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Sean Owen commented on SPARK-16802: ----------------------------------- Do you have a particular fix that addressed it [~wm624]? which version did you reproduce it on, and where is it working? > joins.LongToUnsafeRowMap crashes with ArrayIndexOutOfBoundsException > -------------------------------------------------------------------- > > Key: SPARK-16802 > URL: https://issues.apache.org/jira/browse/SPARK-16802 > Project: Spark > Issue Type: Bug > Components: SQL > Affects Versions: 2.0.0 > Reporter: Sylvain Zimmer > Assignee: Davies Liu > Priority: Critical > > Hello! > This is a little similar to > [SPARK-16740|https://issues.apache.org/jira/browse/SPARK-16740] (should I > have reopened it?). > I would recommend to give another full review to {{HashedRelation.scala}}, > particularly the new {{LongToUnsafeRowMap}} code. I've had a few other errors > that I haven't managed to reproduce so far, as well as what I suspect could > be memory leaks (I have a query in a loop OOMing after a few iterations > despite not caching its results). > Here is the script to reproduce the ArrayIndexOutOfBoundsException on the > current 2.0 branch: > {code} > import os > import random > from pyspark import SparkContext > from pyspark.sql import types as SparkTypes > from pyspark.sql import SQLContext > sc = SparkContext() > sqlc = SQLContext(sc) > schema1 = SparkTypes.StructType([ > SparkTypes.StructField("id1", SparkTypes.LongType(), nullable=True) > ]) > schema2 = SparkTypes.StructType([ > SparkTypes.StructField("id2", SparkTypes.LongType(), nullable=True) > ]) > def randlong(): > return random.randint(-9223372036854775808, 9223372036854775807) > while True: > l1, l2 = randlong(), randlong() > # Sample values that crash: > # l1, l2 = 4661454128115150227, -5543241376386463808 > print "Testing with %s, %s" % (l1, l2) > data1 = [(l1, ), (l2, )] > data2 = [(l1, )] > df1 = sqlc.createDataFrame(sc.parallelize(data1), schema1) > df2 = sqlc.createDataFrame(sc.parallelize(data2), schema2) > crash = True > if crash: > os.system("rm -rf /tmp/sparkbug") > df1.write.parquet("/tmp/sparkbug/vertex") > df2.write.parquet("/tmp/sparkbug/edge") > df1 = sqlc.read.load("/tmp/sparkbug/vertex") > df2 = sqlc.read.load("/tmp/sparkbug/edge") > sqlc.registerDataFrameAsTable(df1, "df1") > sqlc.registerDataFrameAsTable(df2, "df2") > result_df = sqlc.sql(""" > SELECT > df1.id1 > FROM df1 > LEFT OUTER JOIN df2 ON df1.id1 = df2.id2 > """) > print result_df.collect() > {code} > {code} > java.lang.ArrayIndexOutOfBoundsException: 1728150825 > at > org.apache.spark.sql.execution.joins.LongToUnsafeRowMap.getValue(HashedRelation.scala:463) > at > org.apache.spark.sql.execution.joins.LongHashedRelation.getValue(HashedRelation.scala:762) > 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$$anon$11.hasNext(Iterator.scala:408) > at > org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.hasNext(SerDeUtil.scala:117) > at scala.collection.Iterator$class.foreach(Iterator.scala:893) > at > org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.foreach(SerDeUtil.scala:112) > at > scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59) > at > scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104) > at > scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48) > at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310) > at > org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.to(SerDeUtil.scala:112) > at > scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302) > at > org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.toBuffer(SerDeUtil.scala:112) > at > scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289) > at > org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.toArray(SerDeUtil.scala:112) > at > org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$13.apply(RDD.scala:899) > at > org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$13.apply(RDD.scala:899) > at > org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1898) > at > org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1898) > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70) > at org.apache.spark.scheduler.Task.run(Task.scala:85) > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274) > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) > at java.lang.Thread.run(Thread.java:745) > 16/07/29 20:19:00 WARN TaskSetManager: Lost task 0.0 in stage 17.0 (TID 50, > localhost): java.lang.ArrayIndexOutOfBoundsException: 1728150825 > at > org.apache.spark.sql.execution.joins.LongToUnsafeRowMap.getValue(HashedRelation.scala:463) > at > org.apache.spark.sql.execution.joins.LongHashedRelation.getValue(HashedRelation.scala:762) > at > org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown > Source) > at > org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) > at > org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370) > at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408) > at > org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.hasNext(SerDeUtil.scala:117) > at scala.collection.Iterator$class.foreach(Iterator.scala:893) > at > org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.foreach(SerDeUtil.scala:112) > at > scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59) > at > scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104) > at > scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48) > at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310) > at > org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.to(SerDeUtil.scala:112) > at > scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302) > at > org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.toBuffer(SerDeUtil.scala:112) > at > scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289) > at > org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.toArray(SerDeUtil.scala:112) > at > org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$13.apply(RDD.scala:899) > at > org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$13.apply(RDD.scala:899) > at > org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1898) > at > org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1898) > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70) > at org.apache.spark.scheduler.Task.run(Task.scala:85) > at org.apache.spark.executor.Executor$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) > {code} -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org