[
https://issues.apache.org/jira/browse/HIVE-16823?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16136156#comment-16136156
]
liyunzhang_intel edited comment on HIVE-16823 at 8/22/17 2:16 AM:
------------------------------------------------------------------
some updates about the jira.
The root cause of the problem is because the difference of sub-query {{select
ds as ds, ds as `date` from srcpart group by ds}} between tez and spark mode.
the spark explain(the full spark explain is attached in
[here|https://issues.apache.org/jira/secure/attachment/12883036/explain.spark] )
{code}
Map 3
Map Operator Tree:
TableScan
alias: srcpart
filterExpr: (ds = '2008-04-08') (type: boolean)
Statistics: Num rows: 1 Data size: 11624 Basic stats: PARTIAL
Column stats: NONE
Select Operator
Statistics: Num rows: 1 Data size: 11624 Basic stats:
PARTIAL Column stats: NONE
Group By Operator
keys: '2008-04-08' (type: string)
mode: hash
outputColumnNames: _col0
Statistics: Num rows: 1 Data size: 11624 Basic stats:
COMPLETE Column stats: NONE
Reduce Output Operator
key expressions: '2008-04-08' (type: string)
sort order: +
Map-reduce partition columns: '2008-04-08' (type:
string)
Statistics: Num rows: 1 Data size: 11624 Basic stats:
COMPLETE Column stats: NONE
Reducer 4
Local Work:
Map Reduce Local Work
Reduce Operator Tree:
Group By Operator
keys: '2008-04-08' (type: string)
mode: mergepartial
outputColumnNames: _col0
Statistics: Num rows: 1 Data size: 11624 Basic stats: COMPLETE
Column stats: NONE
{code}
the tez explain(the full tez explain is attached in
[here|https://issues.apache.org/jira/secure/attachment/12883035/explain.tez] )
{code}
Map 2
Map Operator Tree:
TableScan
alias: srcpart
filterExpr: (ds = '2008-04-08') (type: boolean)
Statistics: Num rows: 1 Data size: 11624 Basic stats: PARTIAL
Column stats: NONE
Select Operator
Statistics: Num rows: 1 Data size: 11624 Basic stats:
PARTIAL Column stats: NONE
Group By Operator
keys: '2008-04-08' (type: string)
mode: hash
outputColumnNames: _col0
Statistics: Num rows: 1 Data size: 11624 Basic stats:
COMPLETE Column stats: NONE
Reduce Output Operator
key expressions: _col0 (type: string)
sort order: +
Map-reduce partition columns: _col0 (type: string)
Statistics: Num rows: 1 Data size: 11624 Basic stats:
COMPLETE Column stats: NONE
Execution mode: vectorized
Reducer 3
Execution mode: vectorized
Reduce Operator Tree:
Group By Operator
keys: KEY._col0 (type: string)
mode: mergepartial
outputColumnNames: _col0
{code}
The Group By Operator appears in Map and Reducer in tez or spark mode. But the
keys of GroupByOperator in Reducer is different. In tez, the key is {{keys:
KEY._col0 (type: string)}} while in spark the key is {{keys: '2008-04-08'
(type: string)}}. This difference causes
[VectorizationContext#getVectorExpression|https://github.com/kellyzly/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/exec/vector/VectorizationContext.java#L579
] returns
[getColumnVectorExpression|https://github.com/kellyzly/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/exec/vector/VectorizationContext.java#L582]
in tez mode while returns
[getConstantVectorExpression|https://github.com/kellyzly/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/exec/vector/VectorizationContext.java#L660].
was (Author: kellyzly):
some updates about the jira.
