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https://issues.apache.org/jira/browse/SPARK-18058?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Herman van Hovell resolved SPARK-18058.
---------------------------------------
Resolution: Fixed
Assignee: Nan Zhu
Fix Version/s: 2.1.0
> AnalysisException may be thrown when union two DFs whose struct fields have
> different nullability
> -------------------------------------------------------------------------------------------------
>
> Key: SPARK-18058
> URL: https://issues.apache.org/jira/browse/SPARK-18058
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.6.2, 2.0.1
> Reporter: Cheng Lian
> Assignee: Nan Zhu
> Fix For: 2.1.0
>
>
> The following Spark shell snippet reproduces this issue:
> {code}
> spark.range(10).createOrReplaceTempView("t1")
> spark.range(10).map(i => i:
> java.lang.Long).toDF("id").createOrReplaceTempView("t2")
> sql("SELECT struct(id) FROM t1 UNION ALL SELECT struct(id) FROM t2")
> {code}
> {noformat}
> org.apache.spark.sql.AnalysisException: Union can only be performed on tables
> with the compatible column types. StructType(StructField(id,LongType,true))
> <> StructType(StructField(id,LongType,false)) at the first column of the
> second table;
> at
> org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.failAnalysis(CheckAnalysis.scala:40)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer.failAnalysis(Analyzer.scala:57)
> at
> org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$11$$anonfun$apply$12.apply(CheckAnalysis.scala:291)
> at
> org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$11$$anonfun$apply$12.apply(CheckAnalysis.scala:289)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at
> org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$11.apply(CheckAnalysis.scala:289)
> at
> org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$11.apply(CheckAnalysis.scala:278)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at
> org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:278)
> at
> org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:67)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:132)
> at
> org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.checkAnalysis(CheckAnalysis.scala:67)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer.checkAnalysis(Analyzer.scala:57)
> at
> org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:49)
> at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:61)
> at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:573)
> ... 50 elided
> {noformat}
> The reason is that we treat two {{StructType}} incompatible even if their
> only differ from each other in field nullability.
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