From 01e755ccca671bcfa9c78f4a251a4494c4170c7f Mon Sep 17 00:00:00 2001 From: duanmeng Date: Tue, 17 Dec 2024 21:50:22 -0800 Subject: [PATCH] docs: Update tracing doc (#11890) Summary: Updates query tracing docs. Pull Request resolved: https://github.com/facebookincubator/velox/pull/11890 Reviewed By: gggrace14 Differential Revision: D67370905 Pulled By: xiaoxmeng fbshipit-source-id: 09ad7857992027d79b0a84d8c6336e6bca899ccb --- velox/docs/develop/debugging/tracing.rst | 201 ++++++++++++++--------- velox/docs/develop/images/trace-arch.png | Bin 530034 -> 261206 bytes 2 files changed, 126 insertions(+), 75 deletions(-) diff --git a/velox/docs/develop/debugging/tracing.rst b/velox/docs/develop/debugging/tracing.rst index 0536546d2a6e..02579d684e13 100644 --- a/velox/docs/develop/debugging/tracing.rst +++ b/velox/docs/develop/debugging/tracing.rst @@ -2,43 +2,42 @@ Tracing ======= - Background ---------- -The query trace tool helps analyze and debug query performance and correctness -issues. It helps prevent interference from the test noises in a production -environment (such as storage, network etc) by allowing replay of a part of the -query plan and data set in an isolated environment such as a local machine. -This is useful for debugging query performance debugging as we don't have to -replay the whole query in a production environment. +The query trace tool helps analyze and debug query performance and correctness issues. It helps prevent +interference from external noise in a production environment (such as storage, network, etc.) by allowing +replay of a part of the query plan and dataset in an isolated environment, such as a local machine. +This is much more efficient for query performance analysis and issue debugging, as it eliminates the need +to replay the whole query in a production environment. How Tracing Tool Works ---------------------- -The tracing process consists of two phases: tracing and replaying. +The tracing process consists of two distinct phases: the tracing phase and the replaying phase. The +tracing phase is executed within a production environment, while the replaying phase is conducted in +a local development environment. **Tracing Phase** -- When the query starts, the task records the metadata including query plan fragment, - query configuration, and connector properties. -- During the query execution, each traced operator records the input vectors and saves - in the specified storage location. -- The metadata are serialized using json format and operator data inputs are serialized - using `Presto serializer `_. +1. Trace replay required metadata, including the query plan fragment, query configuration, + and connector properties, is recorded during the query task initiation. +2. Throughout query processing, each traced operator logs the input vectors or splits + storing them in a designated storage location. +3. The metadata and splits are serialized in JSON format, and the operator data inputs are + serialized using a `Presto serializer `_. **Replaying Phase** -1. Read and deserialize the recorded query plan in tracing phase, extract the target plan - node, and assemble a plan fragment with a customized source and sink nodes. The source - node reads the input from the serialized operator inputs on storage and sink operator +1. Read and deserialize the recorded query plan, extract the traced plan node, and assemble a plan + fragment with customized source and sink nodes. +2. The source node reads the input from the serialized operator inputs on storage and the sink operator prints or logs out the execution stats. -2. Build a task with the assembled plan fragment in step 1. -3. Apply the recorded query configuration and connector properties to replay the task with - the same input and configuration as in production. +3. Build a task with the assembled plan fragment in step 1. Apply the recorded query configuration and + connector properties to replay the task with the same input and configuration setup as in production. -**NOTE**: The Presto serialization doesn't always preserve vector encoding (lazy vectors are -loaded, nested dictionaries are flattened). Hence, replay may differ from the original run. +**NOTE**: The presto serialization might lose input vector encoding, such as lazy vector and nested dictionary +encoding, which affects the operator’s execution. Hence, it might not always be the