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Posted to issues@spark.apache.org by "Ameen Tayyebi (JIRA)" <ji...@apache.org> on 2017/05/03 19:39:04 UTC
[jira] [Commented] (SPARK-20588) from_utc_timestamp causes
bottleneck
[ https://issues.apache.org/jira/browse/SPARK-20588?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15995499#comment-15995499 ]
Ameen Tayyebi commented on SPARK-20588:
---------------------------------------
Hopefully more readable version of the call stack:
"Executor task launch worker-63" #261 daemon prio=5 os_prio=0 tid=0x00007f848472e000 nid=0x4294 waiting for monitor entry [0x00007f501981c000]
java.lang.Thread.State: BLOCKED (on object monitor)
at java.util.TimeZone.getTimeZone(TimeZone.java:516)
- waiting to lock <0x00007f5216c2aa58> (a java.lang.Class for java.util.TimeZone)
at org.apache.spark.sql.catalyst.util.DateTimeUtils$.stringToTimestamp(DateTimeUtils.scala:356)
at org.apache.spark.sql.catalyst.util.DateTimeUtils.stringToTimestamp(DateTimeUtils.scala)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithKeys$(Unknown Source)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at org.apache.spark.shuffle.sort.UnsafeShuffleWriter.write(UnsafeShuffleWriter.java:161)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47)
at org.apache.spark.scheduler.Task.run(Task.scala:86)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
> from_utc_timestamp causes bottleneck
> ------------------------------------
>
> Key: SPARK-20588
> URL: https://issues.apache.org/jira/browse/SPARK-20588
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.0.2
> Environment: AWS EMR AMI 5.2.1
> Reporter: Ameen Tayyebi
>
> We have a SQL query that makes use of the from_utc_timestamp function like so: from_utc_timestamp(itemSigningTime,'America/Los_Angeles')
> This causes a major bottleneck. Our exact call is:
> date_add(from_utc_timestamp(itemSigningTime,'America/Los_Angeles'), 1)
> Switching from the above to date_add(itemSigningTime, 1) reduces the job running time from 40 minutes to 9.
> When from_utc_timestamp function is used, several threads in the executors are in the BLOCKED state, on this call stack:
> "Executor task launch worker-63" #261 daemon prio=5 os_prio=0 tid=0x00007f848472e000 nid=0x4294 waiting for monitor entry [0x00007f501981c000]
> java.lang.Thread.State: BLOCKED (on object monitor)
> at java.util.TimeZone.getTimeZone(TimeZone.java:516)
> - waiting to lock <0x00007f5216c2aa58> (a java.lang.Class for java.util.TimeZone)
> at org.apache.spark.sql.catalyst.util.DateTimeUtils$.stringToTimestamp(DateTimeUtils.scala:356)
> at org.apache.spark.sql.catalyst.util.DateTimeUtils.stringToTimestamp(DateTimeUtils.scala)
> at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithKeys$(Unknown Source)
> at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
> at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
> at org.apache.spark.shuffle.sort.UnsafeShuffleWriter.write(UnsafeShuffleWriter.java:161)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47)
> at org.apache.spark.scheduler.Task.run(Task.scala:86)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) at java.lang.Thread.run(Thread.java:745)
> Can we cache the locale's once per JVM so that we don't do this for every record?
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