: PreparedQuery = serde_json::from_str(&line)?; | ||
| queries.push(query); | ||
| } | ||
| let duration = start.elapsed(); | ||
| info!("Reading {} queries took {:?}", size, duration); | ||
| Ok((metadata, queries)) | ||
| } | ||
| Err(e) => Err(OtherError(format!("Error parsing metadata: {}", e))), |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Add proper error handling for file operations.
The read_queries function should handle file-related errors more gracefully.
Enhance error handling:
async fn read_queries(
file_name: String
) -> BenchmarkResult<(PrepareQueriesMetadata, Vec<PreparedQuery>)> {
let start = Instant::now();
- let file = File::open(file_name).await?;
+ let file = File::open(&file_name)
+ .await
+ .map_err(|e| OtherError(format!("Failed to open file {}: {}", file_name, e)))?;
let mut reader = BufReader::new(file);📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| async fn read_queries( | |
| file_name: String | |
| ) -> BenchmarkResult<(PrepareQueriesMetadata, Vec<PreparedQuery>)> { | |
| let start = Instant::now(); | |
| let file = File::open(file_name).await?; | |
| let mut reader = BufReader::new(file); | |
| // the first line is PrepareQueriesMetadata read it | |
| let mut metadata_line = String::new(); | |
| reader.read_line(&mut metadata_line).await?; | |
| match serde_json::from_str::<PrepareQueriesMetadata>(&metadata_line) { | |
| Ok(metadata) => { | |
| let size = metadata.size; | |
| let mut queries = Vec::with_capacity(size); | |
| let mut lines = reader.lines(); | |
| while let Some(line) = lines.next_line().await? { | |
| let query: PreparedQuery = serde_json::from_str(&line)?; | |
| queries.push(query); | |
| } | |
| let duration = start.elapsed(); | |
| info!("Reading {} queries took {:?}", size, duration); | |
| Ok((metadata, queries)) | |
| } | |
| Err(e) => Err(OtherError(format!("Error parsing metadata: {}", e))), | |
| async fn read_queries( | |
| file_name: String | |
| ) -> BenchmarkResult<(PrepareQueriesMetadata, Vec<PreparedQuery>)> { | |
| let start = Instant::now(); | |
| let file = File::open(&file_name) | |
| .await | |
| .map_err(|e| OtherError(format!("Failed to open file {}: {}", file_name, e)))?; | |
| let mut reader = BufReader::new(file); | |
| // the first line is PrepareQueriesMetadata read it | |
| let mut metadata_line = String::new(); | |
| reader.read_line(&mut metadata_line).await?; | |
| match serde_json::from_str::<PrepareQueriesMetadata>(&metadata_line) { | |
| Ok(metadata) => { | |
| let size = metadata.size; | |
| let mut queries = Vec::with_capacity(size); | |
| let mut lines = reader.lines(); | |
| while let Some(line) = lines.next_line().await? { | |
| let query: PreparedQuery = serde_json::from_str(&line)?; | |
| queries.push(query); | |
| } | |
| let duration = start.elapsed(); | |
| info!("Reading {} queries took {:?}", size, duration); | |
| Ok((metadata, queries)) | |
| } | |
| Err(e) => Err(OtherError(format!("Error parsing metadata: {}", e))), |
There was a problem hiding this comment.
Actionable comments posted: 0
♻️ Duplicate comments (3)
dashboards/falkor_dashboard.json (3)
93-93: 🛠️ Refactor suggestionImprove uptime metric calculation.
The current uptime calculation using
max_over_timewith$__intervalmight miss data points during server restarts.Apply this diff to improve reliability:
- "expr": "max(max_over_time(redis_uptime_in_seconds{instance=~\"redis-exporter:9121\"}[$__interval]))", + "expr": "time() - process_start_time_seconds{instance=~\"redis-exporter:9121\"}",
869-870: 🛠️ Refactor suggestionConsolidate duplicate queries/sec panels.
There are two nearly identical panels showing queries/sec metrics with slightly different grouping.
Merge these panels into a single, more comprehensive view:
- "expr": "sum by (vendor) (rate(operations_total{vendor=\"falkor\"}[1m]))", - "legendFormat": "executor {{spawn_id}}", + "expr": "sum by (vendor) (rate(operations_total{vendor=\"falkor\"}[1m]))", + "legendFormat": "Total", + "refId": "A" + }, + { + "expr": "sum by (vendor, spawn_id) (rate(operations_total{vendor=\"falkor\"}[1m]))", + "legendFormat": "Worker {{spawn_id}}",Also applies to: 962-963
477-478: 🛠️ Refactor suggestionEnhance latency metric visualization.
The current latency metric might not provide accurate percentiles.
Apply this diff for better latency tracking:
- "expr": "rate(redis_commands_latencies_usec_count[1m])", - "legendFormat": "{{ cmd }}", + "expr": "histogram_quantile(0.95, sum(rate(redis_commands_duration_seconds_bucket[5m])) by (le, cmd))", + "legendFormat": "p95 {{ cmd }}",
🧹 Nitpick comments (3)
dashboards/falkor_dashboard.json (1)
1-1714: Consider adding alerting rules for key metrics.The dashboard provides comprehensive monitoring but could benefit from predefined alerting rules for critical metrics like:
- High error rates
- Latency spikes
- Memory usage thresholds
- Connection limits
todo.md (2)
4-7: Fix markdown list indentationThe sub-tasks under "performance read/write vs. read" have incorrect indentation which affects readability.
Apply this diff to fix the indentation:
- [ ] performance read/write vs. read - - [x] read/write without increasing the graph size - - [x] set read/write cli - - [x] read using GRAPH.RO_QUERY - - [x] delete data when update + [ ] performance read/write vs. read + - [x] read/write without increasing the graph size + - [x] set read/write cli + - [x] read using GRAPH.RO_QUERY + - [x] delete data when update🧰 Tools
🪛 Markdownlint (0.37.0)
4-4: Expected: 2; Actual: 4
Unordered list indentation(MD007, ul-indent)
5-5: Expected: 2; Actual: 4
Unordered list indentation(MD007, ul-indent)
6-6: Expected: 2; Actual: 4
Unordered list indentation(MD007, ul-indent)
7-7: Expected: 2; Actual: 4
Unordered list indentation(MD007, ul-indent)
13-15: Consider adding more specificity to open-ended tasksThe following tasks would benefit from more detailed descriptions:
- "add more queries?" - Specify what types of queries and their purpose
- "vendors" - Clarify which vendors and what needs to be done
- "benchmark hardware settings ?" - Define specific hardware parameters to be tested
This will help track progress and ensure clear objectives.
