wuchong commented on a change in pull request #10001:
[FLINK-14535][table-planner-blink] Fix distinct key type for DecimalT…
URL: https://github.com/apache/flink/pull/10001#discussion_r339445914
##########
File path:
flink-table/flink-table-planner-blink/src/test/scala/org/apache/flink/table/planner/runtime/stream/sql/AggregateITCase.scala
##########
@@ -180,34 +180,68 @@ class AggregateITCase(
@Test
def testCountDistinct(): Unit = {
val data = new mutable.MutableList[Row]
- data.+=(Row.of(JInt.valueOf(1), JLong.valueOf(1L), "A"))
- data.+=(Row.of(JInt.valueOf(2), JLong.valueOf(2L), "B"))
- data.+=(Row.of(null, JLong.valueOf(2L), "B"))
- data.+=(Row.of(JInt.valueOf(3), JLong.valueOf(2L), "B"))
- data.+=(Row.of(JInt.valueOf(4), JLong.valueOf(3L), "C"))
- data.+=(Row.of(JInt.valueOf(5), JLong.valueOf(3L), "C"))
- data.+=(Row.of(JInt.valueOf(5), JLong.valueOf(3L), null))
- data.+=(Row.of(JInt.valueOf(6), JLong.valueOf(3L), "C"))
- data.+=(Row.of(JInt.valueOf(7), JLong.valueOf(4L), "B"))
- data.+=(Row.of(JInt.valueOf(8), JLong.valueOf(4L), "A"))
- data.+=(Row.of(JInt.valueOf(9), JLong.valueOf(4L), "D"))
- data.+=(Row.of(null, JLong.valueOf(4L), null))
- data.+=(Row.of(JInt.valueOf(10), JLong.valueOf(4L), "E"))
- data.+=(Row.of(JInt.valueOf(11), JLong.valueOf(5L), "A"))
- data.+=(Row.of(JInt.valueOf(12), JLong.valueOf(5L), "B"))
-
- val rowType: RowTypeInfo = new RowTypeInfo(Types.INT, Types.LONG,
Types.STRING)
-
- val t = failingDataSource(data)(rowType).toTable(tEnv, 'a, 'b, 'c)
+ data.+=(Row.of(localDateTime("1970-01-01 00:00:01"),
localDate("1970-01-01"),
+ mLocalTime("00:00:01"), BigDecimal(1).bigDecimal, JInt.valueOf(1),
JLong.valueOf(1L),
+ Long.box(1L), "A"))
+ data.+=(Row.of(localDateTime("1970-01-01 00:00:02"),
localDate("1970-01-02"),
+ mLocalTime("00:00:02"), BigDecimal(2).bigDecimal, JInt.valueOf(2),
JLong.valueOf(2L),
+ Long.box(2L), "B"))
+ data.+=(Row.of(localDateTime("1970-01-01 00:00:03"),
localDate("1970-01-03"),
+ mLocalTime("00:00:03"), BigDecimal(3).bigDecimal, null,
JLong.valueOf(3L),
+ Long.box(2L), "B"))
+ data.+=(Row.of(localDateTime("1970-01-01 00:00:04"),
localDate("1970-01-04"),
+ mLocalTime("00:00:04"), BigDecimal(4).bigDecimal, JInt.valueOf(4),
JLong.valueOf(4L),
+ Long.box(3L), "C"))
+ data.+=(Row.of(localDateTime("1970-01-01 00:00:05"),
localDate("1970-01-05"),
+ mLocalTime("00:00:05"), BigDecimal(5).bigDecimal, JInt.valueOf(5),
JLong.valueOf(5L),
+ Long.box(3L), "C"))
+ data.+=(Row.of(localDateTime("1970-01-01 00:00:06"),
localDate("1970-01-06"),
+ mLocalTime("00:00:06"), BigDecimal(6).bigDecimal, JInt.valueOf(6),
JLong.valueOf(6L),
+ Long.box(3L), "C"))
+ data.+=(Row.of(localDateTime("1970-01-01 00:00:07"),
