StanZhai created SPARK-19471:
--------------------------------

             Summary: [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
            Priority: Critical


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() + group by + join. 



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