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https://issues.apache.org/jira/browse/HIVE-21935?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Richard Zhang reassigned HIVE-21935:
------------------------------------
Assignee: Richard Zhang (was: Mustafa Iman)
> Hive Vectorization : degraded performance with vectorize UDF
> --------------------------------------------------------------
>
> Key: HIVE-21935
> URL: https://issues.apache.org/jira/browse/HIVE-21935
> Project: Hive
> Issue Type: Bug
> Components: Vectorization
> Affects Versions: 3.1.1
> Environment: Hive-3, JDK-8
> Reporter: Rajkumar Singh
> Assignee: Richard Zhang
> Priority: Major
> Labels: performance
> Attachments: CustomSplit-1.0-SNAPSHOT.jar
>
>
> with vectorization turned on and hive.vectorized.adaptor.usage.mode=all we
> were seeing severe performance degradation. looking at the task jstacks it
> seems that it is running the code which vectorizes UDF and stuck in some loop.
> {code:java}
> jstack -l 14954 | grep 0x3af0 -A20
> "TezChild" #15 daemon prio=5 os_prio=0 tid=0x00007f157538d800 nid=0x3af0
> runnable [0x00007f1547581000]
> java.lang.Thread.State: RUNNABLE
> at
> org.apache.hadoop.hive.ql.exec.vector.VectorAssignRow.assignRowColumn(VectorAssignRow.java:573)
> at
> org.apache.hadoop.hive.ql.exec.vector.VectorAssignRow.assignRowColumn(VectorAssignRow.java:350)
> at
> org.apache.hadoop.hive.ql.exec.vector.udf.VectorUDFAdaptor.setResult(VectorUDFAdaptor.java:205)
> at
> org.apache.hadoop.hive.ql.exec.vector.udf.VectorUDFAdaptor.evaluate(VectorUDFAdaptor.java:150)
> at
> org.apache.hadoop.hive.ql.exec.vector.expressions.VectorExpression.evaluateChildren(VectorExpression.java:271)
> at
> org.apache.hadoop.hive.ql.exec.vector.expressions.ListIndexColScalar.evaluate(ListIndexColScalar.java:59)
> at
> org.apache.hadoop.hive.ql.exec.vector.VectorSelectOperator.process(VectorSelectOperator.java:146)
> at
> org.apache.hadoop.hive.ql.exec.Operator.vectorForward(Operator.java:965)
> at org.apache.hadoop.hive.ql.exec.Operator.forward(Operator.java:938)
> at
> org.apache.hadoop.hive.ql.exec.TableScanOperator.process(TableScanOperator.java:125)
> at
> org.apache.hadoop.hive.ql.exec.vector.VectorMapOperator.process(VectorMapOperator.java:889)
> at
> org.apache.hadoop.hive.ql.exec.tez.MapRecordSource.processRow(MapRecordSource.java:92)
> at
> org.apache.hadoop.hive.ql.exec.tez.MapRecordSource.pushRecord(MapRecordSource.java:76)
> at
> org.apache.hadoop.hive.ql.exec.tez.MapRecordProcessor.run(MapRecordProcessor.java:426)
> at
> org.apache.hadoop.hive.ql.exec.tez.TezProcessor.initializeAndRunProcessor(TezProcessor.java:267)
> at
> org.apache.hadoop.hive.ql.exec.tez.TezProcessor.run(TezProcessor.java:250)
> at
> org.apache.tez.runtime.LogicalIOProcessorRuntimeTask.run(LogicalIOProcessorRuntimeTask.java:374)
> at
> org.apache.tez.runtime.task.TaskRunner2Callable$1.run(TaskRunner2Callable.java:73)
> at
> org.apache.tez.runtime.task.TaskRunner2Callable$1.run(TaskRunner2Callable.java:61)
> [yarn@hdp32b ~]$ jstack -l 14954 | grep 0x3af0 -A20
> "TezChild" #15 daemon prio=5 os_prio=0 tid=0x00007f157538d800 nid=0x3af0
> runnable [0x00007f1547581000]
> java.lang.Thread.State: RUNNABLE
> at
> org.apache.hadoop.hive.ql.exec.vector.BytesColumnVector.ensureSize(BytesColumnVector.java:554)
> at
> org.apache.hadoop.hive.ql.exec.vector.VectorAssignRow.assignRowColumn(VectorAssignRow.java:570)
