Consolidate custom data source examples (#18142) (#18553)

## Which issue does this PR close?
This PR is for consolidating all the `custom_data_source` examples into
a single example binary. We are agreed on the pattern and we can apply
it to the remaining examples

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- part of ##18142.

## Rationale for this change

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## What changes are included in this PR?

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## Are these changes tested?

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## Are there any user-facing changes?

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---------

Co-authored-by: Sergey Zhukov <[email protected]>
Co-authored-by: Andrew Lamb <[email protected]>

Author: 3 people

datafusion-examples/Cargo.toml

@@ -43,10 +43,6 @@ path = "examples/external_dependency/dataframe-to-s3.rs"
 name = "query_aws_s3"
 path = "examples/external_dependency/query-aws-s3.rs"
 
-[[example]]
-name = "custom_file_casts"
-path = "examples/custom_file_casts.rs"
-
 [dev-dependencies]
 arrow = { workspace = true }
 # arrow_schema is required for record_batch! macro :sad:

datafusion-examples/README.md

@@ -54,18 +54,18 @@ cargo run --example dataframe
 - [`analyzer_rule.rs`](examples/analyzer_rule.rs): Use a custom AnalyzerRule to change a query's semantics (row level access control)
 - [`catalog.rs`](examples/catalog.rs): Register the table into a custom catalog
 - [`composed_extension_codec`](examples/composed_extension_codec.rs): Example of using multiple extension codecs for serialization / deserialization
-- [`csv_sql_streaming.rs`](examples/csv_sql_streaming.rs): Build and run a streaming query plan from a SQL statement against a local CSV file
-- [`csv_json_opener.rs`](examples/csv_json_opener.rs): Use low level `FileOpener` APIs to read CSV/JSON into Arrow `RecordBatch`es
-- [`custom_datasource.rs`](examples/custom_datasource.rs): Run queries against a custom datasource (TableProvider)
-- [`custom_file_casts.rs`](examples/custom_file_casts.rs): Implement custom casting rules to adapt file schemas
-- [`custom_file_format.rs`](examples/custom_file_format.rs): Write data to a custom file format
+- [`examples/custom_data_source/csv_sql_streaming.rs`](examples/custom_data_source/csv_sql_streaming.rs): Build and run a streaming query plan from a SQL statement against a local CSV file
+- [`examples/custom_data_source/csv_json_opener.rs`](examples/custom_data_source/csv_json_opener.rs): Use low level `FileOpener` APIs to read CSV/JSON into Arrow `RecordBatch`es
+- [`examples/custom_data_source/custom_datasource.rs`](examples/custom_data_source/custom_datasource.rs): Run queries against a custom datasource (TableProvider)
+- [`examples/custom_data_source/custom_file_casts.rs`](examples/custom_data_source/custom_file_casts.rs): Implement custom casting rules to adapt file schemas
+- [`examples/custom_data_source/custom_file_format.rs`](examples/custom_data_source/custom_file_format.rs): Write data to a custom file format
 - [`dataframe-to-s3.rs`](examples/external_dependency/dataframe-to-s3.rs): Run a query using a DataFrame against a parquet file from s3 and writing back to s3
 - [`dataframe.rs`](examples/dataframe.rs): Run a query using a DataFrame API against parquet files, csv files, and in-memory data, including multiple subqueries. Also demonstrates the various methods to write out a DataFrame to a table, parquet file, csv file, and json file.
 - [`examples/builtin_functions/date_time`](examples/builtin_functions/date_time.rs): Examples of date-time related functions and queries
 - [`default_column_values.rs`](examples/default_column_values.rs): Implement custom default value handling for missing columns using field metadata and PhysicalExprAdapter
 - [`deserialize_to_struct.rs`](examples/deserialize_to_struct.rs): Convert query results (Arrow ArrayRefs) into Rust structs
 - [`expr_api.rs`](examples/expr_api.rs): Create, execute, simplify, analyze and coerce `Expr`s
-- [`file_stream_provider.rs`](examples/file_stream_provider.rs): Run a query on `FileStreamProvider` which implements `StreamProvider` for reading and writing to arbitrary stream sources / sinks.
+- [`examples/custom_data_source/file_stream_provider.rs`](examples/custom_data_source/file_stream_provider.rs): Run a query on `FileStreamProvider` which implements `StreamProvider` for reading and writing to arbitrary stream sources / sinks.
 - [`flight/sql_server.rs`](examples/flight/sql_server.rs): Run DataFusion as a standalone process and execute SQL queries from Flight and and FlightSQL (e.g. JDBC) clients
 - [`examples/builtin_functions/function_factory.rs`](examples/builtin_functions/function_factory.rs): Register `CREATE FUNCTION` handler to implement SQL macros
 - [`memory_pool_tracking.rs`](examples/memory_pool_tracking.rs): Demonstrates TrackConsumersPool for memory tracking and debugging with enhanced error messages