same as in production. .. image:: ../images/trace-arch.png :width: 600 @@ -49,13 +48,16 @@ Tracing Framework The tracing framework consists of three components: -1. **Metadata and Data Writer**: metadata writer and the data writer. -2. **Metadata and Data Reader**: metadata reader and the data reader. -3. **Query Trace Replayer**: display query summaries or replay the - execution of the target operator. +1. **Query Trace Writers**: records the metadata, input data, and scan splits. +2. **Query Trace Readers**: load the metadata, read input data, and scan splits. +3. **Query Trace Replayers**: display query summaries or replay the execution of the target operator. + +Trace Writers +^^^^^^^^^^^^^ -Query Trace Writer -^^^^^^^^^^^^^^^^^^ +There are three types of writers: `TaskTraceMetadataWriter`, `OperatorTraceInputWriter`, +and `OperatorTraceSplitWriter`. They are used in the prod or shadow environment to record +the real execution data. **TaskTraceMetadataWriter** records the query metadata during task creation, serializes, and writes them into a file in JSON format. There are two kinds @@ -66,77 +68,126 @@ of metadata: - Plan fragment of the task (also known as a plan node tree). It can be serialized as a JSON object, which is already supported in Velox. -**OperatorTraceWriter** records the input vectors from the target operator, which are -serialized and written as a binary file. +**OperatorTraceInputWriter** records the input vectors from the target operator, it uses a Presto +serializer to serialize each vector batch and flush immediately to ensure that replay is possible +even if a crash occurs during execution. It is created during the target operator's initialization +and writes data in the `Operator::addInput` method during execution. It finishes when the target +operator is closed. However, it can finish early if the recorded data size exceeds the limit specified +by the user. -Query Trace Reader -^^^^^^^^^^^^^^^^^^ +**OperatorTraceSplitWriter** captures the input splits from the target `TableScan` operator. It +serializes each split and immediately flushes it to ensure that replay is possible even if a crash +occurs during execution. Each split is serialized as follows: -**TaskTraceMetadataReader** can load the query metadata JSON file, and extract the query -configurations, connector properties, and the plan fragment. +.. code-block:: c++ -**QueryDataReader** can read and deserialize the input vectors of the target operator. -It is used as the utility to replay the input data as a source operator in the target -operator replay. + | length : uint32_t | split : JSON string | crc32 : uint32_t | -**NOTE**: `OperatorTraceWriter` serializes and flushes the input vectors in batches, -allowing it to replay the input process using the same sequence of batches. -Query Trace Util -^^^^^^^^^^^^^^^^ +Query Trace Readers +^^^^^^^^^^^^^^^^^^^ -- Create tracing directories. -- Get query summaries. -- Provide utilities to extract the target plan node, and assemble a plan fragment with - customized trace source and sink node with it. +Three types of readers correspond to the query trace writers: `TaskTraceMetadataReader`, +`OperatorTraceInputReader`, and `OperatorTraceSplitReader`. The replayers typically use +them in the local environment, which will be described in detail in the Query Trace Replayer section. -Query Trace Tool ----------------- +**TaskTraceMetadataReader** can load the query metadata JSON file and extract the query +configurations, connector properties, and a plan fragment. The replayer uses these to build +a replay task. -The query trace tool leverages the trace reader to display query summaries and replay the -execution of specific operators (TBD). +**OperatorTraceInputReader** reads and deserializes the input vectors in a tracing data file. +It is created and used by a `QueryTraceScan` operator which will be described in detail in +the **Query Trace Scan** section. -Tracing tools Usage -^^^^^^^^^^^^^^^^^^^ +**OperatorTraceSplitReader** reads and deserializes the input splits in tracing split info files, +and produces a list of `exec::Split` for the query replay. -.. code-block:: c++ +How To Replay +------------- - query_replayer --root $root_dir --summary --pretty +After the traced query finishes, its metadata and the input data for the target tasks and operators +are all saved in the directory specified by `query_trace_dir`. +To get a glance at the traced task, we can execute the following command: -It would show something as the follows +.. code-block:: c++ + + velox_query_replayer --root_dir /trace_root --task_id task-4 --summary + +It would show something as the follows: .. code-block:: c++ ++++++Query trace summary++++++ Number of tasks: 1 - Task ids: task-1 - ++++++Query configs and plan:++++++ - { - "planNode":{ - "filter":{}, - "outputType":{...