gengliangwang commented on code in PR #51236:
URL: https://github.com/apache/spark/pull/51236#discussion_r2162664508
##########
sql/core/src/test/scala/org/apache/spark/sql/DataFrameAggregateSuite.scala:
##########
@@ -2567,6 +2571,266 @@ class DataFrameAggregateSuite extends QueryTest
checkAnswer(df, Row(1.001d, 1, 1) :: Row(6.002d, 1, 1) :: Nil)
}
}
+
+ test("SPARK-52515: test of 1 parameter") {
+ val res = sql(
+ "SELECT approx_top_k(expr) FROM VALUES (0), (0), (1), (1), (2), (3),
(4), (4) AS tab(expr);"
+ )
+ checkAnswer(res, Row(Seq(Row(0, 2), Row(4, 2), Row(1, 2), Row(2, 1),
Row(3, 1))))
+ }
+
+ test("SPARK-52515: test of 2 parameter") {
+ val res = sql(
+ "SELECT approx_top_k(expr, 2) " +
+ "FROM VALUES 'a', 'b', 'c', 'c', 'c', 'c', 'd', 'd' AS tab(expr);")
+ checkAnswer(res, Row(Seq(Row("c", 4), Row("d", 2))))
+ }
+
+ test("SPARK-52515: test of 3 parameter") {
+ val res = sql(
+ "SELECT approx_top_k(expr, 10, 100) FROM VALUES (0), (1), (1), (2), (2),
(2) AS tab(expr);"
+ )
+ checkAnswer(res, Row(Seq(Row(2, 3), Row(1, 2), Row(0, 1))))
+ }
+
+ test("SPARK-52515: test of Integer type") {
+ val res = sql(
+ "SELECT approx_top_k(expr) FROM VALUES (0), (0), (1), (1), (2), (3),
(4), (4) AS tab(expr);"
+ )
+ checkAnswer(res, Row(Seq(Row(0, 2), Row(4, 2), Row(1, 2), Row(2, 1),
Row(3, 1))))
+ }
+
+ test("SPARK-52515: test of String type") {
+ val res = sql(
+ "SELECT approx_top_k(expr, 2)" +
+ "FROM VALUES 'a', 'b', 'c', 'c', 'c', 'c', 'd', 'd' AS tab(expr);")
+ checkAnswer(res, Row(Seq(Row("c", 4), Row("d", 2))))
+ }
+
+ test("SPARK-52515: test of Boolean type") {
+ Seq(true, true, false, true, true, false,
false).toDF("expr").createOrReplaceTempView("t_bool")
+ val res = sql("SELECT approx_top_k(expr, 1) FROM t_bool;")
+ checkAnswer(res, Row(Seq(Row(true, 4))))
+ }
+
+ test("SPARK-52515: test of Byte type") {
+ val res = sql(
+ "SELECT approx_top_k(expr, 2) " +
+ "FROM VALUES cast(0 AS BYTE), cast(0 AS BYTE), cast(1 AS BYTE), cast(1
AS BYTE), " +
+ "cast(2 AS BYTE), cast(3 AS BYTE), cast(4 AS BYTE), cast(4 AS BYTE) AS
tab(expr);")
+ checkAnswer(res, Row(Seq(Row(0, 2), Row(4, 2))))
+ }
+
+ test("SPARK-52515: test of Short type") {
+ val res = sql(
+ "SELECT approx_top_k(expr, 2) " +
+ "FROM VALUES cast(0 AS SHORT), cast(0 AS SHORT), cast(1 AS SHORT),
cast(1 AS SHORT), " +
+ "cast(2 AS SHORT), cast(3 AS SHORT), cast(4 AS SHORT), cast(4 AS
SHORT) AS tab(expr);")
+ checkAnswer(res, Row(Seq(Row(0, 2), Row(4, 2))))
+ }
+
+ test("SPARK-52515: test of Long type") {
+ val res = sql(
+ "SELECT approx_top_k(expr, 2) " +
+ "FROM VALUES cast(0 AS LONG), cast(0 AS LONG), cast(1 AS LONG), cast(1
AS LONG), " +
+ "cast(2 AS LONG), cast(3 AS LONG), cast(4 AS LONG), cast(4 AS LONG) AS
tab(expr);")
+ checkAnswer(res, Row(Seq(Row(0, 2), Row(4, 2))))
+ }
+
+ test("SPARK-52515: test of Float type") {
+ val res = sql(
+ "SELECT approx_top_k(expr) " +
+ "FROM VALUES cast(0.0 AS FLOAT), cast(0.0 AS FLOAT), " +
+ "cast(1.0 AS FLOAT), cast(1.0 AS FLOAT), " +
+ "cast(2.0 AS FLOAT), cast(3.0 AS FLOAT), " +
+ "cast(4.0 AS FLOAT), cast(4.0 AS FLOAT) AS tab(expr);")
+ checkAnswer(res, Row(Seq(Row(0.0, 2), Row(1.0, 2), Row(4.0, 2), Row(2.0,