datafusion-examples/examples/builtin_functions/main.rs

@@ -19,6 +19,11 @@
 //!
 //! These examples demonstrate miscellaneous function-related features.
 //!
+//! ## Usage
+//! ```bash
+//! cargo run --example builtin_functions -- [date_time|function_factory|regexp]
+//! ```
+//!
 //! Each subcommand runs a corresponding example:
 //! - `date_time` — examples of date-time related functions and queries
 //! - `function_factory` — register `CREATE FUNCTION` handler to implement SQL macros

datafusion-examples/examples/csv_json_opener.rs renamed to datafusion-examples/examples/custom_data_source/csv_json_opener.rs

@@ -40,8 +40,7 @@ use object_store::{local::LocalFileSystem, memory::InMemory, ObjectStore};
 /// read data from (CSV/JSON) into Arrow RecordBatches.
 ///
 /// If you want to query data in CSV or JSON files, see the [`dataframe.rs`] and [`sql_query.rs`] examples
-#[tokio::main]
-async fn main() -> Result<()> {
+pub async fn csv_json_opener() -> Result<()> {
     csv_opener().await?;
     json_opener().await?;
     Ok(())

datafusion-examples/examples/csv_sql_streaming.rs renamed to datafusion-examples/examples/custom_data_source/csv_sql_streaming.rs

@@ -21,8 +21,7 @@ use datafusion::prelude::*;
 
 /// This example demonstrates executing a simple query against an Arrow data source (CSV) and
 /// fetching results with streaming aggregation and streaming window
-#[tokio::main]
-async fn main() -> Result<()> {
+pub async fn csv_sql_streaming() -> Result<()> {
     // create local execution context
     let ctx = SessionContext::new();
 

datafusion-examples/examples/custom_datasource.rs renamed to datafusion-examples/examples/custom_data_source/custom_datasource.rs

@@ -42,8 +42,7 @@ use datafusion::catalog::Session;
 use tokio::time::timeout;
 
 /// This example demonstrates executing a simple query against a custom datasource
-#[tokio::main]
-async fn main() -> Result<()> {
+pub async fn custom_datasource() -> Result<()> {
     // create our custom datasource and adding some users
     let db = CustomDataSource::default();
     db.populate_users();

datafusion-examples/examples/custom_file_casts.rs renamed to datafusion-examples/examples/custom_data_source/custom_file_casts.rs

@@ -44,9 +44,7 @@ use object_store::{ObjectStore, PutPayload};
 // This example enforces that casts must be strictly widening: if the file type is Int64 and the table type is Int32, it will error
 // before even reading the data.
 // Without this custom cast rule DataFusion would happily do the narrowing cast, potentially erroring only if it found a row with data it could not cast.
-
-#[tokio::main]
-async fn main() -> Result<()> {
+pub async fn custom_file_casts() -> Result<()> {
     println!("=== Creating example data ===");
 
     // Create a logical / table schema with an Int32 column

datafusion-examples/examples/custom_file_format.rs renamed to datafusion-examples/examples/custom_data_source/custom_file_format.rs