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todo.md
4-4: Expected: 2; Actual: 4
Unordered list indentation
(MD007, ul-indent)
5-5: Expected: 2; Actual: 4
Unordered list indentation
(MD007, ul-indent)
6-6: Expected: 2; Actual: 4
Unordered list indentation
(MD007, ul-indent)
7-7: Expected: 2; Actual: 4
Unordered list indentation
(MD007, ul-indent)
🔇 Additional comments (2)
dashboards/falkor_dashboard.json (1)
1277-1378: LGTM! Well-structured database metrics panels.
The graph metrics panels (nodes and relationships) are well configured with appropriate counters and visualizations.
todo.md (1)
1-2:
Prioritize crash-related issues investigation
The presence of crash scenarios during timeout and read-write operations suggests critical stability issues that should be addressed with high priority. Consider adding more details about the crash conditions to help with reproduction and debugging.
Let's check for related crash reports or issues:
There was a problem hiding this comment.
Actionable comments posted: 0
🧹 Nitpick comments (4)
dashboards/falkor_dashboard.json (4)
1-21: Consider enhancing dashboard configuration for better usability.The dashboard configuration could benefit from the following improvements:
- Add template variables for instance selection to make the dashboard reusable across different environments
- Consider increasing the default time range from 5 minutes to a longer duration for better trend visibility
- Add description field to provide context about the dashboard's purpose and usage
"templating": { "list": [] }, + "description": "Dashboard for monitoring FalkorDB performance, resource usage, and operational metrics", "time": { - "from": "now-5m", + "from": "now-1h", "to": "now" }, + "templating": { + "list": [ + { + "name": "instance", + "type": "query", + "datasource": "PBFA97CFB590B2093", + "query": "label_values(redis_up, instance)", + "refresh": 2, + "includeAll": true, + "current": { + "selected": true, + "text": "All", + "value": "$__all" + } + } + ] + }Also applies to: 1694-1714
568-575: Add memory usage prediction.The memory usage panel could benefit from adding a prediction line to help with capacity planning.
"targets": [ { "editorMode": "code", "expr": "redis_memory_used_bytes{instance=~\"redis-exporter:9121\"} ", "legendFormat": "redis_memory_used_bytes", "range": true, "refId": "A" - } + }, + { + "editorMode": "code", + "expr": "predict_linear(redis_memory_used_bytes{instance=~\"redis-exporter:9121\"}[1h], 24 * 3600)", + "legendFormat": "24h prediction", + "range": true, + "refId": "B" + } ]
1464-1476: Enhance error tracking with categorization.The current error tracking only shows total errors. Consider adding error categorization to better understand the types of errors occurring.
"targets": [ { "editorMode": "code", - "expr": "sum by (vendor) (operations_error_total{vendor=\"falkor\"}) or vector(0)", - "legendFormat": "all errors", + "expr": "sum by (vendor, error_type) (operations_error_total{vendor=\"falkor\"}) or vector(0)", + "legendFormat": "{{error_type}}", "range": true, "refId": "B" } ]
1278-1285: Add growth rate metrics for graph statistics.The nodes and relationships panels only show absolute numbers. Adding growth rate metrics would help track the graph's evolution over time.
"targets": [ { "editorMode": "code", "expr": "falkordb_nodes_total", "legendFormat": "nodes number", "range": true, "refId": "A" - } + }, + { + "editorMode": "code", + "expr": "rate(falkordb_nodes_total[5m])", + "legendFormat": "nodes growth rate", + "range": true, + "refId": "B" + } ]Apply similar changes to the relationships panel.
Also applies to: 1371-1378
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🔇 Additional comments (3)
dashboards/falkor_dashboard.json (3)
91-97: Improve uptime metric calculation.
The current uptime calculation using max_over_time with $__interval might miss data points or provide inaccurate results.
869-870: Consolidate duplicate queries/sec panels.
The dashboard contains two nearly identical panels showing queries/sec metrics with slightly different visualizations.
Also applies to: 962-963
476-481: Enhance latency metric visualization.
The current latency metric might not provide accurate percentiles.
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Actionable comments posted: 2
♻️ Duplicate comments (1)
docker-compose.yml (1)
25-38:⚠️ Potential issueCritical security concerns in Grafana configuration remain unaddressed
The previous review comments about security risks are still valid:
- Anonymous admin access is a significant security risk
- Using
latesttag could lead to unexpected updates- Bind mounts should be replaced with named volumes
🧹 Nitpick comments (1)
docker-compose.yml (1)
1-41: Consider using a dedicated Docker network for service isolationInstead of using host network mode, create a dedicated Docker network for these services. This provides better:
- Service isolation and security
- Internal service discovery
- Network access control
Add this at the top level of your docker-compose.yml:
+networks: + monitoring: + driver: bridge🧰 Tools
🪛 yamllint (1.35.1)
[error] 18-18: trailing spaces
(trailing-spaces)
[error] 41-41: no new line character at the end of file
(new-line-at-end-of-file)
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🪛 yamllint (1.35.1)
docker-compose.yml
[error] 18-18: trailing spaces
(trailing-spaces)
[error] 41-41: no new line character at the end of file
(new-line-at-end-of-file)
🔇 Additional comments (1)
docker-compose.yml (1)
40-41: Incomplete volumes configuration
The volumes section needs additional named volumes as previously suggested.
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[error] 41-41: no new line character at the end of file
(new-line-at-end-of-file)
docker-compose.yml
Outdated
| redis-exporter: | ||
| image: oliver006/redis_exporter:latest | ||
| command: | ||
| # - '--redis.addr=host.docker.internal:6379' | ||
| - '--redis.addr=127.0.0.1:6379' | ||
| ports: | ||
| - 9121:9121 | ||
| #extra_hosts: | ||
| # - "host.docker.internal:host-gateway" | ||
| network_mode: host |
There was a problem hiding this comment.
Clean up Redis Exporter configuration and address security concerns
Issues to address:
- Using
latesttag - Host network mode exposes all ports
- Trailing spaces in command
- Commented out configuration should be removed
Apply this diff to improve the configuration:
redis-exporter:
- image: oliver006/redis_exporter:latest
+ image: oliver006/redis_exporter:v1.55.0
- command:
- # - '--redis.addr=host.docker.internal:6379'
- - '--redis.addr=127.0.0.1:6379'
+ command: ['--redis.addr=127.0.0.1:6379']
ports:
- 9121:9121
- #extra_hosts:
- # - "host.docker.internal:host-gateway"
- network_mode: host
+ networks:
+ - monitoring📝 Committable suggestion
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| redis-exporter: | |
| image: oliver006/redis_exporter:latest | |
| command: | |
| # - '--redis.addr=host.docker.internal:6379' | |
| - '--redis.addr=127.0.0.1:6379' | |
| ports: | |
| - 9121:9121 | |
| #extra_hosts: | |
| # - "host.docker.internal:host-gateway" | |
| network_mode: host | |
| redis-exporter: | |
| image: oliver006/redis_exporter:v1.55.0 | |
| command: ['--redis.addr=127.0.0.1:6379'] | |
| ports: | |
| - 9121:9121 | |
| networks: | |
| - monitoring |
🧰 Tools
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[error] 18-18: trailing spaces
(trailing-spaces)
docker-compose.yml
Outdated
| prometheus: | ||
| image: prom/prometheus:latest | ||
| # extra_hosts: | ||
| # - "host.docker.internal:host-gateway" | ||
| network_mode: host | ||
| ports: | ||
| - 9090:9090 | ||
| volumes: | ||
| - ./prometheus.yml:/etc/prometheus/prometheus.yml | ||
| command: | ||
| - '--config.file=/etc/prometheus/prometheus.yml' |
There was a problem hiding this comment.
