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https://issues.apache.org/jira/browse/SPARK-25028?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16573120#comment-16573120
]
Apache Spark commented on SPARK-25028:
--------------------------------------
User 'mgaido91' has created a pull request for this issue:
https://github.com/apache/spark/pull/22036
> AnalyzePartitionCommand failed with NPE if value is null
> --------------------------------------------------------
>
> Key: SPARK-25028
> URL: https://issues.apache.org/jira/browse/SPARK-25028
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 2.4.0
> Reporter: Izek Greenfield
> Priority: Major
>
> on line 143: val partitionColumnValues =
> partitionColumns.indices.map(r.get(_).toString)
> If the value is NULL the code will fail with NPE
> *sample:*
> {code:scala}
> val df = List((1, null , "first"), (2, null , "second")).toDF("index",
> "name", "value").withColumn("name", $"name".cast("string"))
> df.write.partitionBy("name").saveAsTable("df13")
> spark.sql("ANALYZE TABLE df13 PARTITION (name) COMPUTE STATISTICS")
> {code}
> output:
> 2018-08-08 09:25:43 WARN BaseSessionStateBuilder$$anon$1:66 - Max iterations
> (2) reached for batch Resolution
> java.lang.NullPointerException
> at
> org.apache.spark.sql.execution.command.AnalyzePartitionCommand$$anonfun$calculateRowCountsPerPartition$1$$anonfun$8.apply(AnalyzePartitionCommand.scala:143)
> at
> org.apache.spark.sql.execution.command.AnalyzePartitionCommand$$anonfun$calculateRowCountsPerPartition$1$$anonfun$8.apply(AnalyzePartitionCommand.scala:143)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at scala.collection.immutable.Range.foreach(Range.scala:160)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
> at scala.collection.AbstractTraversable.map(Traversable.scala:104)
> at
> org.apache.spark.sql.execution.command.AnalyzePartitionCommand$$anonfun$calculateRowCountsPerPartition$1.apply(AnalyzePartitionCommand.scala:143)
> at
> org.apache.spark.sql.execution.command.AnalyzePartitionCommand$$anonfun$calculateRowCountsPerPartition$1.apply(AnalyzePartitionCommand.scala:142)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at
> scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
> at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:186)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
> at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:186)
> at
> org.apache.spark.sql.execution.command.AnalyzePartitionCommand.calculateRowCountsPerPartition(AnalyzePartitionCommand.scala:142)
> at
> org.apache.spark.sql.execution.command.AnalyzePartitionCommand.run(AnalyzePartitionCommand.scala:104)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:70)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:68)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.executeCollect(commands.scala:79)
> at org.apache.spark.sql.Dataset$$anonfun$6.apply(Dataset.scala:190)
> at org.apache.spark.sql.Dataset$$anonfun$6.apply(Dataset.scala:190)
> at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3254)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77)
> at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3253)
> at org.apache.spark.sql.Dataset.<init>(Dataset.scala:190)
> at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:75)
> at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:641)
> ... 49 elided
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