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From "Ian (JIRA)" <j...@apache.org>
Subject [jira] [Created] (SPARK-19462) when spark.sql.adaptive.enabled is enabled RDD is not resilient to node container failure
Date Sun, 05 Feb 2017 10:07:41 GMT
Ian created SPARK-19462:
---------------------------

             Summary: when spark.sql.adaptive.enabled is enabled RDD is not resilient to node
container failure
                 Key: SPARK-19462
                 URL: https://issues.apache.org/jira/browse/SPARK-19462
             Project: Spark
          Issue Type: Bug
          Components: SQL
    Affects Versions: 1.6.3
            Reporter: Ian


property spark.sql.adaptive.enabled needs to be set "true"

reproducible steps using spark-shell
1. launch spark-shell
2. 
{code}
val df1 = sc.parallelize( 1 to 1000, 2).toDF("number")
df1.registerTempTable("test")

val data1 = sqlContext.sql("SELECT * FROM test WHERE number > 50")
data1.collect

val data2 = sqlContext.sql("SELECT number, count(*) cnt FROM test GROUP BY number")
data2.collect

// everything is fine up to this point
// manually kill all both the AM and all the NM of the spark-shell app

// rerun data1.collect the result is return successfully
data1.collect

// but data2.collect will fail
data2.collect

// stacktrace
Caused by: java.lang.RuntimeException: Exchange not implemented for UnknownPartitioning(1)
  at scala.sys.package$.error(package.scala:27)
  at org.apache.spark.sql.execution.Exchange.org$apache$spark$sql$execution$Exchange$$getPartitionKeyExtractor$1(Exchange.scala:198)
  at org.apache.spark.sql.execution.Exchange$$anonfun$3.apply(Exchange.scala:208)
  at org.apache.spark.sql.execution.Exchange$$anonfun$3.apply(Exchange.scala:207)
  at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$21.apply(RDD.scala:728)
  at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$21.apply(RDD.scala:728)
  at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
  at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
  at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
  at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
  at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
  at org.apache.spark.scheduler.Task.run(Task.scala:89)
  at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:227)
  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)

{code}








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