Security and configuration concerns in Prometheus setup
Several critical issues need attention:
- Using
latesttag can lead to unexpected updates - Host network mode exposes all container ports directly to the host
- Port mapping is redundant when using host network mode
- Configuration file as bind mount may cause maintainability issues
Apply this diff to improve the configuration:
prometheus:
- image: prom/prometheus:latest
+ image: prom/prometheus:v2.48.1
- network_mode: host
+ networks:
+ - monitoring
ports:
- 9090:9090
volumes:
- - ./prometheus.yml:/etc/prometheus/prometheus.yml
+ - prometheus_config:/etc/prometheus/
+ - prometheus_data:/prometheus
command:
- '--config.file=/etc/prometheus/prometheus.yml'Committable suggestion skipped: line range outside the PR's diff.
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Actionable comments posted: 7
🧹 Nitpick comments (3)
readme.md (1)
101-140: Improve CLI examples documentationConsider enhancing the CLI documentation:
- Add example output for each command
- Explain the significance of parameters (e.g.,
-p40,--mps 4000)- Include common usage scenarios
- Document error cases and troubleshooting
generate_docker_compose.sh (2)
145-150: Enhance error handling and success verification.Add verification of file creation and more informative messages.
else - echo "Unsupported OS" + echo "Error: Unsupported operating system: $OS" exit 1 fi -echo "Docker Compose files generated successfully." +# Verify file creation +for file in "docker-compose.yml" "prometheus.yml" "grafana-datasources.yml"; do + if [[ ! -f "$file" ]]; then + echo "Error: Failed to generate $file" + exit 1 + fi +done + +echo "Successfully generated Docker Compose configuration files:" +echo "- docker-compose.yml" +echo "- prometheus.yml" +echo "- grafana-datasources.yml" +echo "Run 'docker-compose up -d' to start the monitoring stack"
1-2: Add prerequisites check and documentation.The script would benefit from additional features to improve usability and maintainability:
- Add prerequisites validation:
# Add at the beginning of the script prerequisites() { local missing_deps=() for cmd in docker docker-compose curl jq; do if ! command -v "$cmd" >/dev/null 2>&1; then missing_deps+=("$cmd") fi done if [[ ${#missing_deps[@]} -gt 0 ]]; then echo "Error: Missing required dependencies: ${missing_deps[*]}" exit 1 fi } prerequisites
- Add cleanup functionality:
cleanup() { local files=("docker-compose.yml" "prometheus.yml" "grafana-datasources.yml") for file in "${files[@]}"; do [[ -f "$file" ]] && rm "$file" done } # Add trap for cleanup on script failure trap cleanup ERR
- Add script documentation:
#!/bin/bash # # Setup script for FalkorDB monitoring infrastructure # # Prerequisites: # - Docker # - Docker Compose # - curl # - jq # # Environment variables: # PROMETHEUS_PORT - Prometheus port (default: 9090) # REDIS_EXPORTER_PORT - Redis Exporter port (default: 9121) # GRAFANA_PORT - Grafana port (default: 3000) # GRAFANA_DISABLE_AUTH - Disable Grafana auth (default: false)
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🪛 Markdownlint (0.37.0)
readme.md
216-216: Expected: atx; Actual: setext
Heading style
(MD003, heading-style)
144-144: null
Bare URL used
(MD034, no-bare-urls)
145-145: null
Bare URL used
(MD034, no-bare-urls)
197-197: null
Bare URL used
(MD034, no-bare-urls)
198-198: null
Bare URL used
(MD034, no-bare-urls)
🔇 Additional comments (3)
readme.md (3)
12-14: Verify benchmark methodology for performance claims
The performance claims are significant (10.5x to 344.5x faster). Consider adding:
- Benchmark methodology details
- Hardware specifications used
- Configuration parameters for both databases
- Test dataset characteristics
This will help users reproduce and validate the results.
197-198: Format URLs as proper markdown links
Previous review comment still applies. URLs should be formatted as proper markdown links.
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🪛 Markdownlint (0.37.0)
197-197: null
Bare URL used
(MD034, no-bare-urls)
198-198: null
Bare URL used
(MD034, no-bare-urls)
199-216: Enhance the Prometheus queries documentation
Previous review comment about organizing and documenting Prometheus queries still applies. The metrics list needs better structure and context.
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216-216: Expected: atx; Actual: setext
Heading style
(MD003, heading-style)
| ##### Generate the docker compose for prometheus and grafana | ||
|
|
||
| ```bash | ||
| ./generate_docker_compose.sh | ||
| ``` | ||
|
|
||
| ##### Run the docker compose | ||
|
|
||
| ```bash | ||
| docker-compose up | ||
| ``` |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Enhance docker-compose setup instructions
The docker-compose setup instructions should include:
- Prerequisites (Docker and Docker Compose versions)
- Expected directory structure
- Configuration options
- Verification steps after startup
| - redis_memory_used_peak_bytes | ||
| - redis_memory_used_vm_total | ||
| - redis_process_id | ||
| ======= |
There was a problem hiding this comment.
Remove merge conflict marker
The ======= at the end of the file appears to be an unresolved merge conflict marker and should be removed.
| global: | ||
| scrape_interval: 5s | ||
| scrape_timeout: 500ms | ||
|
|
There was a problem hiding this comment.
🛠️ Refactor suggestion
Review Prometheus configuration parameters.
The current scrape settings might be too aggressive and there's no data retention configuration.
global:
- scrape_interval: 5s
- scrape_timeout: 500ms
+ scrape_interval: ${PROMETHEUS_SCRAPE_INTERVAL:-15s}
+ scrape_timeout: ${PROMETHEUS_SCRAPE_TIMEOUT:-10s}
+ evaluation_interval: ${PROMETHEUS_EVAL_INTERVAL:-15s}
+
+storage:
+ tsdb:
+ retention.time: ${PROMETHEUS_RETENTION:-15d}
+ retention.size: ${PROMETHEUS_RETENTION_SIZE:-5GB}Also applies to: 119-122
| # Determine the operating system | ||
| OS="$(uname)" |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Add error handling for OS detection.
