[
https://issues.apache.org/jira/browse/HIVE-16780?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16036670#comment-16036670
]
liyunzhang_intel commented on HIVE-16780:
-----------------------------------------
[~csun]: case "multiple sources, single key" pass if
hive.tez.dynamic.semijoin.reduction is false.
bq.Maybe we should first disable this optimization for Spark in
DynamicPartitionPruningOptimization
agree, update HIVE-16780.1.patch.
the explain when enabling hive.tez.dynamic.semijoin.reduction
{noformat}
TAGE DEPENDENCIES:
Stage-2 is a root stage
Stage-3 depends on stages: Stage-2
Stage-1 depends on stages: Stage-3
Stage-0 depends on stages: Stage-1
STAGE PLANS:
Stage: Stage-2
Spark
DagName: root_20170605152828_4c4f4f82-d08f-41e9-9a07-4147b8529dd0:2
Vertices:
Map 4
Map Operator Tree:
TableScan
alias: srcpart_date
filterExpr: ds is not null (type: boolean)
Statistics: Num rows: 2 Data size: 42 Basic stats: COMPLETE
Column stats: NONE
Filter Operator
predicate: ds is not null (type: boolean)
Statistics: Num rows: 2 Data size: 42 Basic stats: COMPLETE
Column stats: NONE
Spark HashTable Sink Operator
keys:
0 ds (type: string)
1 ds (type: string)
Select Operator
expressions: ds (type: string)
outputColumnNames: _col0
Statistics: Num rows: 2 Data size: 42 Basic stats:
COMPLETE Column stats: NONE
Group By Operator
keys: _col0 (type: string)
mode: hash
outputColumnNames: _col0
Statistics: Num rows: 2 Data size: 42 Basic stats:
COMPLETE Column stats: NONE
Spark Partition Pruning Sink Operator
partition key expr: ds
Statistics: Num rows: 2 Data size: 42 Basic stats:
COMPLETE Column stats: NONE
target column name: ds
target work: Map 1
Local Work:
Map Reduce Local Work
Map 5
Map Operator Tree:
TableScan
alias: srcpart_hour
filterExpr: (hr is not null and (hr BETWEEN
DynamicValue(RS_7_srcpart__col3_min) AND DynamicValue(RS_7_srcpart__col3_max)
and in_bloom_filter(hr, DynamicValue(RS_7_srcpart__col3_bloom_filter)))) (type:
boolean)
Statistics: Num rows: 2 Data size: 10 Basic stats: COMPLETE
Column stats: NONE
Filter Operator
predicate: (hr is not null and (hr BETWEEN
DynamicValue(RS_7_srcpart__col3_min) AND DynamicValue(RS_7_srcpart__col3_max)
and in_bloom_filter(hr, DynamicValue(RS_7_srcpart__col3_bloom_filter)))) (type:
boolean)
Statistics: Num rows: 2 Data size: 10 Basic stats: COMPLETE
Column stats: NONE
Spark HashTable Sink Operator
keys:
0 _col3 (type: string)
1 hr (type: string)
Select Operator
expressions: hr (type: string)
outputColumnNames: _col0
Statistics: Num rows: 2 Data size: 10 Basic stats:
COMPLETE Column stats: NONE
Group By Operator
keys: _col0 (type: string)
mode: hash
outputColumnNames: _col0
Statistics: Num rows: 2 Data size: 10 Basic stats:
COMPLETE Column stats: NONE
Spark Partition Pruning Sink Operator
partition key expr: hr
Statistics: Num rows: 2 Data size: 10 Basic stats:
COMPLETE Column stats: NONE
target column name: hr
target work: Map 1
Local Work:
Map Reduce Local Work
Stage: Stage-3
Spark
DagName: root_20170605152828_4c4f4f82-d08f-41e9-9a07-4147b8529dd0:3
Vertices:
Map 4