}, - "nullAware":false, - "sources":[{...}, {...}], - "leftKeys":[], - "joinType":"INNER", - "id":"5", - "name":"HashJoinNode" - }, - "connectorProperties":{...}, - "queryConfig":{...} - } + ++++++Query configs++++++ + query_trace_task_reg_exp: .* + query_trace_node_ids: 2 + query_trace_max_bytes: 107374182400 + query_trace_dir: /tmp/velox_test_aJqeFd/basic/traceRoot/ + query_trace_enabled: 1 + + ++++++Connector configs++++++ + + ++++++Task query plan++++++ + -- HashJoin[2][INNER t0=u0] -> t0:BIGINT, t1:VARCHAR, t2:SMALLINT, t3:REAL, u0:BIGINT, u1:INTEGER, u2:SMALLINT, u3:VARCHAR + -- TableScan[0][table: hive_table] -> t0:BIGINT, t1:VARCHAR, t2:SMALLINT, t3:REAL + -- TableScan[1][table: hive_table] -> u0:BIGINT, u1:INTEGER, u2:SMALLINT, u3:VARCHAR + + ++++++Task Summaries++++++ + + ++++++Task task-1++++++ + + ++++++Pipeline 2++++++ + driver 0: opType HashProbe, inputRows 70720, peakMemory 108.00KB + driver 1: opType HashProbe, inputRows 70720, peakMemory 108.00KB + + ++++++Pipeline 3++++++ + driver 0: opType HashBuild, inputRows 48000, peakMemory 4.51MB + driver 1: opType HashBuild, inputRows 48000, peakMemory 2.25MB + +Then we can re-execute the query using the following command in the terminal or use the same flags in your IDE to debug. + +.. code-block:: c++ + + velox_query_replayer --root_dir /Users/bytedance/work/native/trace --query_id query-1 --task_id task-1 --node_id 2 + +.. code-block:: c++ + + Stats of replaying operator HashBuild : Output: 0 rows (0B, 0 batches), Cpu time: 48.63us, Wall time: 65.22us, Blocked wall time: 24.08ms, Peak memory: 4.51MB, Memory allocations: 16, Threads: 2, CPU breakdown: B/I/O/F (23.79us/0ns/14.46us/10.38us) + + Stats of replaying operator HashProbe : Output: 13578240 rows (1.17GB, 13280 batches), Cpu time: 3.99s, Wall time: 4.01s, Blocked wall time: 98.58ms, Peak memory: 108.00KB, Memory allocations: 12534, Threads: 2, CPU breakdown: B/I/O/F (8.52ms/1.59s/2.39s/20.29us) + + Memory usage: TaskCursorQuery_0 usage 0B reserved 0B peak 10.00MB + task.test_cursor 1 usage 0B reserved 0B peak 10.00MB + node.2 usage 0B reserved 0B peak 0B + op.2.1.1.OperatorTraceScan usage 0B reserved 0B peak 0B + op.2.1.0.OperatorTraceScan usage 0B reserved 0B peak 0B + node.N/A usage 0B reserved 0B peak 0B + op.N/A.0.1.CallbackSink usage 0B reserved 0B peak 0B + op.N/A.0.0.CallbackSink usage 0B reserved 0B peak 0B + node.1 usage 0B reserved 0B peak 10.00MB + op.1.1.0.HashBuild usage 0B reserved 0B peak 4.51MB + op.1.0.1.HashProbe usage 0B reserved 0B peak 108.00KB + op.1.1.1.HashBuild usage 0B reserved 0B peak 2.25MB + op.1.0.0.HashProbe usage 0B reserved 0B peak 108.00KB + node.0 usage 0B reserved 0B peak 0B + op.0.0.1.OperatorTraceScan usage 0B reserved 0B peak 0B + op.0.0.0.OperatorTraceScan usage 0B reserved 0B peak 0B Here is a full list of supported command line arguments. -* ``--usage``: Show the usage. -* ``--root``: Root dir of the query tracing. +* ``--root_dir``: The root directory where the replayer is reading the traced data, must be set. * ``--summary``: Show the summary of the tracing including number of tasks and task ids. It also print the query metadata including query configs, connectors properties, and query plan in JSON format. -* ``--short_summary``: Only show number of tasks and task ids. -* ``--task_id``: Specify the target task id, if empty, show the summary of all the traced query tasks. - +* ``--query_id``: Specify the target query ID, it must be set. +* ``--task_id``: Specify the target task ID, it must be set. +* ``--node_id``: Specify the target node ID, it must be set. +* ``--driver_ids``: Specify the target driver IDs to replay. +* ``--shuffle_serialization_format``: Specify the shuffle serialization format. +* ``--table_writer_output_dir``: Specify the output directory of TableWriter. +* ``--hiveConnectorExecutorHwMultiplier``: Hardware multiplier for hive connector. 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