The OS detection logic should handle potential failures and use proper shell variable quoting.
-OS="$(uname)"
+if ! OS="$(uname)"; then
+ echo "Failed to detect operating system"
+ exit 1
+fi📝 Committable suggestion
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Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| # Determine the operating system | |
| OS="$(uname)" | |
| # Determine the operating system | |
| if ! OS="$(uname)"; then | |
| echo "Failed to detect operating system" | |
| exit 1 | |
| fi |
| environment: | ||
| - GF_AUTH_DISABLE_LOGIN_FORM=true | ||
| - GF_AUTH_ANONYMOUS_ENABLED=true | ||
| - GF_AUTH_ANONYMOUS_ORG_ROLE=Admin |
There was a problem hiding this comment.
Review Grafana authentication settings.
The current configuration disables Grafana authentication completely. Consider making this configurable based on the environment.
environment:
- - GF_AUTH_DISABLE_LOGIN_FORM=true
- - GF_AUTH_ANONYMOUS_ENABLED=true
- - GF_AUTH_ANONYMOUS_ORG_ROLE=Admin
+ - GF_AUTH_DISABLE_LOGIN_FORM=${GRAFANA_DISABLE_AUTH:-false}
+ - GF_AUTH_ANONYMOUS_ENABLED=${GRAFANA_ANONYMOUS_AUTH:-false}
+ - GF_AUTH_ANONYMOUS_ORG_ROLE=${GRAFANA_ANONYMOUS_ROLE:-Viewer}📝 Committable suggestion
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Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| environment: | |
| - GF_AUTH_DISABLE_LOGIN_FORM=true | |
| - GF_AUTH_ANONYMOUS_ENABLED=true | |
| - GF_AUTH_ANONYMOUS_ORG_ROLE=Admin | |
| environment: | |
| - GF_AUTH_DISABLE_LOGIN_FORM=${GRAFANA_DISABLE_AUTH:-false} | |
| - GF_AUTH_ANONYMOUS_ENABLED=${GRAFANA_ANONYMOUS_AUTH:-false} | |
| - GF_AUTH_ANONYMOUS_ORG_ROLE=${GRAFANA_ANONYMOUS_ROLE:-Viewer} |
|
|
||
| elif [[ "$OS" == "Linux" ]]; then | ||
| # Linux configuration | ||
| HOST_IP=$(hostname -I | awk '{print $1}') # Get the host IP address |
There was a problem hiding this comment.
Improve IP address detection reliability.
The current IP detection method might be unreliable in certain network configurations.
- HOST_IP=$(hostname -I | awk '{print $1}') # Get the host IP address
+ if ! HOST_IP=$(ip route get 1 | awk '{print $(NF-2);exit}'); then
+ echo "Failed to detect host IP address"
+ exit 1
+ fi
+ if [[ -z "${HOST_IP}" ]]; then
+ echo "No valid IP address detected"
+ exit 1
+ fi📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| HOST_IP=$(hostname -I | awk '{print $1}') # Get the host IP address | |
| if ! HOST_IP=$(ip route get 1 | awk '{print $(NF-2);exit}'); then | |
| echo "Failed to detect host IP address" | |
| exit 1 | |
| fi | |
| if [[ -z "${HOST_IP}" ]]; then | |
| echo "No valid IP address detected" | |
| exit 1 | |
| fi |
| cat <<EOF > docker-compose.yml | ||
| services: | ||
| prometheus: | ||
| image: prom/prometheus:latest | ||
| extra_hosts: | ||
| - "host.docker.internal:host-gateway" | ||
| ports: | ||
| - 9090:9090 | ||
| volumes: | ||
| - ./prometheus.yml:/etc/prometheus/prometheus.yml | ||
| command: | ||
| - '--config.file=/etc/prometheus/prometheus.yml' | ||
|
|
||
| redis-exporter: | ||
| image: oliver006/redis_exporter:latest | ||
| command: | ||
| - '--redis.addr=host.docker.internal:6379' | ||
| ports: | ||
| - 9121:9121 | ||
| extra_hosts: | ||
| - "host.docker.internal:host-gateway" | ||
|
|
||
| grafana: | ||
| image: grafana/grafana:latest | ||
| ports: | ||
| - 3000:3000 | ||
| environment: | ||
| - GF_AUTH_DISABLE_LOGIN_FORM=true | ||
| - GF_AUTH_ANONYMOUS_ENABLED=true | ||
| - GF_AUTH_ANONYMOUS_ORG_ROLE=Admin | ||
| - GF_DASHBOARDS_JSON_ENABLED=true | ||
| volumes: | ||
| - ./grafana-datasources.yml:/etc/grafana/provisioning/datasources/datasources.yml | ||
| - ./dashboards:/var/lib/grafana/dashboards | ||
| - ./provisioning:/etc/grafana/provisioning | ||
|
|
||
| volumes: | ||
| prometheus_data: | ||
| EOF |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Add configuration flexibility and security measures.
Several improvements can enhance the security and maintainability of the Docker Compose configuration:
- Use environment variables for ports:
+# At the top of the script
+PROMETHEUS_PORT="${PROMETHEUS_PORT:-9090}"
+REDIS_EXPORTER_PORT="${REDIS_EXPORTER_PORT:-9121}"
+GRAFANA_PORT="${GRAFANA_PORT:-3000}"
services:
prometheus:
ports:
- - 9090:9090
+ - ${PROMETHEUS_PORT}:9090- Add version and health checks:
+version: '3.8'
services:
prometheus:
image: prom/prometheus:latest
+ healthcheck:
+ test: ["CMD", "wget", "--spider", "http://localhost:9090/-/healthy"]
+ interval: 10s
+ timeout: 5s
+ retries: 3Committable suggestion skipped: line range outside the PR's diff.
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Actionable comments posted: 5
♻️ Duplicate comments (3)
src/prometheus_endpoint.rs (3)
50-59:⚠️ Potential issueEnsure graceful shutdown of the server.
The current
Dropimplementation doesn't properly await the server task completion, which might lead to improper shutdown.
66-66:⚠️ Potential issueHandle potential errors from encoder.encode instead of using unwrap().
Using
unwrap()on the encoder can cause panics if encoding fails.
68-71:⚠️ Potential issueHandle potential errors when building the HTTP response.
Using
unwrap()when constructing the HTTP response can lead to panics.
