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Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2022/08/02 04:03:40 UTC
[GitHub] [spark] beliefer commented on a diff in pull request #37320: [SPARK-39819][SQL] DS V2 aggregate push down can work with Top N or Paging (Sort with group expressions)
beliefer commented on code in PR #37320:
URL: https://github.com/apache/spark/pull/37320#discussion_r935093496
##########
sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCV2Suite.scala:
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@@ -864,6 +851,254 @@ class JDBCV2Suite extends QueryTest with SharedSparkSession with ExplainSuiteHel
checkAnswer(df2, Seq(Row(2, "david", 10000.00)))
}
+ test("scan with aggregate push-down and top N push-down") {
+ val df1 = spark.read
+ .table("h2.test.employee")
+ .groupBy("DEPT").sum("SALARY")
+ .orderBy("DEPT")
+ .limit(1)
+ checkSortRemoved(df1)
+ checkLimitRemoved(df1)
+ checkPushedInfo(df1,
+ "PushedAggregates: [SUM(SALARY)]",
+ "PushedGroupByExpressions: [DEPT]",
+ "PushedFilters: []",
+ "PushedTopN: ORDER BY [DEPT ASC NULLS FIRST] LIMIT 1")
+ checkAnswer(df1, Seq(Row(1, 19000.00)))
+
+ val df2 = spark.read
+ .table("h2.test.employee")
+ .select($"DEPT".as("my_dept"), $"SALARY")
+ .groupBy("my_dept").sum("SALARY")
+ .orderBy("my_dept")
+ .limit(1)
+ checkSortRemoved(df2)
+ checkLimitRemoved(df2)
+ checkPushedInfo(df2,
+ "PushedAggregates: [SUM(SALARY)]",
+ "PushedGroupByExpressions: [DEPT]",
+ "PushedFilters: []",
+ "PushedTopN: ORDER BY [DEPT ASC NULLS FIRST] LIMIT 1")
+ checkAnswer(df2, Seq(Row(1, 19000.00)))
+
+ val df3 = spark.read
+ .table("h2.test.employee")
+ .select($"SALARY",
+ when(($"SALARY" > 8000).and($"SALARY" < 10000), $"salary").otherwise(0).as("key"))
+ .groupBy("key").sum("SALARY")
+ .orderBy("key")
+ .limit(1)
+ checkSortRemoved(df3)
+ checkLimitRemoved(df3)
+ checkPushedInfo(df3,
+ "PushedAggregates: [SUM(SALARY)]",
+ "PushedGroupByExpressions: " +
+ "[CASE WHEN (SALARY > 8000.00) AND (SALARY < 10000.00) THEN SALARY ELSE 0.00 END]",
+ "PushedFilters: []",
+ "PushedTopN: ORDER BY [" +
+ "CASE WHEN (SALARY > 8000.00) AND (SALARY < 10000.00) THEN SALARY ELSE 0.00 END " +
+ "ASC NULLS FIRST] LIMIT 1")
+ checkAnswer(df3, Seq(Row(0, 44000.00)))
+
+ val df4 = spark.read
+ .table("h2.test.employee")
+ .groupBy("DEPT", "IS_MANAGER").sum("SALARY")
+ .orderBy("DEPT", "IS_MANAGER")
+ .limit(1)
+ checkSortRemoved(df4)
+ checkLimitRemoved(df4)
+ checkPushedInfo(df4,
+ "PushedAggregates: [SUM(SALARY)]",
+ "PushedGroupByExpressions: [DEPT, IS_MANAGER]",
+ "PushedFilters: []",
+ "PushedTopN: ORDER BY [DEPT ASC NULLS FIRST, IS_MANAGER ASC NULLS FIRST] LIMIT 1")
+ checkAnswer(df4, Seq(Row(1, false, 9000.00)))
+
+ val df5 = spark.read
+ .table("h2.test.employee")
+ .select($"DEPT".as("my_dept"), $"IS_MANAGER".as("my_manager"), $"SALARY")
+ .groupBy("my_dept", "my_manager").sum("SALARY")
+ .orderBy("my_dept", "my_manager")
+ .limit(1)
+ checkSortRemoved(df5)
+ checkLimitRemoved(df5)
+ checkPushedInfo(df5,
+ "PushedAggregates: [SUM(SALARY)]",
+ "PushedGroupByExpressions: [DEPT, IS_MANAGER]",
+ "PushedFilters: []",
+ "PushedTopN: ORDER BY [DEPT ASC NULLS FIRST, IS_MANAGER ASC NULLS FIRST] LIMIT 1")
+ checkAnswer(df5, Seq(Row(1, false, 9000.00)))
+
+ val df6 = spark.read
+ .table("h2.test.employee")
+ .select($"SALARY", $"IS_MANAGER",
+ when(($"SALARY" > 8000).and($"SALARY" < 10000), $"salary").otherwise(0).as("key"))
+ .groupBy("key", "IS_MANAGER").sum("SALARY")
+ .orderBy("key", "IS_MANAGER")
+ .limit(1)
+ checkSortRemoved(df6)
+ checkLimitRemoved(df6)
+ checkPushedInfo(df6,
+ "PushedAggregates: [SUM(SALARY)]",
+ "PushedGroupByExpressions: " +
+ "[CASE WHEN (SALARY > 8000.00) AND (SALARY < 10000.00) THEN SALARY ELSE 0.00 END, " +
+ "IS_MANAGER]",
+ "PushedFilters: []",
+ "PushedTopN: ORDER BY [" +
+ "CASE WHEN (SALARY > 8000.00) AND (SALARY < 10000.00) THEN SALARY ELSE 0.00 END " +
+ "ASC NULLS FIRST, IS_MANAGER ASC NULLS FIRST] LIMIT 1")
+ checkAnswer(df6, Seq(Row(0.00, false, 12000.00)))
+
+ val df7 = spark.read
+ .table("h2.test.employee")
+ .select($"DEPT", $"SALARY")
+ .groupBy("dept").agg(sum("SALARY"))
+ .orderBy(sum("SALARY"))
Review Comment:
OK
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