The root cause of the problem is because the difference of sub-query {{select
ds as ds, ds as `date` from srcpart group by ds}} between tez and spark mode.
the spark explain(the full spark explain is attached in
[here|https://issues.apache.org/jira/secure/attachment/12883036/explain.spark] )
{code}
Map 3
Map Operator Tree:
TableScan
alias: srcpart
filterExpr: (ds = '2008-04-08') (type: boolean)
Statistics: Num rows: 1 Data size: 11624 Basic stats: PARTIAL
Column stats: NONE
Select Operator
Statistics: Num rows: 1 Data size: 11624 Basic stats:
PARTIAL Column stats: NONE
Group By Operator
keys: '2008-04-08' (type: string)
mode: hash
outputColumnNames: _col0
Statistics: Num rows: 1 Data size: 11624 Basic stats:
COMPLETE Column stats: NONE
Reduce Output Operator
key expressions: '2008-04-08' (type: string)
sort order: +
Map-reduce partition columns: '2008-04-08' (type:
string)
Statistics: Num rows: 1 Data size: 11624 Basic stats:
COMPLETE Column stats: NONE
Reducer 4
Local Work:
Map Reduce Local Work
Reduce Operator Tree:
Group By Operator
keys: '2008-04-08' (type: string)
mode: mergepartial
outputColumnNames: _col0
Statistics: Num rows: 1 Data size: 11624 Basic stats: COMPLETE
Column stats: NONE
{code}
the tez explain(the full tez explain is attached in
[here|https://issues.apache.org/jira/secure/attachment/12883035/explain.tez] )
{code}
Map 2
Map Operator Tree:
TableScan
alias: srcpart
filterExpr: (ds = '2008-04-08') (type: boolean)
Statistics: Num rows: 1 Data size: 11624 Basic stats: PARTIAL
Column stats: NONE
Select Operator
Statistics: Num rows: 1 Data size: 11624 Basic stats:
PARTIAL Column stats: NONE
Group By Operator
keys: '2008-04-08' (type: string)
mode: hash
outputColumnNames: _col0
Statistics: Num rows: 1 Data size: 11624 Basic stats:
COMPLETE Column stats: NONE
Reduce Output Operator
key expressions: _col0 (type: string)
sort order: +
Map-reduce partition columns: _col0 (type: string)
Statistics: Num rows: 1 Data size: 11624 Basic stats:
COMPLETE Column stats: NONE
Execution mode: vectorized
Reducer 3
Execution mode: vectorized
Reduce Operator Tree:
Group By Operator
keys: KEY._col0 (type: string)
mode: mergepartial
outputColumnNames: _col0
{code}
The Group By Operator appears in Map and Reducer in tez or spark mode. But the
keys of GroupByOperator in Reducer is different. In tez, the key is {{keys:
KEY._col0 (type: string)}} while in spark the key is {{keys: '2008-04-08'
(type: string)}}. This difference causes
[VectorizationContext#getVectorExpression|https://github.com/kellyzly/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/exec/vector/VectorizationContext.java#L597
] returns
[getColumnVectorExpression|https://github.com/kellyzly/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/exec/vector/VectorizationContext.java#L582]
in tez mode while returns
[getConstantVectorExpression|https://github.com/kellyzly/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/exec/vector/VectorizationContext.java#L660].
> "ArrayIndexOutOfBoundsException" in
> spark_vectorized_dynamic_partition_pruning.q
> --------------------------------------------------------------------------------
>
> Key: HIVE-16823
> URL: https://issues.apache.org/jira/browse/HIVE-16823
> Project: Hive
> Issue Type: Bug
> Reporter: Jianguo Tian
> Assignee: liyunzhang_intel
> Attachments: explain.spark, explain.tez
>
>
> spark_vectorized_dynamic_partition_pruning.q
> {code}
> set hive.optimize.ppd=true;
> set hive.ppd.remove.duplicatefilters=true;
> set hive.spark.dynamic.partition.pruning=true;
> set hive.optimize.metadataonly=false;
> set hive.optimize.index.filter=true;
> set hive.vectorized.execution.enabled=true;
> set hive.strict.checks.cartesian.product=false;
> -- parent is reduce tasks
> select count(*) from srcpart join (select ds as ds, ds as `date` from srcpart
> group by ds) s on (srcpart.ds = s.ds) where s.`date` = '2008-04-08';
> {code}
> The exceptions are as follows:
> {code}
> 2017-06-05T09:20:31,468 ERROR [Executor task launch worker-0]
> spark.SparkReduceRecordHandler: Fatal error:
> org.apache.hadoop.hive.ql.metadata.HiveException: Error while processing
> vector batch (tag=0) Column vector types: 0:BYTES, 1:BYTES
> ["2008-04-08", "2008-04-08"]
> org.apache.hadoop.hive.ql.metadata.HiveException: Error while processing
> vector batch (tag=0) Column vector types: 0:BYTES, 1:BYTES
