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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-20588) from_utc_timestamp causes bottleneck
Date Wed, 10 May 2017 07:05:04 GMT

    [ https://issues.apache.org/jira/browse/SPARK-20588?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16004184#comment-16004184
] 

Apache Spark commented on SPARK-20588:
--------------------------------------

User 'ueshin' has created a pull request for this issue:
https://github.com/apache/spark/pull/17933

> from_utc_timestamp causes bottleneck
> ------------------------------------
>
>                 Key: SPARK-20588
>                 URL: https://issues.apache.org/jira/browse/SPARK-20588
>             Project: Spark
>          Issue Type: Improvement
>          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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