Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/17348#discussion_r107330581
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/DataFramePivotSuite.scala ---
@@ -230,4 +230,17 @@ class DataFramePivotSuite extends QueryTest with
SharedSQLContext{
.groupBy($"a").pivot("a").agg(min($"b")),
Row(null, Seq(null, 7), null) :: Row(1, null, Seq(1, 7)) :: Nil)
}
+
+ test("pivot with timestamp and count should not print internal
representation") {
+ val ts = "2012-12-31 16:00:10.011"
+ val tsWithZone = "2013-01-01 00:00:10.011"
+
+ withSQLConf(SQLConf.SESSION_LOCAL_TIMEZONE.key -> "GMT") {
+ val df =
Seq(java.sql.Timestamp.valueOf(ts)).toDF("a").groupBy("a").pivot("a").count()
+ val expected = StructType(
+ StructField("a", TimestampType) ::
+ StructField(tsWithZone, LongType) :: Nil)
--- End diff --
Yea, I was confused of it too because the original values are apprently
rendered differently. However, it seems intended.
```scala
scala> spark.conf.set("spark.sql.session.timeZone", "America/Los_Angeles")
scala> val timestamp = java.sql.Timestamp.valueOf("2012-12-31 16:00:10.011")
timestamp: java.sql.Timestamp = 2012-12-31 16:00:10.011
scala> Seq(timestamp).toDF("a").show()
+--------------------+
| a|
+--------------------+
|2012-12-30 23:00:...|
+--------------------+
```
Internal values seem as they are but it seems only changing human readable
format according to the given timezone.
I guess this is as described in https://github.com/apache/spark/pull/16308
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