🧹 Nitpick comments (4)
src/prometheus_endpoint.rs (2)
15-19: Consider makingnew()public for consistency with Default.The
Defaultimplementation is public but calls a privatenew()method. This creates an inconsistent API where users can create instances viaDefault::default()but not vianew().- fn new() -> Self { + pub fn new() -> Self {
10-13: Consider adding configuration options for metrics collection.The current implementation could benefit from configuration options such as:
- Custom metric prefixes
- Configurable metric collection intervals
- Selective metric enabling/disabling
- Custom labels support
This would improve the flexibility and reusability of the metrics endpoint.
generate_docker_compose.sh (2)
155-158: Improve error handling message.The error message could be more informative by including the detected OS.
else - echo "Unsupported OS" + echo "Error: Unsupported operating system: $OS" + echo "This script only supports macOS (Darwin) and Linux." exit 1 fi
1-160: Consider adding configuration flexibility and documentation.
- Add a configuration file or environment variables for customizable settings:
- Ports
- Retention periods
- Authentication settings
- Resource limits
- Add documentation:
- Prerequisites
- Usage instructions
- Configuration options
- Troubleshooting guide
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🔇 Additional comments (5)
src/prometheus_endpoint.rs (1)
1-13: LGTM! Well-structured imports and struct definition.
The imports are comprehensive and the struct design with optional fields enables proper resource management.
generate_docker_compose.sh (4)
3-4: Add error handling for OS detection.
The OS detection logic should handle potential failures and use proper shell variable quoting.
36-38: Review Grafana authentication settings.
The current configuration disables Grafana authentication completely. Consider making this configurable based on the environment.
50-53: Review Prometheus configuration parameters.
The current scrape settings might be too aggressive and there's no data retention configuration.
78-78: Improve IP address detection reliability.
The current IP detection method might be unreliable in certain network configurations.
| if let Err(e) = graceful.await { | ||
| error!("server error: {}", e); | ||
| } | ||
| }); |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Improve error handling for server errors.
The current implementation only logs server errors. Consider implementing a more robust error handling strategy, such as propagating the error or implementing a retry mechanism.
if let Err(e) = graceful.await {
- error!("server error: {}", e);
+ error!("Prometheus metrics server error: {}", e);
+ // Optionally implement retry logic here
+ return;
}Committable suggestion skipped: line range outside the PR's diff.
| let (shutdown_tx, shutdown_rx) = tokio::sync::oneshot::channel::<()>(); | ||
|
|
||
| let server_thread = task::spawn(async { | ||
| let addr = SocketAddr::from(([0, 0, 0, 0], 8080)); |
There was a problem hiding this comment.
Security consideration: Server binds to all interfaces.
Binding to 0.0.0.0 makes the metrics endpoint accessible from any network interface. Consider restricting this to localhost (127.0.0.1) unless external access is specifically required.
- let addr = SocketAddr::from(([0, 0, 0, 0], 8080));
+ let addr = SocketAddr::from(([127, 0, 0, 1], 8080));📝 Committable suggestion
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Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| let addr = SocketAddr::from(([0, 0, 0, 0], 8080)); | |
| let addr = SocketAddr::from(([127, 0, 0, 1], 8080)); |
| exit 1 | ||
| fi | ||
|
|
||
| echo "Docker Compose files generated successfully." |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Add verification of generated files.
Add checks to verify that all required files were generated successfully.
+# Verify generated files
+required_files=("docker-compose.yml" "prometheus.yml" "grafana-datasources.yml")
+for file in "${required_files[@]}"; do
+ if [[ ! -f "$file" ]]; then
+ echo "Error: Failed to generate $file"
+ exit 1
+ fi
+done
+
echo "Docker Compose files generated successfully."📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| echo "Docker Compose files generated successfully." | |
| # Verify generated files | |
| required_files=("docker-compose.yml" "prometheus.yml" "grafana-datasources.yml") | |
| for file in "${required_files[@]}"; do | |
| if [[ ! -f "$file" ]]; then | |
| echo "Error: Failed to generate $file" | |
| exit 1 | |
| fi | |
| done | |
| echo "Docker Compose files generated successfully." |
| node-exporter: | ||
| image: prom/node-exporter:latest | ||
| ports: | ||
| - 9100:9100 | ||
|
|
There was a problem hiding this comment.
🛠️ Refactor suggestion
Review node-exporter configuration.
The node-exporter service lacks:
- Resource limits
- Security configurations
- Host volume mounts for system metrics
node-exporter:
image: prom/node-exporter:latest
+ user: root
+ privileged: true
ports:
- 9100:9100
+ volumes:
+ - /proc:/host/proc:ro
+ - /sys:/host/sys:ro
+ - /:/rootfs:ro
+ command:
+ - '--path.procfs=/host/proc'
+ - '--path.sysfs=/host/sys'
+ - '--path.rootfs=/rootfs'
+ deploy:
+ resources:
+ limits:
+ memory: 128M📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| node-exporter: | |
| image: prom/node-exporter:latest | |
| ports: | |
| - 9100:9100 | |
| node-exporter: | |
| image: prom/node-exporter:latest | |
| user: root | |
| privileged: true | |
| ports: | |
| - 9100:9100 | |
| volumes: | |
| - /proc:/host/proc:ro | |
| - /sys:/host/sys:ro | |
| - /:/rootfs:ro | |
| command: | |
| - '--path.procfs=/host/proc' | |
| - '--path.sysfs=/host/sys' | |
| - '--path.rootfs=/rootfs' | |
| deploy: | |
| resources: | |
| limits: | |
| memory: 128M |
| volumes: | ||
| - ./prometheus.yml:/etc/prometheus/prometheus.yml |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Add volume configuration for Prometheus data persistence.
The Prometheus volume is declared but not used in the service configuration. Add the volume mount to persist Prometheus data:
volumes:
- ./prometheus.yml:/etc/prometheus/prometheus.yml
+ - prometheus_data:/prometheusCommittable suggestion skipped: line range outside the PR's diff.
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Actionable comments posted: 0
♻️ Duplicate comments (4)
src/lib.rs (2)
24-24: 🛠️ Refactor suggestionConsider making REDIS_DATA_DIR configurable via environment variable.
Using a hardcoded relative path could cause issues in different deployment environments.
Apply this diff:
-pub(crate) const REDIS_DATA_DIR: &str = "./redis-data"; +pub(crate) const REDIS_DATA_DIR: &str = option_env!("REDIS_DATA_DIR").unwrap_or("./redis-data");
26-125: 🛠️ Refactor suggestionImprove error handling and reduce duplication in metric definitions.
- Replace unwrap() with expect() for better error messages during metric registration
- Extract common histogram bucket values to avoid duplication
Apply these improvements:
- Create a constant for histogram buckets:
+const DURATION_BUCKETS: &[f64] = &[ + 0.0005, 0.001, 0.005, 0.01, 0.025, + 0.05, 0.1, 0.25, 0.5, 1.0, 2.5, 5.0, 10.0 +];
- Use expect() with descriptive messages:
- .unwrap(); + .expect("Failed to register operations_total counter");
- Update histogram definitions to use the constant:
"falkordb_response_time_success_histogram", "Response time histogram of the successful requests", - vec![0.0005, 0.001, 0.005, 0.01, 0.025, 0.05, 0.1, 0.25, 0.5, 1.0, 2.5, 5.0, 10.0,] + DURATION_BUCKETS.to_vec()dashboards/falkor_dashboard.json (2)
1097-1282: 🛠️ Refactor suggestionConsolidate duplicate queries/sec panels.