Map Operator Tree:
TableScan
alias: srcpart_date
filterExpr: ds is not null (type: boolean)
Statistics: Num rows: 2 Data size: 42 Basic stats: COMPLETE
Column stats: NONE
Filter Operator
predicate: ds is not null (type: boolean)
Statistics: Num rows: 2 Data size: 42 Basic stats: COMPLETE
Column stats: NONE
Spark HashTable Sink Operator
keys:
0 ds (type: string)
1 ds (type: string)
Select Operator
expressions: ds (type: string)
outputColumnNames: _col0
Statistics: Num rows: 2 Data size: 42 Basic stats:
COMPLETE Column stats: NONE
Group By Operator
keys: _col0 (type: string)
mode: hash
outputColumnNames: _col0
Statistics: Num rows: 2 Data size: 42 Basic stats:
COMPLETE Column stats: NONE
Spark Partition Pruning Sink Operator
partition key expr: ds
Statistics: Num rows: 2 Data size: 42 Basic stats:
COMPLETE Column stats: NONE
target column name: ds
target work: Map 1
Local Work:
Map Reduce Local Work
Map 5
Map Operator Tree:
TableScan
alias: srcpart_hour
filterExpr: (hr is not null and (hr BETWEEN
DynamicValue(RS_7_srcpart__col3_min) AND DynamicValue(RS_7_srcpart__col3_max)
and in_bloom_filter(hr, DynamicValue(RS_7_srcpart__col3_bloom_filter)))) (type:
boolean)
Statistics: Num rows: 2 Data size: 10 Basic stats: COMPLETE
Column stats: NONE
Filter Operator
predicate: (hr is not null and (hr BETWEEN
DynamicValue(RS_7_srcpart__col3_min) AND DynamicValue(RS_7_srcpart__col3_max)
and in_bloom_filter(hr, DynamicValue(RS_7_srcpart__col3_bloom_filter)))) (type:
boolean)
Statistics: Num rows: 2 Data size: 10 Basic stats: COMPLETE
Column stats: NONE
Spark HashTable Sink Operator
keys:
0 _col3 (type: string)
1 hr (type: string)
Select Operator
expressions: hr (type: string)
outputColumnNames: _col0
Statistics: Num rows: 2 Data size: 10 Basic stats:
COMPLETE Column stats: NONE
Group By Operator
keys: _col0 (type: string)
mode: hash
outputColumnNames: _col0
Statistics: Num rows: 2 Data size: 10 Basic stats:
COMPLETE Column stats: NONE
Spark Partition Pruning Sink Operator
partition key expr: hr
Statistics: Num rows: 2 Data size: 10 Basic stats:
COMPLETE Column stats: NONE
target column name: hr
target work: Map 1
Local Work:
Map Reduce Local Work
Stage: Stage-1
Spark
Edges:
Reducer 2 <- Map 6 (GROUP, 1)
Reducer 3 <- Map 7 (GROUP, 1)
DagName: root_20170605152828_4c4f4f82-d08f-41e9-9a07-4147b8529dd0:1
Vertices:
Map 6
Map Operator Tree:
TableScan
alias: srcpart
Statistics: Num rows: 1 Data size: 23248 Basic stats: PARTIAL
Column stats: NONE
Map Join Operator
condition map:
Inner Join 0 to 1
keys:
0 ds (type: string)
1 ds (type: string)
outputColumnNames: _col3
input vertices:
1 Map 4
Statistics: Num rows: 2 Data size: 46 Basic stats: COMPLETE
Column stats: NONE
Select Operator
expressions: _col3 (type: string)
outputColumnNames: _col0
Statistics: Num rows: 2 Data size: 46 Basic stats:
COMPLETE Column stats: NONE
Group By Operator
aggregations: min(_col0), max(_col0),
bloom_filter(_col0, expectedEntries=1000000)
mode: hash
outputColumnNames: _col0, _col1, _col2
Statistics: Num rows: 1 Data size: 552 Basic stats:
COMPLETE Column stats: NONE
