Re: [PR] [WIP][SPARK-45230][SQL] Plan sorter for Aggregate after SMJ [spark]

["singhpk234 (via GitHub)" <gi...@apache.org>]

singhpk234 commented on code in PR #43009:
URL: https://github.com/apache/spark/pull/43009#discussion_r1364554543


##########
sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/AggregateAfterSMJBenchmark.scala:
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@@ -0,0 +1,82 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.execution.benchmark
+
+import org.apache.spark.benchmark.Benchmark
+import org.apache.spark.sql.internal.SQLConf
+
+/**
+ * Benchmark to measure performance for aggregate primitives.
+ * To run this benchmark:
+ * {{{
+ *   1. without sbt: bin/spark-submit --class <this class>
+ *      --jars <spark core test jar>,<spark catalyst test jar> <spark sql test jar>
+ *   2. build/sbt "sql/Test/runMain <this class>"
+ *   3. generate result: SPARK_GENERATE_BENCHMARK_FILES=1 build/sbt "sql/Test/runMain <this class>"
+ *      Results will be written to "benchmarks/AggregateAfterSMJBenchmark-results.txt".
+ * }}}
+ */
+object AggregateAfterSMJBenchmark extends SqlBasedBenchmark {
+
+  override def runBenchmarkSuite(mainArgs: Array[String]): Unit = {
+    runBenchmark("Aggregate after SMJ") {
+      val N = 10 << 21
+
+      val benchmark = new Benchmark("Aggregate after SMJ", N, output = output)
+      spark
+        .range(N)
+        .selectExpr(
+          "cast(id as decimal) as id1",
+          "cast(id as decimal) as id2",
+          "cast(id + 1 as decimal) as id3")
+        .createOrReplaceTempView("t1")
+      spark
+        .range(N)
+        .selectExpr(
+          "cast(id as decimal) as id1",
+          "cast(id as decimal) as id2",
+          "cast(id as decimal) as id3")
+        .createOrReplaceTempView("t2")
+
+      def f(): Unit = {
+        withSQLConf(SQLConf.AUTO_BROADCASTJOIN_THRESHOLD.key -> "-1") {
+          spark.sql(
+            s"""SELECT t1.id1, t1.id2, count(t1.id3) as cnt
+               |FROM t1
+               |JOIN t2
+               |ON t1.id2 = t2.id2 AND t1.id3 > t2.id3
+               |GROUP BY t1.id1, t1.id2

Review Comment:
   presently WSCG is not supported for SortAgg when group by expressions are present : https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/SortAggregateExec.scala#L95
   
   wondering if there are scenarios where it can regress because of this ? 



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