@@ -48,6 +48,42 @@ use tempfile::tempdir;
 /// TSVFileFormatFactory is responsible for creating instances of TSVFileFormat.
 /// The former, once registered with the SessionState, will then be used
 /// to facilitate SQL operations on TSV files, such as `COPY TO` shown here.
+pub async fn custom_file_format() -> Result<()> {
+    // Create a new context with the default configuration
+    let mut state = SessionStateBuilder::new().with_default_features().build();
+
+    // Register the custom file format
+    let file_format = Arc::new(TSVFileFactory::new());
+    state.register_file_format(file_format, true)?;
+
+    // Create a new context with the custom file format
+    let ctx = SessionContext::new_with_state(state);
+
+    let mem_table = create_mem_table();
+    ctx.register_table("mem_table", mem_table)?;
+
+    let temp_dir = tempdir().unwrap();
+    let table_save_path = temp_dir.path().join("mem_table.tsv");
+
+    let d = ctx
+        .sql(&format!(
+            "COPY mem_table TO '{}' STORED AS TSV;",
+            table_save_path.display(),
+        ))
+        .await?;
+
+    let results = d.collect().await?;
+    println!(
+        "Number of inserted rows: {:?}",
+        (results[0]
+            .column_by_name("count")
+            .unwrap()
+            .as_primitive::<UInt64Type>()
+            .value(0))
+    );
+
+    Ok(())
+}
 
 #[derive(Debug)]
 /// Custom file format that reads and writes TSV files
@@ -181,44 +217,6 @@ impl GetExt for TSVFileFactory {
     }
 }
 
-#[tokio::main]
-async fn main() -> Result<()> {
-    // Create a new context with the default configuration
-    let mut state = SessionStateBuilder::new().with_default_features().build();
-
-    // Register the custom file format
-    let file_format = Arc::new(TSVFileFactory::new());
-    state.register_file_format(file_format, true).unwrap();
-
-    // Create a new context with the custom file format
-    let ctx = SessionContext::new_with_state(state);
-
-    let mem_table = create_mem_table();
-    ctx.register_table("mem_table", mem_table).unwrap();
-
-    let temp_dir = tempdir().unwrap();
-    let table_save_path = temp_dir.path().join("mem_table.tsv");
-
-    let d = ctx
-        .sql(&format!(
-            "COPY mem_table TO '{}' STORED AS TSV;",
-            table_save_path.display(),
-        ))
-        .await?;
-
-    let results = d.collect().await?;
-    println!(
-        "Number of inserted rows: {:?}",
-        (results[0]
-            .column_by_name("count")
-            .unwrap()
-            .as_primitive::<UInt64Type>()
-            .value(0))
-    );
-
-    Ok(())
-}
-
 // create a simple mem table
 fn create_mem_table() -> Arc<MemTable> {
     let fields = vec![

datafusion-examples/examples/file_stream_provider.rs renamed to datafusion-examples/examples/custom_data_source/file_stream_provider.rs

@@ -15,6 +15,29 @@
 // specific language governing permissions and limitations
 // under the License.
 
+/// Demonstrates how to use [`FileStreamProvider`] and [`StreamTable`] to stream data
+/// from a file-like source (FIFO) into DataFusion for continuous querying.
+///
+/// On non-Windows systems, this example creates a named pipe (FIFO) and
+/// writes rows into it asynchronously while DataFusion reads the data
+/// through a `FileStreamProvider`.  
+///
+/// This illustrates how to integrate dynamically updated data sources
+/// with DataFusion without needing to reload the entire dataset each time.
+///
+/// This example does not work on Windows.
+pub async fn file_stream_provider() -> datafusion::error::Result<()> {
+    #[cfg(target_os = "windows")]
+    {
+        println!("file_stream_provider example does not work on windows");
+        Ok(())
+    }
+    #[cfg(not(target_os = "windows"))]
+    {
+        non_windows::main().await
+    }
+}
+
 #[cfg(not(target_os = "windows"))]
 mod non_windows {
     use datafusion::assert_batches_eq;
@@ -186,16 +209,3 @@ mod non_windows {
         Ok(())
     }
 }
-
-#[tokio::main]
-async fn main() -> datafusion::error::Result<()> {
-    #[cfg(target_os = "windows")]
-    {
-        println!("file_stream_provider example does not work on windows");
-        Ok(())
-    }
-    #[cfg(not(target_os = "windows"))]
-    {
-        non_windows::main().await
-    }
-}

