Kazuaki Ishizaki created SPARK-25036:
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Summary: 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
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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