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https://issues.apache.org/jira/browse/SPARK-8973?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sean Owen resolved SPARK-8973.
------------------------------
Resolution: Not A Problem
Target Version/s: (was: 1.4.0)
Please read
https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark
Just having a busy executor is not a problem. You'd have to state a clearer
problem.
> Spark Executor usage Cpu 100+%
> -------------------------------
>
> Key: SPARK-8973
> URL: https://issues.apache.org/jira/browse/SPARK-8973
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 1.4.0
> Reporter: Xu Chen
>
> Spark Executor usage Cpu 100+%
> Use Spark-Sql-CLI to count a CACHE TABLE , when I look out the top command I
> got some Cpu 100+% processes that Spark Executors
> when I use jstack to check it I found this thread
> {code:java}
> "Executor task launch worker-1" daemon prio=10 tid=0x00007fc9983eb000
> nid=0x2f3 runnable [0x00007fc9893f9000]
> java.lang.Thread.State: RUNNABLE
> at scala.collection.mutable.HashMap.update(HashMap.scala:80)
> at
> org.apache.spark.sql.columnar.compression.DictionaryEncoding$Encoder.gatherCompressibilityStats(compressionSchemes.scala:233)
> at
> org.apache.spark.sql.columnar.compression.CompressibleColumnBuilder$class.gatherCompressibilityStats(CompressibleColumnBuilder.scala:72)
> at
> org.apache.spark.sql.columnar.compression.CompressibleColumnBuilder$class.appendFrom(CompressibleColumnBuilder.scala:80)
> at
> org.apache.spark.sql.columnar.NativeColumnBuilder.appendFrom(ColumnBuilder.scala:87)
> at
> org.apache.spark.sql.columnar.InMemoryRelation$$anonfun$3$$anon$1.next(InMemoryColumnarTableScan.scala:148)
> at
> org.apache.spark.sql.columnar.InMemoryRelation$$anonfun$3$$anon$1.next(InMemoryColumnarTableScan.scala:124)
> at scala.collection.Iterator$$anon$12.next(Iterator.scala:357)
> at
> org.apache.spark.serializer.SerializationStream.writeAll(Serializer.scala:153)
> at
> org.apache.spark.storage.BlockManager.dataSerializeStream(BlockManager.scala:1187)
> at
> org.apache.spark.storage.DiskStore$$anonfun$putIterator$1.apply$mcV$sp(DiskStore.scala:81)
> at
> org.apache.spark.storage.DiskStore$$anonfun$putIterator$1.apply(DiskStore.scala:81)
> at
> org.apache.spark.storage.DiskStore$$anonfun$putIterator$1.apply(DiskStore.scala:81)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1285)
> at org.apache.spark.storage.DiskStore.putIterator(DiskStore.scala:82)
> at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:788)
> - locked <0x00000007a9471e30> (a org.apache.spark.storage.BlockInfo)
> at
> org.apache.spark.storage.BlockManager.putIterator(BlockManager.scala:635)
> at
> org.apache.spark.CacheManager.putInBlockManager(CacheManager.scala:153)
> at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:78)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:242)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:70)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
> at org.apache.spark.scheduler.Task.run(Task.scala:70)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> at java.lang.Thread.run(Thread.java:744)
>
> {code}
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