Panels 4 and 5 (lines 1097-1282) show the same queries/sec metrics with slightly different visualizations.
Merge these panels into a single, more comprehensive view:
- "expr": "sum by (vendor) (rate(operations_total{vendor=\"falkor\"}[1m]))", - "legendFormat": "executor {{spawn_id}}", + "expr": "sum by (vendor) (rate(operations_total{vendor=\"falkor\"}[1m]))", + "legendFormat": "Total", + "refId": "A" + }, + { + "expr": "sum by (vendor, spawn_id) (rate(operations_total{vendor=\"falkor\"}[1m]))", + "legendFormat": "Worker {{spawn_id}}",
787-793: 🛠️ Refactor suggestionEnhance latency metric visualization.
The current latency metric might not provide accurate percentiles.
- "expr": "rate(redis_commands_latencies_usec_count[1m])", - "legendFormat": "{{ cmd }}", + "expr": "histogram_quantile(0.95, sum(rate(redis_commands_duration_seconds_bucket[5m])) by (le, cmd))", + "legendFormat": "p95 {{ cmd }}",
🧹 Nitpick comments (5)
src/falkor/falkor_process.rs (5)
21-30: Use#[derive(Debug)]or define a custom debug for improved traceability.Including a Debug implementation for the struct can help in logging or diagnosing issues, especially with asynchronous processes that rely heavily on runtime inspection.
63-74: Consider dynamic backoff or retries for monitoring processes.
When the monitored Redis process fails to start or exits unexpectedly, it might be useful to introduce an exponential backoff or retries in ProcessMonitor. Relying solely on a short initial delay may not be enough for more unpredictable environments, and you could end up re-spawning processes too quickly.
75-79: Consolidate task management or labeling for better observability.
Collecting references to all spawned tasks (e.g., “prometheus_metrics_reporter” and “ping_server”) under descriptive names or a structured “TaskManager” can improve maintainability. It also makes it easier to track, cancel, or debug tasks.
180-212: Gracefully handle potential Redis unavailability.
“report_metrics” presumes Redis is available locally. If the Redis process is killed or unreachable, you might encounter repeated errors. Consider adding a recovery or a backoff approach for better resilience.
282-299: Add more robust handling of partial query results.
If “execute_i64_query” returns complex or unexpected data, partial or invalid responses could go undetected. Consider more detailed error contexts or logging to facilitate debugging.
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🔇 Additional comments (7)
src/falkor/falkor_process.rs (3)
34-38: Verify error handling for non-existent files.
When calling redis_shutdown() and delete_file(), ensure such scenarios won’t fail due to missing targets. It's typically fine for these calls to be idempotent, but confirming graceful handling of missing files or inactive instances is best.
111-132: Avoid blocking in the Drop implementation.
Blocking in a destructor can lead to deadlocks or runtime panics in asynchronous runtimes. Consider removing this Drop implementation and requiring explicit invocation of “terminate()”.
214-240: Account for multi-core CPU usage in high-load scenarios.
You divide global CPU usage by the number of logical cores, but usage can exceed 100% if processes heavily utilize multiple cores. Carefully confirm this logic for multi-threaded workloads.
src/lib.rs (2)
1-23: LGTM! Well-organized imports and module structure.
The imports and module declarations are clean and well-structured, with appropriate use of lazy_static for prometheus metrics.
1-126: Excellent metric coverage for comprehensive monitoring.
The metrics provide thorough coverage of:
- System resources (CPU, memory)
- Application performance (latency, throughput)
- Error tracking and debugging
- Graph database statistics
dashboards/falkor_dashboard.json (2)
1-23: LGTM! Well-configured dashboard setup.
The dashboard configuration follows Grafana best practices with appropriate metadata and annotation setup.
2006-2026: LGTM! Appropriate dashboard settings.
The dashboard settings are well-configured with:
- Automatic refresh
- Reasonable time window
- Browser timezone
- Relevant tags
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Actionable comments posted: 0
♻️ Duplicate comments (2)
src/main.rs (2)
284-286:⚠️ Potential issueImprove error handling for Falkor worker tasks.
Similar to Neo4j workers, Falkor worker task errors are silently ignored.
Apply the same error handling improvement as suggested for Neo4j workers.
334-342: 🛠️ Refactor suggestionEnhance Falkor worker error handling with retry mechanism.
Similar to Neo4j worker, the error handling needs improvement with retries.
Apply the same retry mechanism improvement as suggested for Neo4j worker.
🧹 Nitpick comments (5)
src/prometheus_metrics.rs (2)
8-16: Consider making the reporting interval configurable
Currently, the metrics are reported every 5 seconds (line 27). In many production scenarios, making this interval configurable can improve flexibility and prevent excessive resource usage.
17-38: Graceful handling of repeated metric failures
Inside the loop, if the measure function fails, the error is logged but the loop continues. This is good for resilience. However, if the problem persists, you might want to include a backoff strategy or an error counter to avoid overwhelming logs.src/neo4j.rs (1)
25-27: Public fields for metrics handle
Exposing metric handles (lines 25–27) is fine internally, but consider restricting them behind methods if you need more control or if you plan to swap out the metrics reporter.src/main.rs (1)
569-570: Improve error handling for file operations.File operations should have more specific error handling.
Apply this diff:
- let file = File::open(file_name).await?; + let file = File::open(&file_name) + .await + .map_err(|e| OtherError(format!("Failed to open file {}: {}", file_name, e)))?;dashboards/neo4j_dashboard.json (1)
525-525: Fix typo in panel title.The panel title contains a typo: "unuccessful" should be "unsuccessful".
Apply this diff:
- "title": "unuccessful queries", + "title": "unsuccessful queries",
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dashboards/neo4j_dashboard.json(1 hunks)src/falkor/falkor_process.rs(1 hunks)src/lib.rs(1 hunks)src/main.rs(8 hunks)src/neo4j.rs(9 hunks)src/prometheus_metrics.rs(1 hunks)
🔇 Additional comments (11)
src/falkor/falkor_process.rs (3)
91-111: Terminate method looks correct
The sequence of dropping sender channels before awaiting joins ensures a tidy shutdown. This pattern generally avoids hanging tasks.
113-133: Potential risk of deadlock by blocking in Drop
This repeats a concern from a past review about blocking in destructors. Spawning the async task and immediately blocking (via futures::executor::block_on) can lead to deadlocks in async contexts or cause runtime panics.
