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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2018/08/06 19:03:00 UTC

[jira] [Assigned] (SPARK-25036) Scala 2.12 issues: Compilation error with sbt

     [ https://issues.apache.org/jira/browse/SPARK-25036?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Apache Spark reassigned SPARK-25036:
------------------------------------

    Assignee: Apache Spark

> Scala 2.12 issues: Compilation error with sbt
> ---------------------------------------------
>
>                 Key: SPARK-25036
>                 URL: https://issues.apache.org/jira/browse/SPARK-25036
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.3.0, 2.4.0
>            Reporter: Kazuaki Ishizaki
>            Assignee: Apache Spark
>            Priority: Major
>
> When compiling with sbt, the following errors occur:
> There are two types:
> 1. {{ExprValue.isNull}} is compared with unexpected type.
> 1. {{match may not be exhaustive}} is detected at {{match}}
> The first one is more serious since it may also generate incorrect code in Spark 2.3.
> {code}
> [error] [warn] /home/ishizaki/Spark/PR/scala212/spark/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/statsEstimation/ValueInterval.scala:63: match may not be exhaustive.
> [error] It would fail on the following inputs: (NumericValueInterval(_, _), _), (_, NumericValueInterval(_, _)), (_, _)
> [error] [warn]   def isIntersected(r1: ValueInterval, r2: ValueInterval): Boolean = (r1, r2) match {
> [error] [warn] 
> [error] [warn] /home/ishizaki/Spark/PR/scala212/spark/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/statsEstimation/ValueInterval.scala:79: match may not be exhaustive.
> [error] It would fail on the following inputs: (NumericValueInterval(_, _), _), (_, NumericValueInterval(_, _)), (_, _)
> [error] [warn]     (r1, r2) match {
> [error] [warn] 
> [error] [warn] /home/ishizaki/Spark/PR/scala212/spark/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/ApproxCountDistinctForIntervals.scala:67: match may not be exhaustive.
> [error] It would fail on the following inputs: (ArrayType(_, _), _), (_, ArrayData()), (_, _)
> [error] [warn]     (endpointsExpression.dataType, endpointsExpression.eval()) match {
> [error] [warn] 
> [error] [warn] /home/ishizaki/Spark/PR/scala212/spark/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala:470: match may not be exhaustive.
> [error] It would fail on the following inputs: NewFunctionSpec(_, None, Some(_)), NewFunctionSpec(_, Some(_), None)
> [error] [warn]     newFunction match {
> [error] [warn] 
> [error] [warn] /home/ishizaki/Spark/PR/scala212/spark/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/stringExpressions.scala:94: org.apache.spark.sql.catalyst.expressions.codegen.ExprValue and String are unrelated: they will most likely always compare unequal
> [error] [warn]         if (eval.isNull != "true") {
> [error] [warn] 
> [error] [warn] /home/ishizaki/Spark/PR/scala212/spark/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/stringExpressions.scala:126: org.apache.spark.sql.catalyst.expressions.codegen.ExprValue and String are unrelated: they will most likely never compare equal
> [error] [warn]              if (eval.isNull == "true") {
> [error] [warn] 
> [error] [warn] /home/ishizaki/Spark/PR/scala212/spark/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/stringExpressions.scala:133: org.apache.spark.sql.catalyst.expressions.codegen.ExprValue and String are unrelated: they will most likely never compare equal
> [error] [warn]             if (eval.isNull == "true") {
> [error] [warn] 
> [error] [warn] /home/ishizaki/Spark/PR/scala212/spark/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/ScalaReflection.scala:709: match may not be exhaustive.
> [error] It would fail on the following input: Schema((x: org.apache.spark.sql.types.DataType forSome x not in org.apache.spark.sql.types.StructType), _)
> [error] [warn]   def attributesFor[T: TypeTag]: Seq[Attribute] = schemaFor[T] match {
> [error] [warn] 
> [error] [warn] /home/ishizaki/Spark/PR/scala212/spark/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GenerateUnsafeProjection.scala:90: org.apache.spark.sql.catalyst.expressions.codegen.ExprValue and String are unrelated: they will most likely never compare equal
> [error] [warn]       if (inputs.map(_.isNull).forall(_ == "false")) {
> [error] [warn] 
> {code}



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