peng bo created SPARK-27406:
-------------------------------
Summary: UnsafeArrayData serialization breaks when two machines
have different Oops size
Key: SPARK-27406
URL: https://issues.apache.org/jira/browse/SPARK-27406
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 2.4.1
Reporter: peng bo
java.lang.NullPointerException
at
org.apache.spark.sql.catalyst.expressions.aggregate.ApproxCountDistinctForIntervals$$anonfun$endpoints$1.apply(ApproxCountDistinctForIntervals.scala:69)
at
org.apache.spark.sql.catalyst.expressions.aggregate.ApproxCountDistinctForIntervals$$anonfun$endpoints$1.apply(ApproxCountDistinctForIntervals.scala:69)
at
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at
scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:186)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:186)
at
org.apache.spark.sql.catalyst.expressions.aggregate.ApproxCountDistinctForIntervals.endpoints$lzycompute(ApproxCountDistinctForIntervals.scala:69)
at
org.apache.spark.sql.catalyst.expressions.aggregate.ApproxCountDistinctForIntervals.endpoints(ApproxCountDistinctForIntervals.scala:66)
at
org.apache.spark.sql.catalyst.expressions.aggregate.ApproxCountDistinctForIntervals.org$apache$spark$sql$catalyst$expressions$aggregate$ApproxCountDistinctForIntervals$$hllppArray$lzycompute(ApproxCountDistinctForIntervals.scala:94)
at
org.apache.spark.sql.catalyst.expressions.aggregate.ApproxCountDistinctForIntervals.org$apache$spark$sql$catalyst$expressions$aggregate$ApproxCountDistinctForIntervals$$hllppArray(ApproxCountDistinctForIntervals.scala:93)
at
org.apache.spark.sql.catalyst.expressions.aggregate.ApproxCountDistinctForIntervals.org$apache$spark$sql$catalyst$expressions$aggregate$ApproxCountDistinctForIntervals$$numWordsPerHllpp$lzycompute(ApproxCountDistinctForIntervals.scala:104)
at
org.apache.spark.sql.catalyst.expressions.aggregate.ApproxCountDistinctForIntervals.org$apache$spark$sql$catalyst$expressions$aggregate$ApproxCountDistinctForIntervals$$numWordsPerHllpp(ApproxCountDistinctForIntervals.scala:104)
at
org.apache.spark.sql.catalyst.expressions.aggregate.ApproxCountDistinctForIntervals.totalNumWords$lzycompute(ApproxCountDistinctForIntervals.scala:106)
at
org.apache.spark.sql.catalyst.expressions.aggregate.ApproxCountDistinctForIntervals.totalNumWords(ApproxCountDistinctForIntervals.scala:106)
at
org.apache.spark.sql.catalyst.expressions.aggregate.ApproxCountDistinctForIntervals.createAggregationBuffer(ApproxCountDistinctForIntervals.scala:110)
at
org.apache.spark.sql.catalyst.expressions.aggregate.ApproxCountDistinctForIntervals.createAggregationBuffer(ApproxCountDistinctForIntervals.scala:44)
at
org.apache.spark.sql.catalyst.expressions.aggregate.TypedImperativeAggregate.initialize(interfaces.scala:528)
at
org.apache.spark.sql.execution.aggregate.ObjectAggregationIterator$$anonfun$initAggregationBuffer$2.apply(ObjectAggregationIterator.scala:120)
at
org.apache.spark.sql.execution.aggregate.ObjectAggregationIterator$$anonfun$initAggregationBuffer$2.apply(ObjectAggregationIterator.scala:120)
at
scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:186)
at
org.apache.spark.sql.execution.aggregate.ObjectAggregationIterator.initAggregationBuffer(ObjectAggregationIterator.scala:120)
at
org.apache.spark.sql.execution.aggregate.ObjectAggregationIterator.org$apache$spark$sql$execution$aggregate$ObjectAggregationIterator$$createNewAggregationBuffer(ObjectAggregationIterator.scala:112)
at
org.apache.spark.sql.execution.aggregate.ObjectAggregationIterator.getAggregationBufferByKey(ObjectAggregationIterator.scala:128)
at
org.apache.spark.sql.execution.aggregate.ObjectAggregationIterator.processInputs(ObjectAggregationIterator.scala:150)
at
org.apache.spark.sql.execution.aggregate.ObjectAggregationIterator.<init>(ObjectAggregationIterator.scala:78)
at
org.apache.spark.sql.execution.aggregate.ObjectHashAggregateExec$$anonfun$doExecute$1$$anonfun$2.apply(ObjectHashAggregateExec.scala:114)
at
org.apache.spark.sql.execution.aggregate.ObjectHashAggregateExec$$anonfun$doExecute$1$$anonfun$2.apply(ObjectHashAggregateExec.scala:105)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndexInternal$1$$anonfun$12.apply(RDD.scala:823)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndexInternal$1$$anonfun$12.apply(RDD.scala:823)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:55)
at org.apache.spark.scheduler.Task.run(Task.scala:121)
ApproxCountDistinctForIntervals holds the UnsafeArrayData data to initialize
endpoints. When the UnsafeArrayData is serialized with Java serialization, the
BYTE_ARRAY_OFFSET in memory can change if two machines have different pointer
width (Oops in JVM).
It's similar to SPARK-10914.
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