Reduce Output Operator
sort order:
Statistics: Num rows: 1 Data size: 552 Basic stats:
COMPLETE Column stats: NONE
value expressions: _col0 (type: string), _col1 (type:
string), _col2 (type: binary)
Local Work:
Map Reduce Local Work
Map 7
Map Operator Tree:
TableScan
alias: srcpart
Statistics: Num rows: 1 Data size: 23248 Basic stats: PARTIAL
Column stats: NONE
Map Join Operator
condition map:
Inner Join 0 to 1
keys:
0 ds (type: string)
1 ds (type: string)
outputColumnNames: _col3
input vertices:
1 Map 4
Statistics: Num rows: 2 Data size: 46 Basic stats: COMPLETE
Column stats: NONE
Map Join Operator
condition map:
Inner Join 0 to 1
keys:
0 _col3 (type: string)
1 hr (type: string)
input vertices:
1 Map 5
Statistics: Num rows: 2 Data size: 50 Basic stats:
COMPLETE Column stats: NONE
Group By Operator
aggregations: count()
mode: hash
outputColumnNames: _col0
Statistics: Num rows: 1 Data size: 8 Basic stats:
COMPLETE Column stats: NONE
Reduce Output Operator
sort order:
Statistics: Num rows: 1 Data size: 8 Basic stats:
COMPLETE Column stats: NONE
value expressions: _col0 (type: bigint)
Local Work:
Map Reduce Local Work
Reducer 2
Reduce Operator Tree:
Group By Operator
aggregations: min(VALUE._col0), max(VALUE._col1),
bloom_filter(VALUE._col2, expectedEntries=1000000)
mode: final
outputColumnNames: _col0, _col1, _col2
Statistics: Num rows: 1 Data size: 552 Basic stats: COMPLETE
Column stats: NONE
Reduce Output Operator
sort order:
Statistics: Num rows: 1 Data size: 552 Basic stats: COMPLETE
Column stats: NONE
value expressions: _col0 (type: string), _col1 (type:
string), _col2 (type: binary)
Reducer 3
Reduce Operator Tree:
Group By Operator
aggregations: count(VALUE._col0)
mode: mergepartial
outputColumnNames: _col0
Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE
Column stats: NONE
File Output Operator
compressed: false
Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE
Column stats: NONE
table:
input format:
org.apache.hadoop.mapred.SequenceFileInputFormat
output format:
org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat
serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe
Stage: Stage-0
Fetch Operator
limit: -1
Processor Tree:
ListSink
{noformat}
the explain when disabling hive.tez.dynamic.semijoin.reduction
{noformat}
STAGE DEPENDENCIES:
Stage-2 is a root stage
Stage-1 depends on stages: Stage-2
Stage-0 depends on stages: Stage-1
STAGE PLANS:
Stage: Stage-2
Spark
DagName: root_20170605153113_6d0bbb45-8a4a-4b10-9b2c-4585abdf2a79:2
Vertices:
Map 3
Map Operator Tree:
TableScan
alias: srcpart_date
filterExpr: ds is not null (type: boolean)
Statistics: Num rows: 2 Data size: 42 Basic stats: COMPLETE
Column stats: NONE
Filter Operator
predicate: ds is not null (type: boolean)
Statistics: Num rows: 2 Data size: 42 Basic stats: COMPLETE
Column stats: NONE
Spark HashTable Sink Operator
keys:
0 ds (type: string)
1 ds (type: string)
Select Operator
expressions: ds (type: string)
outputColumnNames: _col0
Statistics: Num rows: 2 Data size: 42 Basic stats:
COMPLETE Column stats: NONE
Group By Operator
