cloud-fan commented on a change in pull request #17277:
URL: https://github.com/apache/spark/pull/17277#discussion_r532348435
##########
File path:
sql/hive/src/test/scala/org/apache/spark/sql/hive/PartitionProviderCompatibilitySuite.scala
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@@ -316,6 +316,28 @@ class PartitionProviderCompatibilitySuite
}
}
}
+
+ test(s"SPARK-19887 partition value is null - partition management
$enabled") {
+ withTable("test") {
+ Seq((1, "p", 1), (2, null, 2)).toDF("a", "b", "c")
+ .write.partitionBy("b", "c").saveAsTable("test")
+ checkAnswer(spark.table("test"),
+ Row(1, "p", 1) :: Row(2, null, 2) :: Nil)
+
+ Seq((3, null: String, 3)).toDF("a", "b", "c")
+ .write.mode("append").partitionBy("b", "c").saveAsTable("test")
+ checkAnswer(spark.table("test"),
+ Row(1, "p", 1) :: Row(2, null, 2) :: Row(3, null, 3) :: Nil)
+ // make sure partition pruning also works.
+ checkAnswer(spark.table("test").filter($"b".isNotNull), Row(1, "p", 1))
+
+ // empty string is an invalid partition value and we treat it as null
when read back.
Review comment:
I can't remember all the details as this PR is pretty old. This is
probably the behavior of Hive so we just followed it.
Looking at it now, I agree it's not ideal to treat invalid partition values
as null. We'd better fail earlier. Can we leave it as a known bug of v1 table
and fix it in v2?
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