157-189: Validate array bounds more defensively
In redis_to_query_info (lines 232-247), you assume at least 4 elements. Though you do check for some minimal length, be sure future changes won’t break this assumption. A fallback or more descriptive error handling can help.
src/lib.rs (1)
25-137: 🛠️ Refactor suggestion
Avoid using .unwrap() on metric registrations
Using .unwrap() on lines 40, 53, 58, 63, 68, 73, 78, 84, 90, 95, 101, 107, 112, 114, 116, 121, 126, 131, and 136 may cause runtime panics. Prefer a more descriptive error approach (e.g., .expect("Failed to register …")) or graceful error handling for reliability.
Example fix for lines 39–40:
)
-.unwrap();
+.expect("Failed to register operations_total counter");Likely invalid or redundant comment.
src/neo4j.rs (2)
Line range hint 161-194: Start method correctness
Using sleep loops until the DB is ready ensures stability. Good approach to avoid race conditions. If startup time can sometimes exceed these loops, consider a maximum retry or more adaptive logic.
241-265: CPU usage calculation may underrepresent values
Dividing the output of global_cpu_usage() or process.cpu_usage() by the number of logical CPUs might produce underreported metrics on some platforms. Verify if this logic aligns with your performance monitoring goals.
src/main.rs (4)
50-50:
Add error handling for Prometheus endpoint initialization.
The Prometheus endpoint initialization should handle potential errors (e.g., port already in use).
Apply this diff:
-let prometheus_endpoint = benchmark::prometheus_endpoint::PrometheusEndpoint::default();
+let prometheus_endpoint = benchmark::prometheus_endpoint::PrometheusEndpoint::default()
+ .map_err(|e| OtherError(format!("Failed to initialize Prometheus endpoint: {}", e)))?;Likely invalid or redundant comment.
154-156:
Improve error handling for worker tasks.
Worker task errors are silently ignored, which could mask important failures.
Apply this diff:
- for handle in workers_handles {
- let _ = handle.await;
- }
+ let mut errors = Vec::new();
+ for handle in workers_handles {
+ if let Err(e) = handle.await {
+ error!("Worker task failed: {:?}", e);
+ errors.push(e);
+ }
+ }
+ if !errors.is_empty() {
+ return Err(OtherError(format!("{} workers failed", errors.len())));
+ }Likely invalid or redundant comment.
205-212: 🛠️ Refactor suggestion
Enhance error handling with retry mechanism.
The current error handling only logs errors without any retry mechanism, which could lead to unnecessary failures.
Apply this diff:
Err(e) => {
NEO4J_ERROR_REQUESTS_DURATION_HISTOGRAM.observe(duration.as_secs_f64());
- let seconds_wait = 3u64;
- info!(
- "worker {} failed to process query, not sleeping for {} seconds {:?}",
- worker_id, seconds_wait, e
+ error!(
+ "Worker {} failed to process query: {:?}",
+ worker_id, e
);
+ // Implement exponential backoff retry
+ let retry_delay = Duration::from_secs(3);
+ tokio::time::sleep(retry_delay).await;
+ continue;
}Likely invalid or redundant comment.
543-544: 🛠️ Refactor suggestion
Avoid hardcoding repository parameters.
The values 9998 and 121716 should be configurable parameters.
Apply this diff:
+const DEFAULT_NODE_COUNT: u64 = 9998;
+const DEFAULT_RELATION_COUNT: u64 = 121716;
+
let queries_repository =
- benchmark::queries_repository::UsersQueriesRepository::new(9998, 121716);
+ benchmark::queries_repository::UsersQueriesRepository::new(
+ std::env::var("NODE_COUNT")
+ .ok()
+ .and_then(|v| v.parse().ok())
+ .unwrap_or(DEFAULT_NODE_COUNT),
+ std::env::var("RELATION_COUNT")
+ .ok()
+ .and_then(|v| v.parse().ok())
+ .unwrap_or(DEFAULT_RELATION_COUNT),
+ );Likely invalid or redundant comment.
dashboards/neo4j_dashboard.json (1)
331-331: 🛠️ Refactor suggestion
Add rate() function for error metrics.
The error metric query doesn't use rate(), which might lead to misleading results over time.
Apply this diff:
- "expr": "sum by (vendor) (operations_error_total{vendor=\"neo4j\"}) or vector(0)",
+ "expr": "sum by (vendor) (rate(operations_error_total{vendor=\"neo4j\"}[5m])) or vector(0)",Likely invalid or redundant comment.
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Actionable comments posted: 0
🧹 Nitpick comments (2)
src/falkor.rs (2)
1-2: LGTM! Good module organization.The separation into driver and process modules improves modularity and follows the single responsibility principle. Making the process module public while keeping the driver module private is a good encapsulation decision.
This modular structure will make it easier to:
- Maintain and test components independently
- Extend functionality without affecting other parts
- Control the public API surface
5-6: Consider documenting the re-export rationale.While the comment explains what the re-export does, it would be helpful to document why this re-export pattern was chosen over alternatives.
Add documentation explaining the architectural decision:
-// Re-export the falkor module as if it in crate::falkor +/// Re-exports the falkor driver functionality at the crate level. +/// This pattern was chosen to: +/// - Provide a clean public API +/// - Maintain implementation flexibility +/// - Allow future refactoring without breaking client code pub use falkor_driver::*;
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🔇 Additional comments (1)
src/falkor.rs (1)
1-6: Verify the impact of architectural changes.The significant restructuring from state-based to modular architecture might affect existing code. Let's verify the changes:
✅ Verification successful
Architectural changes are properly implemented ✅
The codebase shows a clean transition to the new modular architecture with:
- Proper error handling integration
- Clean module boundaries
- No remnants of old state-based code
- Consistent use of the re-exported interfaces
🏁 Scripts executed
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Script:
#!/bin/bash # Description: Check for potential issues after architectural changes # Check for any remaining references to old state-based types echo "Checking for references to removed types..." rg -l "Connected|Disconnected" --type rust # Check for any direct usage of FalkorDriver (should be through re-export) echo "Checking for direct driver usage..." rg -l "use.*falkor_driver" --type rust # Look for potential breaking changes in dependent code echo "Checking for potential breaking changes..." rg -l "Falkor::<.*>" --type rustLength of output: 407
Script:
#!/bin/bash # Search for state-related patterns and error handling echo "Checking for state-related code..." ast-grep --pattern 'struct $_ { state: $_ }' echo "Checking module structure..." fd -e rs --exec head -n 10 {} echo "Checking error handling..." rg -l 'Result<|Error' --type rustLength of output: 6125
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Actionable comments posted: 2
🧹 Nitpick comments (3)
src/neo4j.rs (3)
29-32: Add documentation explaining the constructor pattern.The implementation of
Defaultis correct, but consider adding documentation to explain whynew()is private whileDefaultis public, as this pattern might be unexpected.Also applies to: 36-36
265-271: Make process identification more robust.The current implementation might miss the Neo4j process if the command string varies. Consider a more flexible matching approach.