keys: _col0 (type: string)
mode: hash
outputColumnNames: _col0
Statistics: Num rows: 2 Data size: 42 Basic stats:
COMPLETE Column stats: NONE
Spark Partition Pruning Sink Operator
partition key expr: ds
Statistics: Num rows: 2 Data size: 42 Basic stats:
COMPLETE Column stats: NONE
target column name: ds
target work: Map 1
Local Work:
Map Reduce Local Work
Map 4
Map Operator Tree:
TableScan
alias: srcpart_hour
filterExpr: hr is not null (type: boolean)
Statistics: Num rows: 2 Data size: 10 Basic stats: COMPLETE
Column stats: NONE
Filter Operator
predicate: hr is not null (type: boolean)
Statistics: Num rows: 2 Data size: 10 Basic stats: COMPLETE
Column stats: NONE
Spark HashTable Sink Operator
keys:
0 _col3 (type: string)
1 hr (type: string)
Select Operator
expressions: hr (type: string)
outputColumnNames: _col0
Statistics: Num rows: 2 Data size: 10 Basic stats:
COMPLETE Column stats: NONE
Group By Operator
keys: _col0 (type: string)
mode: hash
outputColumnNames: _col0
Statistics: Num rows: 2 Data size: 10 Basic stats:
COMPLETE Column stats: NONE
Spark Partition Pruning Sink Operator
partition key expr: hr
Statistics: Num rows: 2 Data size: 10 Basic stats:
COMPLETE Column stats: NONE
target column name: hr
target work: Map 1
Local Work:
Map Reduce Local Work
Stage: Stage-1
Spark
Edges:
Reducer 2 <- Map 1 (GROUP, 1)
DagName: root_20170605153113_6d0bbb45-8a4a-4b10-9b2c-4585abdf2a79:1
Vertices:
Map 1
Map Operator Tree:
TableScan
alias: srcpart
Statistics: Num rows: 1 Data size: 23248 Basic stats: PARTIAL
Column stats: NONE
Map Join Operator
condition map:
Inner Join 0 to 1
keys:
0 ds (type: string)
1 ds (type: string)
outputColumnNames: _col3
input vertices:
1 Map 3
Statistics: Num rows: 2 Data size: 46 Basic stats: COMPLETE
Column stats: NONE
Map Join Operator
condition map:
Inner Join 0 to 1
keys:
0 _col3 (type: string)
1 hr (type: string)
input vertices:
1 Map 4
Statistics: Num rows: 2 Data size: 50 Basic stats:
COMPLETE Column stats: NONE
Group By Operator
aggregations: count()
mode: hash
outputColumnNames: _col0
Statistics: Num rows: 1 Data size: 8 Basic stats:
COMPLETE Column stats: NONE
Reduce Output Operator
sort order:
Statistics: Num rows: 1 Data size: 8 Basic stats:
COMPLETE Column stats: NONE
value expressions: _col0 (type: bigint)
Local Work:
Map Reduce Local Work
Reducer 2
Reduce Operator Tree:
Group By Operator
aggregations: count(VALUE._col0)
mode: mergepartial
outputColumnNames: _col0
Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE
Column stats: NONE
File Output Operator
compressed: false
Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE
Column stats: NONE
table:
input format:
org.apache.hadoop.mapred.SequenceFileInputFormat
output format:
org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat
serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe
Stage: Stage-0
Fetch Operator
limit: -1
Processor Tree:
ListSink
{noformat}
One interesting thing is when enabling {{hive.tez.dynamic.semijoin.reduction}},
there is an extra reduce Reducer 2 <- Map 6 (GROUP, 1). But what's purpose of
Reducer 2?