datafusion-examples/examples/custom_data_source/main.rs

@@ -0,0 +1,126 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements.  See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership.  The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License.  You may obtain a copy of the License at
+//
+//   http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied.  See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+//! # These examples are all related to extending or defining how DataFusion reads data
+//!
+//! These examples demonstrate how DataFusion reads data.
+//!
+//! ## Usage
+//! ```bash
+//! cargo run --example custom_data_source -- [csv_json_opener|csv_sql_streaming|custom_datasource|custom_file_casts|custom_file_format|file_stream_provider]
+//! ```
+//!
+//! Each subcommand runs a corresponding example:
+//! - `csv_json_opener` — use low level FileOpener APIs to read CSV/JSON into Arrow RecordBatches
+//! - `csv_sql_streaming` — build and run a streaming query plan from a SQL statement against a local CSV file
+//! - `custom_datasource` — run queries against a custom datasource (TableProvider)
+//! - `custom_file_casts` — implement custom casting rules to adapt file schemas
+//! - `custom_file_format` — write data to a custom file format
+//! - `file_stream_provider` — run a query on FileStreamProvider which implements StreamProvider for reading and writing to arbitrary stream sources/sinks
+
+mod csv_json_opener;
+mod csv_sql_streaming;
+mod custom_datasource;
+mod custom_file_casts;
+mod custom_file_format;
+mod file_stream_provider;
+
+use std::str::FromStr;
+
+use datafusion::error::{DataFusionError, Result};
+
+enum ExampleKind {
+    CsvJsonOpener,
+    CsvSqlStreaming,
+    CustomDatasource,
+    CustomFileCasts,
+    CustomFileFormat,
+    FileFtreamProvider,
+}
+
+impl AsRef<str> for ExampleKind {
+    fn as_ref(&self) -> &str {
+        match self {
+            Self::CsvJsonOpener => "csv_json_opener",
+            Self::CsvSqlStreaming => "csv_sql_streaming",
+            Self::CustomDatasource => "custom_datasource",
+            Self::CustomFileCasts => "custom_file_casts",
+            Self::CustomFileFormat => "custom_file_format",
+            Self::FileFtreamProvider => "file_stream_provider",
+        }
+    }
+}
+
+impl FromStr for ExampleKind {
+    type Err = DataFusionError;
+
+    fn from_str(s: &str) -> Result<Self> {
+        match s {
+            "csv_json_opener" => Ok(Self::CsvJsonOpener),
+            "csv_sql_streaming" => Ok(Self::CsvSqlStreaming),
+            "custom_datasource" => Ok(Self::CustomDatasource),
+            "custom_file_casts" => Ok(Self::CustomFileCasts),
+            "custom_file_format" => Ok(Self::CustomFileFormat),
+            "file_stream_provider" => Ok(Self::FileFtreamProvider),
+            _ => Err(DataFusionError::Execution(format!("Unknown example: {s}"))),
+        }
+    }
+}
+
+impl ExampleKind {
+    const ALL: [Self; 6] = [
+        Self::CsvJsonOpener,
+        Self::CsvSqlStreaming,
+        Self::CustomDatasource,
+        Self::CustomFileCasts,
+        Self::CustomFileFormat,
+        Self::FileFtreamProvider,
+    ];
+
+    const EXAMPLE_NAME: &str = "custom_data_source";
+
+    fn variants() -> Vec<&'static str> {
+        Self::ALL.iter().map(|x| x.as_ref()).collect()
+    }
+}
+
+#[tokio::main]
+async fn main() -> Result<()> {
+    let usage = format!(
+        "Usage: cargo run --example {} -- [{}]",
+        ExampleKind::EXAMPLE_NAME,
+        ExampleKind::variants().join("|")
+    );
+
+    let arg = std::env::args().nth(1).ok_or_else(|| {
+        eprintln!("{usage}");
+        DataFusionError::Execution("Missing argument".to_string())
+    })?;
+
+    match arg.parse::<ExampleKind>()? {
+        ExampleKind::CsvJsonOpener => csv_json_opener::csv_json_opener().await?,
+        ExampleKind::CsvSqlStreaming => csv_sql_streaming::csv_sql_streaming().await?,
+        ExampleKind::CustomDatasource => custom_datasource::custom_datasource().await?,
+        ExampleKind::CustomFileCasts => custom_file_casts::custom_file_casts().await?,
+        ExampleKind::CustomFileFormat => custom_file_format::custom_file_format().await?,
+        ExampleKind::FileFtreamProvider => {
+            file_stream_provider::file_stream_provider().await?
+        }
+    }
+
+    Ok(())
+}