1), Row(3.0, 1))))
+ }
+
+ test("SPARK-52515: test of Double type") {
+ val res = sql(
+ "SELECT approx_top_k(expr, 2) " +
+ "FROM VALUES cast(0.0 AS DOUBLE), cast(0.0 AS DOUBLE), " +
+ "cast(1.0 AS DOUBLE), cast(1.0 AS DOUBLE), " +
+ "cast(2.0 AS DOUBLE), cast(3.0 AS DOUBLE), " +
+ "cast(4.0 AS DOUBLE), cast(4.0 AS DOUBLE) AS tab(expr);")
+ checkAnswer(res, Row(Seq(Row(0.0, 2), Row(4.0, 2))))
+ }
+
+ test("SPARK-52515: test of Date type") {
+ val res = sql(
+ "SELECT approx_top_k(expr, 2) " +
+ "FROM VALUES cast('2023-01-01' AS DATE), cast('2023-01-01' AS DATE), "
+
+ "cast('2023-01-02' AS DATE), cast('2023-01-02' AS DATE), " +
+ "cast('2023-01-03' AS DATE), cast('2023-01-04' AS DATE), " +
+ "cast('2023-01-05' AS DATE), cast('2023-01-05' AS DATE) AS tab(expr);")
+ checkAnswer(
+ res,
+ Row(Seq(Row(Date.valueOf("2023-01-02"), 2),
Row(Date.valueOf("2023-01-01"), 2))))
+ }
+
+ test("SPARK-52515: test of Timestamp type") {
+ val res = sql(
+ "SELECT approx_top_k(expr, 2) " +
+ "FROM VALUES cast('2023-01-01 00:00:00' AS TIMESTAMP), " +
+ "cast('2023-01-01 00:00:00' AS TIMESTAMP), " +
+ "cast('2023-01-02 00:00:00' AS TIMESTAMP), " +
+ "cast('2023-01-02 00:00:00' AS TIMESTAMP), " +
+ "cast('2023-01-03 00:00:00' AS TIMESTAMP), " +
+ "cast('2023-01-04 00:00:00' AS TIMESTAMP), " +
+ "cast('2023-01-05 00:00:00' AS TIMESTAMP), " +
+ "cast('2023-01-05 00:00:00' AS TIMESTAMP) AS tab(expr);")
+ checkAnswer(
+ res,
+ Row(Seq(Row(Timestamp.valueOf("2023-01-02 00:00:00"), 2),
+ Row(Timestamp.valueOf("2023-01-05 00:00:00"), 2))))
+ }
+
+ test("SPARK-52515: test of Decimal type") {
+ val res = sql(
+ "SELECT approx_top_k(expr, 2) AS top_k_result " +
+ "FROM VALUES (0.0), (0.0), (0.0) ,(1.0), (1.0), (2.0), (3.0), (4.0) AS
tab(expr);")
+ checkAnswer(
+ res,
+ Row(Seq(Row(new java.math.BigDecimal("0.0"), 3), Row(new
java.math.BigDecimal("1.0"), 2))))
+ }
+
+ test("SPARK-52515: test of Decimal(10, 2) type") {
+ val res = sql(
+ "SELECT approx_top_k(expr, 2) AS top_k_result " +
+ "FROM VALUES CAST(0.0 AS DECIMAL(10, 2)), CAST(0.0 AS DECIMAL(10, 2)),
" +
+ "CAST(0.0 AS DECIMAL(10, 2)), CAST(1.0 AS DECIMAL(10, 2)), " +
+ "CAST(1.0 AS DECIMAL(10, 2)), CAST(2.0 AS DECIMAL(10, 2)), " +
+ "CAST(3.0 AS DECIMAL(10, 2)), CAST(4.0 AS DECIMAL(10, 2)) AS
tab(expr);")
+ checkAnswer(
+ res,
+ Row(Seq(Row(new java.math.BigDecimal("0.00"), 3), Row(new
java.math.BigDecimal("1.00"), 2))))
+ }
+
+ test("SPARK-52515: test of Decimal(20, 1) type") {
+ val res = sql(
+ "SELECT approx_top_k(expr, 2) AS top_k_result " +
+ "FROM VALUES CAST(0.0 AS DECIMAL(20, 1)), CAST(0.0 AS DECIMAL(20, 1)),
" +
+ "CAST(0.0 AS DECIMAL(20, 1)), CAST(1.0 AS DECIMAL(20, 1)), " +
+ "CAST(1.0 AS DECIMAL(20, 1)), CAST(2.0 AS DECIMAL(20, 1)), " +
+ "CAST(3.0 AS DECIMAL(20, 1)), CAST(4.0 AS DECIMAL(20, 1)) AS
tab(expr);")
+ checkAnswer(
+ res,
+ Row(Seq(Row(new java.math.BigDecimal("0.0"), 3), Row(new
java.math.BigDecimal("1.0"), 2))))
+ }
+
+ test("SPARK-52515: invalid k value") {
+ checkError(
+ exception = intercept[SparkRuntimeException] {
+ sql("SELECT approx_top_k(expr, 0) FROM VALUES (0), (1), (2) AS
tab(expr);").collect()