{noformat}
Reducer 2
Reduce Operator Tree:
Group By Operator
aggregations: min(VALUE._col0), max(VALUE._col1),
bloom_filter(VALUE._col2, expectedEntries=1000000)
mode: final
outputColumnNames: _col0, _col1, _col2
Statistics: Num rows: 1 Data size: 552 Basic stats: COMPLETE
Column stats: NONE
Reduce Output Operator
sort order:
Statistics: Num rows: 1 Data size: 552 Basic stats: COMPLETE
Column stats: NONE
value expressions: _col0 (type: string), _col1 (type:
string), _col2 (type: binary)
{noformat}
> Case "multiple sources, single key" in spark_dynamic_pruning.q fails
> ---------------------------------------------------------------------
>
> Key: HIVE-16780
> URL: https://issues.apache.org/jira/browse/HIVE-16780
> Project: Hive
> Issue Type: Bug
> Reporter: liyunzhang_intel
> Assignee: liyunzhang_intel
> Attachments: HIVE-16780.patch
>
>
> script.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.strict.checks.cartesian.product=false;
> set hive.spark.dynamic.partition.pruning=true;
> -- multiple sources, single key
> select count(*) from srcpart join srcpart_date on (srcpart.ds =
> srcpart_date.ds) join srcpart_hour on (srcpart.hr = srcpart_hour.hr)
> {code}
> if disabling "hive.optimize.index.filter", case passes otherwise it always
> hang out in the first job. Exception
> {code}
> 17/05/27 23:39:45 DEBUG Executor task launch worker-0 PerfLogger: </PERFLOG
> method=SparkInitializeOperators start=1495899585574 end=1495899585933
> duration=359 from=org.apache.hadoop.hive.ql.exec.spark.SparkRecordHandler>
> 17/05/27 23:39:45 INFO Executor task launch worker-0 Utilities: PLAN PATH =
> hdfs://bdpe41:8020/tmp/hive/root/029a2d8a-c6e5-4ea9-adea-ef8fbea3cde2/hive_2017-05-27_23-39-06_464_5915518562441677640-1/-mr-10007/617d9dd6-9f9a-4786-8131-a7b98e8abc3e/map.xml
> 17/05/27 23:39:45 DEBUG Executor task launch worker-0 Utilities: Found plan
> in cache for name: map.xml
> 17/05/27 23:39:45 DEBUG Executor task launch worker-0 DFSClient: Connecting
> to datanode 10.239.47.162:50010
> 17/05/27 23:39:45 DEBUG Executor task launch worker-0 MapOperator: Processing
> alias(es) srcpart_hour for file
> hdfs://bdpe41:8020/user/hive/warehouse/srcpart_hour/000008_0
> 17/05/27 23:39:45 DEBUG Executor task launch worker-0 ObjectCache: Creating
> root_20170527233906_ac2934e1-2e58-4116-9f0d-35dee302d689_DynamicValueRegistry
> 17/05/27 23:39:45 ERROR Executor task launch worker-0 SparkMapRecordHandler:
> Error processing row: org.apache.hadoop.hive.ql.metadata.HiveException: Hive
> Runtime Error while processing row {"hr":"11","hour":"11"}
> org.apache.hadoop.hive.ql.metadata.HiveException: Hive Runtime Error while
> processing row {"hr":"11","hour":"11"}
> at
> org.apache.hadoop.hive.ql.exec.MapOperator.process(MapOperator.java:562)
> at
> org.apache.hadoop.hive.ql.exec.spark.SparkMapRecordHandler.processRow(SparkMapRecordHandler.java:136)
> at
> org.apache.hadoop.hive.ql.exec.spark.HiveMapFunctionResultList.processNextRecord(HiveMapFunctionResultList.java:48)
> at
> org.apache.hadoop.hive.ql.exec.spark.HiveMapFunctionResultList.processNextRecord(HiveMapFunctionResultList.java:27)
