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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-23429) Add executor memory metrics to heartbeat and expose in executors REST API
Date Tue, 30 Oct 2018 03:58:02 GMT

    [ https://issues.apache.org/jira/browse/SPARK-23429?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16668089#comment-16668089
] 

Apache Spark commented on SPARK-23429:
--------------------------------------

User 'LantaoJin' has created a pull request for this issue:
https://github.com/apache/spark/pull/22884

> Add executor memory metrics to heartbeat and expose in executors REST API
> -------------------------------------------------------------------------
>
>                 Key: SPARK-23429
>                 URL: https://issues.apache.org/jira/browse/SPARK-23429
>             Project: Spark
>          Issue Type: Sub-task
>          Components: Spark Core
>    Affects Versions: 2.2.1
>            Reporter: Edwina Lu
>            Priority: Major
>             Fix For: 3.0.0
>
>
> Add new executor level memory metrics ( jvmUsedMemory, onHeapExecutionMemory, offHeapExecutionMemory,
onHeapStorageMemory, offHeapStorageMemory, onHeapUnifiedMemory, and offHeapUnifiedMemory),
and expose these via the executors REST API. This information will help provide insight into
how executor and driver JVM memory is used, and for the different memory regions. It can be
used to help determine good values for spark.executor.memory, spark.driver.memory, spark.memory.fraction,
and spark.memory.storageFraction.
> Add an ExecutorMetrics class, with jvmUsedMemory, onHeapExecutionMemory, offHeapExecutionMemory,
onHeapStorageMemory, and offHeapStorageMemory. This will track the memory usage at the executor
level. The new ExecutorMetrics will be sent by executors to the driver as part of the Heartbeat.
A heartbeat will be added for the driver as well, to collect these metrics for the driver.
> Modify the EventLoggingListener to log ExecutorMetricsUpdate events if there is a new
peak value for one of the memory metrics for an executor and stage. Only the ExecutorMetrics
will be logged, and not the TaskMetrics, to minimize additional logging. Analysis on a set
of sample applications showed an increase of 0.25% in the size of the Spark history log, with
this approach.
> Modify the AppStatusListener to collect snapshots of peak values for each memory metric.
Each snapshot has the time, jvmUsedMemory, executionMemory and storageMemory, and list of
active stages.
> Add the new memory metrics (snapshots of peak values for each memory metric) to the executors
REST API.
> This is a subtask for SPARK-23206. Please refer to the design doc for that ticket for
more details.



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