[SQL]A confusing NullPointerException when creating table using Spark2.1.0

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[SQL]A confusing NullPointerException when creating table using Spark2.1.0

StanZhai
Hi all,

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

==================== 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)

I also found that when I changed my code as follow:

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

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().

How can I solve this problem?

Any help is greatly appreicated!

Best,
Stan
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Re: [SQL]A confusing NullPointerException when creating table using Spark2.1.0

StanZhai
This issue has been fixed by https://github.com/apache/spark/pull/16820.
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