HeartSaVioR commented on code in PR #38503:
URL: https://github.com/apache/spark/pull/38503#discussion_r1021175378
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sql/core/src/test/scala/org/apache/spark/sql/streaming/FlatMapGroupsInPandasWithStateSuite.scala:
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@@ -240,25 +240,30 @@ class FlatMapGroupsInPandasWithStateSuite extends
StateStoreMetricsTest {
.groupBy("key")
.count()
- testStream(result, Complete)(
- AddData(inputData, "a"),
- CheckNewAnswer(("a", 1)),
- AddData(inputData, "a", "b"),
- // mapGroups generates ("a", "2"), ("b", "1"); so increases counts of a
and b by 1
- CheckNewAnswer(("a", 2), ("b", 1)),
- StopStream,
- StartStream(),
- AddData(inputData, "a", "b"),
- // mapGroups should remove state for "a" and generate ("a", "-1"), ("b",
"2") ;
- // so increment a and b by 1
- CheckNewAnswer(("a", 3), ("b", 2)),
- StopStream,
- StartStream(),
- AddData(inputData, "a", "c"),
- // mapGroups should recreate state for "a" and generate ("a", "1"),
("c", "1") ;
- // so increment a and c by 1
- CheckNewAnswer(("a", 4), ("b", 2), ("c", 1))
- )
+ // As of [SPARK-40940], multiple state operator with Complete mode is
disabled by default
+ val exp = intercept[AnalysisException] {
Review Comment:
In update and complete mode, streaming aggregation does not require event
time column to be a part of grouping key.
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