- search_in_os_strings(process.cmd(), "org.neo4j.server.CommunityEntryPoint") + process.cmd().iter().any(|arg| { + arg.to_str() + .map(|s| s.contains("neo4j") && s.contains("CommunityEntryPoint")) + .unwrap_or(false) + })
273-280: Consider early return optimization.The current implementation always checks all strings. Consider using
findfor early return.- os_strings - .iter() - .any(|os_string| os_string.as_os_str().to_str() == Some(target)) + os_strings.iter().find(|os_string| { + os_string.as_os_str().to_str() == Some(target) + }).is_some()
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🔇 Additional comments (3)
src/neo4j.rs (3)
6-9: LGTM: Clean integration of Prometheus metrics support.The new imports and struct fields are well-organized and properly typed for managing the metrics reporting process.
Also applies to: 15-16, 25-27
80-82: LGTM: Robust implementation of database operations.The dump and restore methods include proper error handling and asynchronous file system operations.
Also applies to: 106-108
52-54: Verify the implications of increased method visibility.The methods have been made public, which could impact module encapsulation. Please ensure this aligns with the intended API design.
Also applies to: 59-65
✅ Verification successful
Visibility changes are appropriate and well-justified
The methods are actively used across different modules (particularly in main.rs) and follow a consistent API design pattern also seen in the Falkor implementation. The public visibility aligns with their intended usage.
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| @@ -142,7 +158,7 @@ impl Neo4j { | |||
| } | |||
| } | |||
|
|
|||
| pub async fn start(&self) -> BenchmarkResult<Child> { | |||
| pub async fn start(&mut self) -> BenchmarkResult<Child> { | |||
There was a problem hiding this comment.
🛠️ Refactor suggestion
Add cleanup of existing metrics handles before initialization.
When start() is called multiple times, existing metrics handles should be cleaned up first to prevent resource leaks.
pub async fn start(&mut self) -> BenchmarkResult<Child> {
+ // Clean up existing metrics handles
+ if let Some(tx) = self.prom_shutdown_tx.take() {
+ drop(tx);
+ }
+ if let Some(handle) = self.prom_process_handle.take() {
+ let _ = handle.await;
+ }
trace!("starting Neo4j process: {} console", self.neo4j_binary());Also applies to: 191-194
| async fn report_metrics(sys: std::sync::Arc<std::sync::Mutex<System>>) -> BenchmarkResult<()> { | ||
| let mut system = sys.lock().unwrap(); | ||
| // Refresh CPU usage | ||
| system.refresh_all(); | ||
| let logical_cpus = system.cpus().len(); | ||
| let cpu_usage = system.global_cpu_usage() as i64 / logical_cpus as i64; | ||
| CPU_USAGE_GAUGE.set(cpu_usage); | ||
|
|
||
| // Refresh memory usage | ||
| let mem_used = system.used_memory(); | ||
| MEM_USAGE_GAUGE.set(mem_used as i64); | ||
|
|
||
| // Find the specific process | ||
| if let Some(pid) = get_neo4j_server_pid() { | ||
| if let Some(process) = system.process(Pid::from(pid as usize)) { | ||
| let cpu_usage = process.cpu_usage() as i64 / logical_cpus as i64; | ||
| NEO4J_CPU_USAGE_GAUGE.set(cpu_usage); | ||
| let mem_used = process.memory() as i64; | ||
| NEO4J_MEM_USAGE_GAUGE.set(mem_used); | ||
| } | ||
| } | ||
| Ok(()) | ||
| } |
There was a problem hiding this comment.
Add error handling for CPU calculations.
The CPU usage calculation could panic if logical_cpus is 0. Consider adding proper error handling.
- let cpu_usage = system.global_cpu_usage() as i64 / logical_cpus as i64;
+ let cpu_usage = if logical_cpus > 0 {
+ system.global_cpu_usage() as i64 / logical_cpus as i64
+ } else {
+ 0
+ };📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| async fn report_metrics(sys: std::sync::Arc<std::sync::Mutex<System>>) -> BenchmarkResult<()> { | |
| let mut system = sys.lock().unwrap(); | |
| // Refresh CPU usage | |
| system.refresh_all(); | |
| let logical_cpus = system.cpus().len(); | |
| let cpu_usage = system.global_cpu_usage() as i64 / logical_cpus as i64; | |
| CPU_USAGE_GAUGE.set(cpu_usage); | |
| // Refresh memory usage | |
| let mem_used = system.used_memory(); | |
| MEM_USAGE_GAUGE.set(mem_used as i64); | |
| // Find the specific process | |
| if let Some(pid) = get_neo4j_server_pid() { | |
| if let Some(process) = system.process(Pid::from(pid as usize)) { | |
| let cpu_usage = process.cpu_usage() as i64 / logical_cpus as i64; | |
| NEO4J_CPU_USAGE_GAUGE.set(cpu_usage); | |
| let mem_used = process.memory() as i64; | |
| NEO4J_MEM_USAGE_GAUGE.set(mem_used); | |
| } | |
| } | |
| Ok(()) | |
| } | |
| async fn report_metrics(sys: std::sync::Arc<std::sync::Mutex<System>>) -> BenchmarkResult<()> { | |
| let mut system = sys.lock().unwrap(); | |
| // Refresh CPU usage | |
| system.refresh_all(); | |
| let logical_cpus = system.cpus().len(); | |
| let cpu_usage = if logical_cpus > 0 { | |
| system.global_cpu_usage() as i64 / logical_cpus as i64 | |
| } else { | |
| 0 | |
| }; | |
| CPU_USAGE_GAUGE.set(cpu_usage); | |
| // Refresh memory usage | |
| let mem_used = system.used_memory(); | |
| MEM_USAGE_GAUGE.set(mem_used as i64); | |
| // Find the specific process | |
| if let Some(pid) = get_neo4j_server_pid() { | |
| if let Some(process) = system.process(Pid::from(pid as usize)) { | |
| let cpu_usage = process.cpu_usage() as i64 / logical_cpus as i64; | |
| NEO4J_CPU_USAGE_GAUGE.set(cpu_usage); | |
| let mem_used = process.memory() as i64; | |
| NEO4J_MEM_USAGE_GAUGE.set(mem_used); | |
| } | |
| } | |
| Ok(()) | |
| } |
Summary by CodeRabbit
New Features
PrometheusEndpointfor metrics server functionality.Falkorprocess management with improved lifecycle control and error handling.Bug Fixes
Documentation
Chores