> 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$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> Caused by: java.lang.IllegalStateException: Failed to retrieve dynamic value
> for RS_7_srcpart__col3_min
> at
> org.apache.hadoop.hive.ql.plan.DynamicValue.getValue(DynamicValue.java:126)
> at
> org.apache.hadoop.hive.ql.plan.DynamicValue.getWritableValue(DynamicValue.java:101)
> at
> org.apache.hadoop.hive.ql.exec.ExprNodeDynamicValueEvaluator._evaluate(ExprNodeDynamicValueEvaluator.java:51)
> at
> org.apache.hadoop.hive.ql.exec.ExprNodeEvaluator.evaluate(ExprNodeEvaluator.java:80)
> at
> org.apache.hadoop.hive.ql.exec.ExprNodeGenericFuncEvaluator$DeferredExprObject.get(ExprNodeGenericFuncEvaluator.java:88)
> at
> org.apache.hadoop.hive.ql.udf.generic.GenericUDFOPEqualOrGreaterThan.evaluate(GenericUDFOPEqualOrGreaterThan.java:108)
> at
> org.apache.hadoop.hive.ql.udf.generic.GenericUDFBetween.evaluate(GenericUDFBetween.java:57)
> at
> org.apache.hadoop.hive.ql.exec.ExprNodeGenericFuncEvaluator._evaluate(ExprNodeGenericFuncEvaluator.java:187)
> at
> org.apache.hadoop.hive.ql.exec.ExprNodeEvaluator.evaluate(ExprNodeEvaluator.java:80)
> at
> org.apache.hadoop.hive.ql.exec.ExprNodeGenericFuncEvaluator$DeferredExprObject.get(ExprNodeGenericFuncEvaluator.java:88)
> at
> org.apache.hadoop.hive.ql.udf.generic.GenericUDFOPAnd.evaluate(GenericUDFOPAnd.java:63)
> at
> org.apache.hadoop.hive.ql.exec.ExprNodeGenericFuncEvaluator._evaluate(ExprNodeGenericFuncEvaluator.java:187)
> at
> org.apache.hadoop.hive.ql.exec.ExprNodeEvaluator.evaluate(ExprNodeEvaluator.java:80)
> at
> org.apache.hadoop.hive.ql.exec.ExprNodeGenericFuncEvaluator$DeferredExprObject.get(ExprNodeGenericFuncEvaluator.java:88)
> at
> org.apache.hadoop.hive.ql.udf.generic.GenericUDFOPAnd.evaluate(GenericUDFOPAnd.java:63)
> at
> org.apache.hadoop.hive.ql.exec.ExprNodeGenericFuncEvaluator._evaluate(ExprNodeGenericFuncEvaluator.java:187)
> at
> org.apache.hadoop.hive.ql.exec.ExprNodeEvaluator.evaluate(ExprNodeEvaluator.java:80)
> at
> org.apache.hadoop.hive.ql.exec.ExprNodeEvaluatorHead._evaluate(ExprNodeEvaluatorHead.java:44)
> at
> org.apache.hadoop.hive.ql.exec.ExprNodeEvaluator.evaluate(ExprNodeEvaluator.java:80)
> at
> org.apache.hadoop.hive.ql.exec.ExprNodeEvaluator.evaluate(ExprNodeEvaluator.java:68)
> at
> org.apache.hadoop.hive.ql.exec.FilterOperator.process(FilterOperator.java:112)
> at org.apache.hadoop.hive.ql.exec.Operator.forward(Operator.java:897)
> at
> org.apache.hadoop.hive.ql.exec.TableScanOperator.process(TableScanOperator.java:130)
> at
> org.apache.hadoop.hive.ql.exec.MapOperator$MapOpCtx.forward(MapOperator.java:148)
> at
> org.apache.hadoop.hive.ql.exec.MapOperator.process(MapOperator.java:547)
> ... 17 more
> Caused by: org.apache.hadoop.hive.ql.metadata.HiveException:
> java.lang.NullPointerException
> at
> org.apache.hadoop.hive.ql.exec.mr.ObjectCache.retrieve(ObjectCache.java:62)
> at
> org.apache.hadoop.hive.ql.exec.mr.ObjectCache.retrieve(ObjectCache.java:51)
> at
> org.apache.hadoop.hive.ql.exec.ObjectCacheWrapper.retrieve(ObjectCacheWrapper.java:40)
> at