localDate("1970-01-07"),
+ mLocalTime("00:00:07"), BigDecimal(7).bigDecimal, JInt.valueOf(7),
JLong.valueOf(7L),
+ Long.box(4L), "B"))
+ data.+=(Row.of(localDateTime("1970-01-01 00:00:08"),
localDate("1970-01-08"),
+ mLocalTime("00:00:08"), BigDecimal(8).bigDecimal, JInt.valueOf(8),
JLong.valueOf(8L),
+ Long.box(4L), "A"))
+ data.+=(Row.of(localDateTime("1970-01-01 00:00:09"),
localDate("1970-01-09"),
+ mLocalTime("00:00:09"), BigDecimal(9).bigDecimal, JInt.valueOf(9),
JLong.valueOf(9L),
+ Long.box(4L), "D"))
+ data.+=(Row.of(localDateTime("1970-01-01 00:00:10"),
localDate("1970-01-10"),
+ mLocalTime("00:00:10"), BigDecimal(10).bigDecimal, null,
JLong.valueOf(10L),
+ Long.box(4L), "E"))
+ data.+=(Row.of(localDateTime("1970-01-01 00:00:11"),
localDate("1970-01-11"),
+ mLocalTime("00:00:11"), BigDecimal(11).bigDecimal, JInt.valueOf(11),
JLong.valueOf(11L),
+ Long.box(5L), "A"))
+ data.+=(Row.of(localDateTime("1970-01-01 00:00:12"),
localDate("1970-01-12"),
+ mLocalTime("00:00:12"), BigDecimal(12).bigDecimal, JInt.valueOf(12),
JLong.valueOf(12L),
+ Long.box(5L), "B"))
Review comment:
We can improve it a bit more, to make it more readable and maintainable, and
cover more aspects,
1) please make sure the test data contains null data for each type
2) please make sure there are some duplicate values per group.
how about:
```scala
@Test
def testCountDistinct(): Unit = {
val ids = List(
1,
2, 2,
3, 3, 3,
4, 4, 4, 4)
val datetimes = List(
"1970-01-01 00:00:01",
"1970-01-01 00:00:02", "1970-01-01 00:00:03",
"1970-01-01 00:00:04", null, "1970-01-01 00:00:06",
"1970-01-01 00:00:07", "1970-01-01 00:00:07", "1970-01-01 00:00:09",
"1970-01-01 00:00:09")
val dates = List(
"1970-01-01",
"1970-01-02", "1970-01-03",
"1970-01-04", null, "1970-01-06",
"1970-01-07", "1970-01-07", "1970-01-09", "1970-01-09")
val data = new mutable.MutableList[Row]
for (i <- ids.indices) {
data += Row.of(Integer.valueOf(ids(i)), localDateTime(datetimes(i)),
localDate(dates(i)))
}
val rowType = new RowTypeInfo(Types.INT(), Types.LOCAL_DATE_TIME(),
Types.LOCAL_DATE())
val t = failingDataSource(data)(rowType).toTable(
tEnv, 'id, 'a, 'b)
tEnv.registerTable("T", t)
val t1 = tEnv.sqlQuery(
s"""
|SELECT
| id,
| 'TIMESTAMP:' || CAST(COUNT(DISTINCT a) AS VARCHAR),
| 'DATE:' || CAST(COUNT(DISTINCT b) AS VARCHAR)
|FROM T
|GROUP BY id
""".stripMargin)
val sink = new TestingRetractSink
t1.toRetractStream[Row].addSink(sink)
env.execute()
val expected = List(
"1,TIMESTAMP:1,DATE:1", "2,TIMESTAMP:2,DATE:2",
"3,TIMESTAMP:2,DATE:2", "4,TIMESTAMP:2,DATE:2")
assertEquals(expected.sorted, sink.getRetractResults.sorted)
}
```
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