> at
> org.apache.hadoop.hive.ql.exec.vector.VectorAssignRow.assignRowColumn(VectorAssignRow.java:350)
> at
> org.apache.hadoop.hive.ql.exec.vector.udf.VectorUDFAdaptor.setResult(VectorUDFAdaptor.java:205)
> at
> org.apache.hadoop.hive.ql.exec.vector.udf.VectorUDFAdaptor.evaluate(VectorUDFAdaptor.java:150)
> at
> org.apache.hadoop.hive.ql.exec.vector.expressions.VectorExpression.evaluateChildren(VectorExpression.java:271)
> at
> org.apache.hadoop.hive.ql.exec.vector.expressions.ListIndexColScalar.evaluate(ListIndexColScalar.java:59)
> at
> org.apache.hadoop.hive.ql.exec.vector.VectorSelectOperator.process(VectorSelectOperator.java:146)
> at
> org.apache.hadoop.hive.ql.exec.Operator.vectorForward(Operator.java:965)
> at org.apache.hadoop.hive.ql.exec.Operator.forward(Operator.java:938)
> at
> org.apache.hadoop.hive.ql.exec.TableScanOperator.process(TableScanOperator.java:125)
> at
> org.apache.hadoop.hive.ql.exec.vector.VectorMapOperator.process(VectorMapOperator.java:889)
> at
> org.apache.hadoop.hive.ql.exec.tez.MapRecordSource.processRow(MapRecordSource.java:92)
> at
> org.apache.hadoop.hive.ql.exec.tez.MapRecordSource.pushRecord(MapRecordSource.java:76)
> at
> org.apache.hadoop.hive.ql.exec.tez.MapRecordProcessor.run(MapRecordProcessor.java:426)
> at
> org.apache.hadoop.hive.ql.exec.tez.TezProcessor.initializeAndRunProcessor(TezProcessor.java:267)
> at
> org.apache.hadoop.hive.ql.exec.tez.TezProcessor.run(TezProcessor.java:250)
> at
> org.apache.tez.runtime.LogicalIOProcessorRuntimeTask.run(LogicalIOProcessorRuntimeTask.java:374)
> at
> org.apache.tez.runtime.task.TaskRunner2Callable$1.run(TaskRunner2Callable.java:73)
> {code}
> after setting the hive.vectorized.adaptor.usage.mode=none query did complete
> much faster.
> Steps To Reproduce:
> 1. Create Table:
> {code}
> +----------------------------------------------------+
> | createtab_stmt |
> +----------------------------------------------------+
> | CREATE EXTERNAL TABLE `splittestloc`( |
> | `id` int, |
> | `value` string) |
> | ROW FORMAT SERDE |
> | 'org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe' |
> | WITH SERDEPROPERTIES ( |
> | 'field.delim'=',', |
> | 'serialization.format'=',') |
> | STORED AS INPUTFORMAT |
> | 'org.apache.hadoop.mapred.TextInputFormat' |
> | OUTPUTFORMAT |
> | 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat' |
> | LOCATION |
> | 'hdfs://hdp31a.hdp.local:8020/tmp/splittableloc' |
> | TBLPROPERTIES ( |
> | 'bucketing_version'='2', |
> | 'transient_lastDdlTime'='1561482451') |
> +----------------------------------------------------+
> {code}
> 2. Sample data: table has some 40M rows and sample data is generated using
> following script.
> {code}
> for i in {1..40000000} ; do echo $i,"start#mid#"$i >> data.log ; done
> {code}
> 3. I believe this should be reproducible with hive generic split but I am
> attaching the custom UDF to split the string.
> 4. create a function
> {code}
> add jar /tmp/CustomSplit-1.0-SNAPSHOT.jar;
> create temporary function mysplit as 'com.rajkrrsingh.split.test.CustomSplit'
> {code}
> 5. run the following query which will reproduce the issue if vectorization
> turned on.
> {code}
> create temporary table tmp2 as select id,mysplit(value,"#")[2] from
> splittestloc
> {code}
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