> org.apache.hadoop.hive.ql.plan.DynamicValue.getValue(DynamicValue.java:119)
> ... 41 more
> Caused by: java.lang.NullPointerException
> at
> org.apache.hadoop.hive.ql.exec.mr.ObjectCache.retrieve(ObjectCache.java:60)
> ... 44 more
> 17/05/27 23:39:45 ERROR Executor task launch worker-0 Executor: Exception in
> task 1.0 in stage 0.0 (TID 1)
> java.lang.RuntimeException: Error processing row:
> org.apache.hadoop.hive.ql.metadata.HiveException: Hive Runtime Error while
> processing row {"hr":"11","hour":"11"}
> at
> org.apache.hadoop.hive.ql.exec.spark.SparkMapRecordHandler.processRow(SparkMapRecordHandler.java:149)
> at
> org.apache.hadoop.hive.ql.exec.spark.HiveMapFunctionResultList.processNextRecord(HiveMapFunctionResultList.java:48)
> at
> org.apache.hadoop.hive.ql.exec.spark.HiveMapFunctionResultList.processNextRecord(HiveMapFunctionResultList.java:27)
> at
> org.apache.hadoop.hive.ql.exec.spark.HiveBaseFunctionResultList.hasNext(HiveBaseFunctionResultList.java:85)
> at
> scala.collection.convert.Wrappers$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$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> Caused by: org.apache.hadoop.hive.ql.metadata.HiveException: Hive Runtime
> Error while processing row {"hr":"11","hour":"11"}
> at
> org.apache.hadoop.hive.ql.exec.MapOperator.process(MapOperator.java:562)
> at
> org.apache.hadoop.hive.ql.exec.spark.SparkMapRecordHandler.processRow(SparkMapRecordHandler.java:136)
> ... 16 more
> Caused by: java.lang.IllegalStateException: Failed to retrieve dynamic value
> for RS_7_srcpart__col3_min
> at
> org.apache.hadoop.hive.ql.plan.DynamicValue.getValue(DynamicValue.java:126)
> at
> org.apache.hadoop.hive.ql.plan.DynamicValue.getWritableValue(DynamicValue.java:101)
> at
> org.apache.hadoop.hive.ql.exec.ExprNodeDynamicValueEvaluator._evaluate(ExprNodeDynamicValueEvaluator.java:51)
> at
> org.apache.hadoop.hive.ql.exec.ExprNodeEvaluator.evaluate(ExprNodeEvaluator.java:80)
> at
> org.apache.hadoop.hive.ql.exec.ExprNodeGenericFuncEvaluator$DeferredExprObject.get(ExprNodeGenericFuncEvaluator.java:88)
> at
> org.apache.hadoop.hive.ql.udf.generic.GenericUDFOPEqualOrGreaterThan.evaluate(GenericUDFOPEqualOrGreaterThan.java:108)
> at
> org.apache.hadoop.hive.ql.udf.generic.GenericUDFBetween.evaluate(GenericUDFBetween.java:57)
> at
> org.apache.hadoop.hive.ql.exec.ExprNodeGenericFuncEvaluator._evaluate(ExprNodeGenericFuncEvaluator.java:187)
> at
> org.apache.hadoop.hive.ql.exec.ExprNodeEvaluator.evaluate(ExprNodeEvaluator.java:80)
> at
> org.apache.hadoop.hive.ql.exec.ExprNodeGenericFuncEvaluator$DeferredExprObject.get(ExprNodeGenericFuncEvaluator.java:88)
> at
> org.apache.hadoop.hive.ql.udf.generic.GenericUDFOPAnd.evaluate(GenericUDFOPAnd.java:63)
> at
> org.apache.hadoop.hive.ql.exec.ExprNodeGenericFuncEvaluator._evaluate(ExprNodeGenericFuncEvaluator.java:187)
> at
> org.apache.hadoop.hive.ql.exec.ExprNodeEvaluator.evaluate(ExprNodeEvaluator.java:80)
> at
> org.apache.hadoop.hive.ql.exec.ExprNodeGenericFuncEvaluator$DeferredExprObject.get(ExprNodeGenericFuncEvaluator.java:88)
> at org.apache.hadoop.hive
> {code}
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