> ["2008-04-08", "2008-04-08"]
> at
> org.apache.hadoop.hive.ql.exec.spark.SparkReduceRecordHandler.processVectors(SparkReduceRecordHandler.java:413)
> ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
> at
> org.apache.hadoop.hive.ql.exec.spark.SparkReduceRecordHandler.processRow(SparkReduceRecordHandler.java:301)
> ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
> at
> org.apache.hadoop.hive.ql.exec.spark.HiveReduceFunctionResultList.processNextRecord(HiveReduceFunctionResultList.java:54)
> ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
> at
> org.apache.hadoop.hive.ql.exec.spark.HiveReduceFunctionResultList.processNextRecord(HiveReduceFunctionResultList.java:28)
> ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
> at
> org.apache.hadoop.hive.ql.exec.spark.HiveBaseFunctionResultList.hasNext(HiveBaseFunctionResultList.java:85)
> ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
> at
> scala.collection.convert.Wrappers$JIteratorWrapper.hasNext(Wrappers.scala:42)
> ~[scala-library-2.11.8.jar:?]
> at scala.collection.Iterator$class.foreach(Iterator.scala:893)
> ~[scala-library-2.11.8.jar:?]
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
> ~[scala-library-2.11.8.jar:?]
> at
> org.apache.spark.rdd.AsyncRDDActions$$anonfun$foreachAsync$1$$anonfun$apply$12.apply(AsyncRDDActions.scala:127)
> ~[spark-core_2.11-2.0.0.jar:2.0.0]
> at
> org.apache.spark.rdd.AsyncRDDActions$$anonfun$foreachAsync$1$$anonfun$apply$12.apply(AsyncRDDActions.scala:127)
> ~[spark-core_2.11-2.0.0.jar:2.0.0]
> at
> org.apache.spark.SparkContext$$anonfun$33.apply(SparkContext.scala:1974)
> ~[spark-core_2.11-2.0.0.jar:2.0.0]
> at
> org.apache.spark.SparkContext$$anonfun$33.apply(SparkContext.scala:1974)
> ~[spark-core_2.11-2.0.0.jar:2.0.0]
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
> ~[spark-core_2.11-2.0.0.jar:2.0.0]
> at org.apache.spark.scheduler.Task.run(Task.scala:85)
> ~[spark-core_2.11-2.0.0.jar:2.0.0]
> at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
> ~[spark-core_2.11-2.0.0.jar:2.0.0]
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> [?:1.8.0_112]
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> [?:1.8.0_112]
> at java.lang.Thread.run(Thread.java:745) [?:1.8.0_112]
> Caused by: java.lang.ArrayIndexOutOfBoundsException: 1
> at
> org.apache.hadoop.hive.ql.exec.vector.VectorGroupKeyHelper.copyGroupKey(VectorGroupKeyHelper.java:107)
> ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
> at
> org.apache.hadoop.hive.ql.exec.vector.VectorGroupByOperator$ProcessingModeReduceMergePartial.doProcessBatch(VectorGroupByOperator.java:832)
> ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
> at
> org.apache.hadoop.hive.ql.exec.vector.VectorGroupByOperator$ProcessingModeBase.processBatch(VectorGroupByOperator.java:179)
> ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
> at
> org.apache.hadoop.hive.ql.exec.vector.VectorGroupByOperator.process(VectorGroupByOperator.java:1035)
> ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
> at
> org.apache.hadoop.hive.ql.exec.spark.SparkReduceRecordHandler.processVectors(SparkReduceRecordHandler.java:400)
> ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
> ... 17 more
> 2017-06-05T09:20:31,472 ERROR [Executor task launch worker-0]
> executor.Executor: Exception in task 2.0 in stage 1.0 (TID 8)
> java.lang.RuntimeException: org.apache.hadoop.hive.ql.metadata.HiveException:
> Error while processing vector batch (tag=0) Column vector types: 0:BYTES,
> 1:BYTES
> ["2008-04-08", "2008-04-08"]
> at
> org.apache.hadoop.hive.ql.exec.spark.SparkReduceRecordHandler.processRow(SparkReduceRecordHandler.java:315)
> ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
> at
> org.apache.hadoop.hive.ql.exec.spark.HiveReduceFunctionResultList.processNextRecord(HiveReduceFunctionResultList.java:54)
> ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
> at
> org.apache.hadoop.hive.ql.exec.spark.HiveReduceFunctionResultList.processNextRecord(HiveReduceFunctionResultList.java:28)
> ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
> at
> org.apache.hadoop.hive.ql.exec.spark.HiveBaseFunctionResultList.hasNext(HiveBaseFunctionResultList.java:85)
> ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
> at
> scala.collection.convert.Wrappers$JIteratorWrapper.hasNext(Wrappers.scala:42)
> ~[scala-library-2.11.8.jar:?]
