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https://issues.apache.org/jira/browse/SPARK-20286?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15972231#comment-15972231
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Umesh Chaudhary commented on SPARK-20286:
-----------------------------------------
Yep, +1 to the UI changes. However, I tested the behaviour by following the
steps mentioned by you and this seems to be fixed in 2.1.0.
{code}
spark2-shell --conf spark.dynamicAllocation.executorIdleTimeout=7s --conf
spark.dynamicAllocation.cachedExecutorIdleTimeout=20s --conf
spark.dynamicAllocation.minExecutors=2
scala> sc.setLogLevel("INFO")
scala> val rdd=sc.textFile("/tmp/config.txt")
..
17/04/17 23:46:58 INFO spark.SparkContext: Created broadcast 0 from textFile at
<console>:24
rdd: org.apache.spark.rdd.RDD[String] = /tmp/config.txt MapPartitionsRDD[1] at
textFile at <console>:24
..
..
scala> rdd.collect
17/04/17 23:47:10 INFO mapred.FileInputFormat: Total input paths to process : 1
17/04/17 23:47:10 INFO spark.SparkContext: Starting job: collect at <console>:27
..
..
17/04/17 23:47:13 INFO scheduler.DAGScheduler: Job 0 finished: collect at
<console>:27, took 3.457215 s
..
scala> 17/04/17 23:47:20 INFO spark.ExecutorAllocationManager: Request to
remove executorIds: 1
{code}
As expected executors remove request was received above after 7 secs. Then I
tested behaviour for persist:
{code}
scala> rdd.persist
res2: rdd.type = /tmp/config.txt MapPartitionsRDD[1] at textFile at <console>:24
scala> rdd.count
17/04/17 23:47:45 INFO spark.SparkContext: Starting job: count at <console>:27
..
17/04/17 23:47:45 INFO scheduler.DAGScheduler: Job 1 finished: count at
<console>:27, took 0.293053 s
..
scala> 17/04/17 23:48:05 INFO spark.ExecutorAllocationManager: Request to
remove executorIds: 1
{code}
In this case also request for removing the executor was received after 20 secs.
Afterwords I tested unpersist:
{code}
scala> rdd.unpersist(true)
17/04/17 23:50:22 INFO rdd.MapPartitionsRDD: Removing RDD 1 from persistence
list
17/04/17 23:50:22 INFO storage.BlockManager: Removing RDD 1
res7: rdd.type = /tmp/config.txt MapPartitionsRDD[1] at textFile at <console>:24
scala> rdd.count
17/04/17 23:50:31 INFO spark.SparkContext: Starting job: count at <console>:27
..
17/04/17 23:50:31 INFO scheduler.DAGScheduler: Job 3 finished: count at
<console>:27, took 0.219764 s
res8: Long = 100
..
scala> 17/04/17 23:50:38 INFO spark.ExecutorAllocationManager: Request to
remove executorIds: 1
{code}
This time remove request was received after 7 secs.
> dynamicAllocation.executorIdleTimeout is ignored after unpersist
> ----------------------------------------------------------------
>
> Key: SPARK-20286
> URL: https://issues.apache.org/jira/browse/SPARK-20286
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 2.0.1
> Reporter: Miguel Pérez
>
> With dynamic allocation enabled, it seems that executors with cached data
> which are unpersisted are still being killed using the
> {{dynamicAllocation.cachedExecutorIdleTimeout}} configuration, instead of
> {{dynamicAllocation.executorIdleTimeout}}. Assuming the default configuration
> ({{dynamicAllocation.cachedExecutorIdleTimeout = Infinity}}), an executor
> with unpersisted data won't be released until the job ends.
> *How to reproduce*
> - Set different values for {{dynamicAllocation.executorIdleTimeout}} and
> {{dynamicAllocation.cachedExecutorIdleTimeout}}
> - Load a file into a RDD and persist it
> - Execute an action on the RDD (like a count) so some executors are activated.
> - When the action has finished, unpersist the RDD
> - The application UI removes correctly the persisted data from the *Storage*
> tab, but if you look in the *Executors* tab, you will find that the executors
> remain *active* until ({{dynamicAllocation.cachedExecutorIdleTimeout}} is
> reached.
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