uros-b commented on code in PR #56777: URL: https://github.com/apache/spark/pull/56777#discussion_r3476316133
########## sql/core/src/test/scala/org/apache/spark/sql/execution/aggregate/PartialAggregationBypassSuite.scala: ########## @@ -0,0 +1,131 @@ +/* + * 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.aggregate + +import org.apache.spark.sql.{functions => F, QueryTest} +import org.apache.spark.sql.catalyst.expressions.aggregate.{Complete, Final, Partial} +import org.apache.spark.sql.execution.SparkPlan +import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanHelper +import org.apache.spark.sql.functions.{count, session_window, sum} +import org.apache.spark.sql.internal.SQLConf +import org.apache.spark.sql.test.SharedSparkSession + +class PartialAggregationBypassSuite + extends QueryTest + with SharedSparkSession + with AdaptiveSparkPlanHelper { + + private def aggNodes(plan: SparkPlan): Seq[BaseAggregateExec] = + collectWithSubqueries(plan) { case a: BaseAggregateExec => a } + + test("bypassPartialAggregation=true produces no Partial-mode node and one Complete-mode node") { + withSQLConf(SQLConf.BYPASS_PARTIAL_AGGREGATION.key -> "true") { + val df = spark.range(100).toDF("v") + .groupBy((F.col("v") % 10).as("k")) + .agg(F.sum("v"), F.count("v")) + val aggs = aggNodes(df.queryExecution.executedPlan) + assert(aggs.forall(_.aggregateExpressions.forall(_.mode != Partial)), + "expected no Partial-mode aggregation nodes") + assert(aggs.exists(_.aggregateExpressions.exists(_.mode == Complete)), + "expected at least one Complete-mode aggregation node") + assert(!aggs.exists(_.aggregateExpressions.exists(_.mode == Final)), + "expected no Final-mode aggregation nodes") + } + } + + test("bypassPartialAggregation=false (default) produces Partial+Final plan") { + val df = spark.range(100).toDF("v") + .groupBy((F.col("v") % 10).as("k")) + .agg(F.sum("v")) + val aggs = aggNodes(df.queryExecution.executedPlan) + assert(aggs.exists(_.aggregateExpressions.exists(_.mode == Partial)), + "expected a Partial-mode aggregation node") + assert(aggs.exists(_.aggregateExpressions.exists(_.mode == Final)), + "expected a Final-mode aggregation node") + } + + test("results are identical with and without partial aggregation — SUM") { + val data = spark.range(1000).selectExpr("id % 7 as k", "id as v") + val expected = data.groupBy("k").sum("v").orderBy("k").collect() + withSQLConf(SQLConf.BYPASS_PARTIAL_AGGREGATION.key -> "true") { + val actual = data.groupBy("k").sum("v").orderBy("k").collect() + assert(actual.toSeq == expected.toSeq) + } + } + + test("results are identical with and without partial aggregation — COUNT") { + val data = spark.range(1000).selectExpr("id % 13 as k") + val expected = data.groupBy("k").count().orderBy("k").collect() + withSQLConf(SQLConf.BYPASS_PARTIAL_AGGREGATION.key -> "true") { + val actual = data.groupBy("k").count().orderBy("k").collect() + assert(actual.toSeq == expected.toSeq) + } + } + + test("results are identical with and without partial aggregation — AVG") { + val data = spark.range(1000).selectExpr("id % 5 as k", "id as v") + val expected = data.groupBy("k").avg("v").orderBy("k").collect() + withSQLConf(SQLConf.BYPASS_PARTIAL_AGGREGATION.key -> "true") { + val actual = data.groupBy("k").avg("v").orderBy("k").collect() + assert(actual.toSeq == expected.toSeq) + } + } + + test("session_window with bypassPartialAggregation=true merges overlapping sessions correctly") { + // Regression test: when bypassPartialAggregation=true, the early-return path in + // planAggregateWithoutDistinct skipped mayAppendMergingSessionExec, so overlapping + // sessions were never merged and the aggregation produced wrong row counts / sums. + import testImplicits._ + // Two events for key "a" fall within 10s of each other and must merge into one session. + // One event for key "b" stands alone. + val df = Seq( + ("2016-03-27 19:39:34", 1, "a"), + ("2016-03-27 19:39:39", 2, "a"), // within 10s of the first "a" — same session + ("2016-03-27 19:39:56", 3, "a"), // > 10s gap — separate session + ("2016-03-27 19:39:27", 4, "b") + ).toDF("time", "value", "id") + + val expected = df + .groupBy(session_window($"time", "10 seconds"), $"id") + .agg(count("*").as("cnt"), sum("value").as("total")) + .orderBy($"session_window.start".asc) + .selectExpr( + "CAST(session_window.start AS STRING)", + "CAST(session_window.end AS STRING)", + "id", "cnt", "total") + .collect() + + // With the bug, bypassPartialAggregation=true skips MergingSessionsExec and the two + // "a" events that belong to the same session appear as separate rows. + withSQLConf(SQLConf.BYPASS_PARTIAL_AGGREGATION.key -> "true") { + val actual = df + .groupBy(session_window($"time", "10 seconds"), $"id") + .agg(count("*").as("cnt"), sum("value").as("total")) + .orderBy($"session_window.start".asc) + .selectExpr( + "CAST(session_window.start AS STRING)", + "CAST(session_window.end AS STRING)", + "id", "cnt", "total") + .collect() + + assert(actual.toSeq == expected.toSeq, + s"session_window results differ with bypassPartialAggregation=true.\n" + + s"Expected:\n${expected.mkString("\n")}\nActual:\n${actual.mkString("\n")}") + } + } +} Review Comment: Test gap: no test with AQE enabled. Also, no TypedImperativeAggregate bypass test. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