> at scala.collection.Iterator$class.foreach(Iterator.scala:893)
> ~[scala-library-2.11.8.jar:?]
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
> ~[scala-library-2.11.8.jar:?]
> at
> org.apache.spark.rdd.AsyncRDDActions$$anonfun$foreachAsync$1$$anonfun$apply$12.apply(AsyncRDDActions.scala:127)
> ~[spark-core_2.11-2.0.0.jar:2.0.0]
> at
> org.apache.spark.rdd.AsyncRDDActions$$anonfun$foreachAsync$1$$anonfun$apply$12.apply(AsyncRDDActions.scala:127)
> ~[spark-core_2.11-2.0.0.jar:2.0.0]
> at
> org.apache.spark.SparkContext$$anonfun$33.apply(SparkContext.scala:1974)
> ~[spark-core_2.11-2.0.0.jar:2.0.0]
> at
> org.apache.spark.SparkContext$$anonfun$33.apply(SparkContext.scala:1974)
> ~[spark-core_2.11-2.0.0.jar:2.0.0]
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
> ~[spark-core_2.11-2.0.0.jar:2.0.0]
> at org.apache.spark.scheduler.Task.run(Task.scala:85)
> ~[spark-core_2.11-2.0.0.jar:2.0.0]
> at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
> ~[spark-core_2.11-2.0.0.jar:2.0.0]
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> [?:1.8.0_112]
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> [?:1.8.0_112]
> at java.lang.Thread.run(Thread.java:745) [?:1.8.0_112]
> Caused by: org.apache.hadoop.hive.ql.metadata.HiveException: Error while
> processing vector batch (tag=0) Column vector types: 0:BYTES, 1:BYTES
> ["2008-04-08", "2008-04-08"]
> at
> org.apache.hadoop.hive.ql.exec.spark.SparkReduceRecordHandler.processVectors(SparkReduceRecordHandler.java:413)
> ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
> at
> org.apache.hadoop.hive.ql.exec.spark.SparkReduceRecordHandler.processRow(SparkReduceRecordHandler.java:301)
> ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
> ... 16 more
> Caused by: java.lang.ArrayIndexOutOfBoundsException: 1
> at
> org.apache.hadoop.hive.ql.exec.vector.VectorGroupKeyHelper.copyGroupKey(VectorGroupKeyHelper.java:107)
> ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
> at
> org.apache.hadoop.hive.ql.exec.vector.VectorGroupByOperator$ProcessingModeReduceMergePartial.doProcessBatch(VectorGroupByOperator.java:832)
> ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
> at
> org.apache.hadoop.hive.ql.exec.vector.VectorGroupByOperator$ProcessingModeBase.processBatch(VectorGroupByOperator.java:179)
> ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
> at
> org.apache.hadoop.hive.ql.exec.vector.VectorGroupByOperator.process(VectorGroupByOperator.java:1035)
> ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
> at
> org.apache.hadoop.hive.ql.exec.spark.SparkReduceRecordHandler.processVectors(SparkReduceRecordHandler.java:400)
> ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
> at
> org.apache.hadoop.hive.ql.exec.spark.SparkReduceRecordHandler.processRow(SparkReduceRecordHandler.java:301)
> ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
> ... 16 more
> 2017-06-05T09:20:31,488 DEBUG [dispatcher-event-loop-2]
> scheduler.TaskSchedulerImpl: parentName: , name: TaskSet_1, runningTasks: 0