+ },
+ condition = "APPROX_TOP_K_NON_POSITIVE_ARG",
+ parameters = Map("argName" -> "`k`", "argValue" -> "0")
+ )
+ }
+
+ test("SPARK-52515: invalid k value null") {
+ checkError(
+ exception = intercept[SparkRuntimeException] {
+ sql("SELECT approx_top_k(expr, NULL) FROM VALUES (0), (1), (2) AS
tab(expr);").collect()
+ },
+ condition = "APPROX_TOP_K_NULL_ARG",
+ parameters = Map("argName" -> "`k`")
+ )
+ }
+
+ test("SPARK-52515: invalid maxItemsTracked value") {
+ checkError(
+ exception = intercept[SparkRuntimeException] {
+ sql("SELECT approx_top_k(expr, 10, -1) FROM VALUES (0), (1), (2) AS
tab(expr);").collect()
+ },
+ condition = "APPROX_TOP_K_MAX_ITEMS_TRACKED_LESS_THAN_K",
+ parameters = Map("maxItemsTracked" -> "-1", "k" -> "10")
+ )
+ }
+
+ test("SPARK-52515: invalid maxItemsTracked value null") {
+ checkError(
+ exception = intercept[SparkRuntimeException] {
+ sql("SELECT approx_top_k(expr, 10, NULL) FROM VALUES (0), (1), (2) AS
tab(expr);").collect()
+ },
+ condition = "APPROX_TOP_K_NULL_ARG",
+ parameters = Map("argName" -> "`maxItemsTracked`")
+ )
+ }
+
+ test("SPARK-52515: invalid maxItemsTracked < k") {
+ checkError(
+ exception = intercept[SparkRuntimeException] {
+ sql("SELECT approx_top_k(expr, 10, 5) FROM VALUES (0), (1), (2) AS
tab(expr);").collect()
+ },
+ condition = "APPROX_TOP_K_MAX_ITEMS_TRACKED_LESS_THAN_K",
+ parameters = Map("maxItemsTracked" -> "5", "k" -> "10")
+ )
+ }
+
+ test("SPARK-52515: invalid item type array") {
+ checkError(
+ exception = intercept[ExtendedAnalysisException] {
+ sql("SELECT approx_top_k(expr) FROM VALUES array(1, 2), array(2, 3) AS
tab(expr);")
+ },
+ condition = "DATATYPE_MISMATCH.TYPE_CHECK_FAILURE_WITH_HINT",
+ parameters = Map(
+ "sqlExpr" -> "\"approx_top_k(expr, 5, 10000)\"",
+ "msg" -> "array columns are not supported",
+ "hint" -> ""
+ ),
+ queryContext = Array(ExpectedContext("approx_top_k(expr)", 7, 24))
+ )
+ }
+
+ test("SPARK-52515: invalid item type struct") {
+ sql("SELECT struct(1, 2) AS expr").createOrReplaceTempView("struct_table")
+ checkError(
+ exception = intercept[ExtendedAnalysisException] {
+ sql("SELECT approx_top_k(expr) FROM struct_table;")
+ },
+ condition = "DATATYPE_MISMATCH.TYPE_CHECK_FAILURE_WITH_HINT",
+ parameters = Map(
+ "sqlExpr" -> "\"approx_top_k(expr, 5, 10000)\"",
+ "msg" -> "struct columns are not supported",
+ "hint" -> ""
+ ),
+ queryContext = Array(ExpectedContext("approx_top_k(expr)", 7, 24))
+ )
+ }
+
+ test("SPARK-52515: does not count NULL values") {
+ val res = sql(
+ "SELECT approx_top_k(expr, 2)" +
+ "FROM VALUES 'a', 'a', 'b', 'b', 'b', NULL, NULL, NULL AS tab(expr);")
+ checkAnswer(res, Row(Seq(Row("b", 3), Row("a", 2))))
+ }
+
+ test("SPARK-52515: Accepts literal and foldable inputs") {
+ val agg = new ApproxTopK(
+ first = BoundReference(0, LongType, nullable = true),
+ second = Abs(Literal(10)),
+ third = Abs(Literal(-10))
+ )
+ assert(agg.checkInputDataTypes().isSuccess)
+ }
+
+ test("SPARK-52515: Fail if parameters are not foldable") {
Review Comment:
what if the parameter contains `current_date` or `current_timestamp`?
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