[
https://issues.apache.org/jira/browse/SPARK-19471?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Xiao Li reassigned SPARK-19471:
-------------------------------
Assignee: Feng Zhu
> [SQL]A confusing NullPointerException when creating table
> ---------------------------------------------------------
>
> Key: SPARK-19471
> URL: https://issues.apache.org/jira/browse/SPARK-19471
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.1.0
> Reporter: StanZhai
> Assignee: Feng Zhu
> Priority: Critical
> Fix For: 2.3.0
>
>
> After upgrading our Spark from 1.6.2 to 2.1.0, I encounter a confusing
> NullPointerException when creating table under Spark 2.1.0, but the problem
> does not exists in Spark 1.6.1.
> Environment: Hive 1.2.1, Hadoop 2.6.4
> {noformat}
> ==================== Code ====================
> // spark is an instance of HiveContext
> // merge is a Hive UDF
> val df = spark.sql("SELECT merge(field_a, null) AS new_a, field_b AS new_b
> FROM tb_1 group by field_a, field_b")
> df.createTempView("tb_temp")
> spark.sql("create table tb_result stored as parquet as " +
> "SELECT new_a" +
> "FROM tb_temp" +
> "LEFT JOIN `tb_2` ON " +
> "if(((`tb_temp`.`new_b`) = '' OR (`tb_temp`.`new_b`) IS NULL),
> concat('GrLSRwZE_', cast((rand() * 200) AS int)), (`tb_temp`.`new_b`)) =
> `tb_2`.`fka6862f17`")
> ==================== Physical Plan ====================
> *Project [new_a]
> +- *BroadcastHashJoin [if (((new_b = ) || isnull(new_b))) concat(GrLSRwZE_,
> cast(cast((_nondeterministic * 200.0) as int) as string)) else new_b],
> [fka6862f17], LeftOuter, BuildRight
> :- HashAggregate(keys=[field_a, field_b], functions=[], output=[new_a,
> new_b, _nondeterministic])
> : +- Exchange(coordinator ) hashpartitioning(field_a, field_b, 180),
> coordinator[target post-shuffle partition size: 1024880]
> : +- *HashAggregate(keys=[field_a, field_b], functions=[],
> output=[field_a, field_b])
> : +- *FileScan parquet bdp.tb_1[field_a,field_b] Batched: true,
> Format: Parquet, Location: InMemoryFileIndex[hdfs://hdcluster/data/tb_1,
> PartitionFilters: [], PushedFilters: [], ReadSchema: struct
> +- BroadcastExchange HashedRelationBroadcastMode(List(input[0, string,
> true]))
> +- *Project [fka6862f17]
> +- *FileScan parquet bdp.tb_2[fka6862f17] Batched: true, Format:
> Parquet, Location: InMemoryFileIndex[hdfs://hdcluster/data/tb_2,
> PartitionFilters: [], PushedFilters: [], ReadSchema: struct
> What does '*' mean before HashAggregate?
> ==================== Exception ====================
> org.apache.spark.SparkException: Task failed while writing rows
> ...
> java.lang.NullPointerException
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply_2$(Unknown
> Source)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown
> Source)
> at
> org.apache.spark.sql.execution.aggregate.AggregationIterator$$anonfun$generateResultProjection$3.apply(AggregationIterator.scala:260)
>
> at
> org.apache.spark.sql.execution.aggregate.AggregationIterator$$anonfun$generateResultProjection$3.apply(AggregationIterator.scala:259)
>
> at
> org.apache.spark.sql.execution.aggregate.TungstenAggregationIterator.next(TungstenAggregationIterator.scala:392)
>
> at
> org.apache.spark.sql.execution.aggregate.TungstenAggregationIterator.next(TungstenAggregationIterator.scala:79)
>
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$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$1.hasNext(WholeStageCodegenExec.scala:377)
>
> at
> org.apache.spark.sql.execution.datasources.FileFormatWriter$SingleDirectoryWriteTask.execute(FileFormatWriter.scala:252)
>
> at
> org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:199)
>
> at
> org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:197)
>
> at
> org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1341)
>
> at
> org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:202)
>
> at
> org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1$$anonfun$4.apply(FileFormatWriter.scala:138)
>
> at
> org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1$$anonfun$4.apply(FileFormatWriter.scala:137)
>
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
> at org.apache.spark.scheduler.Task.run(Task.scala:99)
> at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282)
> 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)
> {noformat}
> I also found that when I changed my code as follow:
> {noformat}
> spark.sql("create table tb_result stored as parquet as " +
> "SELECT new_b" +
> "FROM tb_temp" +
> "LEFT JOIN `tb_2` ON " +
> "if(((`tb_temp`.`new_b`) = '' OR (`tb_temp`.`new_b`) IS NULL),
> concat('GrLSRwZE_', cast((rand() * 200) AS int)), (`tb_temp`.`new_b`)) =
> `tb_2`.`fka6862f17`")
> or
> spark.sql("create table tb_result stored as parquet as " +
> "SELECT new_a" +
> "FROM tb_temp" +
> "LEFT JOIN `tb_2` ON " +
> "if(((`tb_temp`.`new_b`) = '' OR (`tb_temp`.`new_b`) IS NULL),
> concat('GrLSRwZE_', cast((200) AS int)), (`tb_temp`.`new_b`)) =
> `tb_2`.`fka6862f17`")
> will not have this problem.
> == Physical Plan of select new_b ... ==
> *Project [new_b]
> +- *BroadcastHashJoin [if (((new_b = ) || isnull(new_b))) concat(GrLSRwZE_,
> cast(cast((_nondeterministic * 200.0) as int) as string)) else new_b],
> [fka6862f17], LeftOuter, BuildRight
> :- *HashAggregate(keys=[field_a, field_b], functions=[], output=[new_b,
> _nondeterministic])
> : +- Exchange(coordinator ) hashpartitioning(field_a, field_b, 180),
> coordinator[target post-shuffle partition size: 1024880]
> : +- *HashAggregate(keys=[field_a, field_b], functions=[],
> output=[field_a, field_b])
> : +- *FileScan parquet bdp.tb_1[field_a,field_b] Batched: true,
> Format: Parquet, Location: InMemoryFileIndex[hdfs://hdcluster/data/tb_1,
> PartitionFilters: [], PushedFilters: [], ReadSchema: struct
> +- BroadcastExchange HashedRelationBroadcastMode(List(input[0, string,
> true]))
> +- *Project [fka6862f17]
> +- *FileScan parquet bdp.tb_2[fka6862f17] Batched: true, Format:
> Parquet, Location: InMemoryFileIndex[hdfs://hdcluster/data/tb_2,
> PartitionFilters: [], PushedFilters: [], ReadSchema: struct
> {noformat}
> Difference is `HashAggregate(keys=[field_a, field_b], functions=[],
> output=[new_b, _nondeterministic])` has a '*' char before it.
> It looks like something wrong with WholeStageCodegen when combine HiveUDF +
> rand() + group by + join.
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