> 2017-06-05T09:20:31,493 WARN [task-result-getter-0]
> scheduler.TaskSetManager: Lost task 2.0 in stage 1.0 (TID 8, localhost):
> java.lang.RuntimeException: org.apache.hadoop.hive.ql.metadata.HiveException:
> Error while processing vector batch (tag=0) Column vector types: 0:BYTES,
> 1:BYTES
> ["2008-04-08", "2008-04-08"]
> at
> org.apache.hadoop.hive.ql.exec.spark.SparkReduceRecordHandler.processRow(SparkReduceRecordHandler.java:315)
> at
> org.apache.hadoop.hive.ql.exec.spark.HiveReduceFunctionResultList.processNextRecord(HiveReduceFunctionResultList.java:54)
> at
> org.apache.hadoop.hive.ql.exec.spark.HiveReduceFunctionResultList.processNextRecord(HiveReduceFunctionResultList.java:28)
> at
> org.apache.hadoop.hive.ql.exec.spark.HiveBaseFunctionResultList.hasNext(HiveBaseFunctionResultList.java:85)
> at
> scala.collection.convert.Wrappers$JIteratorWrapper.hasNext(Wrappers.scala:42)
> at scala.collection.Iterator$class.foreach(Iterator.scala:893)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
> at
> org.apache.spark.rdd.AsyncRDDActions$$anonfun$foreachAsync$1$$anonfun$apply$12.apply(AsyncRDDActions.scala:127)
> at
> org.apache.spark.rdd.AsyncRDDActions$$anonfun$foreachAsync$1$$anonfun$apply$12.apply(AsyncRDDActions.scala:127)
> at
> org.apache.spark.SparkContext$$anonfun$33.apply(SparkContext.scala:1974)
> at
> org.apache.spark.SparkContext$$anonfun$33.apply(SparkContext.scala:1974)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
> at org.apache.spark.scheduler.Task.run(Task.scala:85)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> Caused by: org.apache.hadoop.hive.ql.metadata.HiveException: Error while
> processing vector batch (tag=0) Column vector types: 0:BYTES, 1:BYTES
> ["2008-04-08", "2008-04-08"]
> at
> org.apache.hadoop.hive.ql.exec.spark.SparkReduceRecordHandler.processVectors(SparkReduceRecordHandler.java:413)
> at
> org.apache.hadoop.hive.ql.exec.spark.SparkReduceRecordHandler.processRow(SparkReduceRecordHandler.java:301)
> ... 16 more
> Caused by: java.lang.ArrayIndexOutOfBoundsException: 1
> at
> org.apache.hadoop.hive.ql.exec.vector.VectorGroupKeyHelper.copyGroupKey(VectorGroupKeyHelper.java:107)
> at
> org.apache.hadoop.hive.ql.exec.vector.VectorGroupByOperator$ProcessingModeReduceMergePartial.doProcessBatch(VectorGroupByOperator.java:832)
> at
> org.apache.hadoop.hive.ql.exec.vector.VectorGroupByOperator$ProcessingModeBase.processBatch(VectorGroupByOperator.java:179)
> at
> org.apache.hadoop.hive.ql.exec.vector.VectorGroupByOperator.process(VectorGroupByOperator.java:1035)
> at
> org.apache.hadoop.hive.ql.exec.spark.SparkReduceRecordHandler.processVectors(SparkReduceRecordHandler.java:400)
> ... 17 more
> 2017-06-05T09:20:31,495 ERROR [task-result-getter-0]
> scheduler.TaskSetManager: Task 2 in stage 1.0 failed 1 times; aborting job
> {code}
> This exception happens in this line of VectorGroupKeyHelper.java:
> {code}
> BytesColumnVector outputColumnVector = (BytesColumnVector)
> outputBatch.cols[columnIndex];
> {code}
--
This message was sent by Atlassian JIRA
(v6.4.14#64029)
