Github user wzhfy commented on a diff in the pull request: https://github.com/apache/spark/pull/17546#discussion_r110089743 --- Diff: sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/StarJoinCostBasedReorderSuite.scala --- @@ -0,0 +1,426 @@ +/* + * 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.catalyst.optimizer + +import org.apache.spark.sql.catalyst.dsl.expressions._ +import org.apache.spark.sql.catalyst.dsl.plans._ +import org.apache.spark.sql.catalyst.expressions.{Attribute, AttributeMap} +import org.apache.spark.sql.catalyst.plans.{Inner, PlanTest} +import org.apache.spark.sql.catalyst.plans.logical.{ColumnStat, LogicalPlan} +import org.apache.spark.sql.catalyst.rules.RuleExecutor +import org.apache.spark.sql.catalyst.statsEstimation.{StatsEstimationTestBase, StatsTestPlan} +import org.apache.spark.sql.internal.SQLConf +import org.apache.spark.sql.internal.SQLConf._ + + +class StarJoinCostBasedReorderSuite extends PlanTest with StatsEstimationTestBase { + + override val conf = new SQLConf().copy( + CASE_SENSITIVE -> true, + CBO_ENABLED -> true, + JOIN_REORDER_ENABLED -> true, + STARSCHEMA_DETECTION -> true, + JOIN_REORDER_DP_STAR_FILTER -> true) + + object Optimize extends RuleExecutor[LogicalPlan] { + val batches = + Batch("Operator Optimizations", FixedPoint(100), + CombineFilters, + PushDownPredicate, + ReorderJoin(conf), + PushPredicateThroughJoin, + ColumnPruning, + CollapseProject) :: + Batch("Join Reorder", Once, + CostBasedJoinReorder(conf)) :: Nil + } + + private val columnInfo: AttributeMap[ColumnStat] = AttributeMap(Seq( + // F1 (fact table) + attr("f1_fk1") -> ColumnStat(distinctCount = 100, min = Some(1), max = Some(50), + nullCount = 0, avgLen = 4, maxLen = 4), + attr("f1_fk2") -> ColumnStat(distinctCount = 100, min = Some(1), max = Some(50), + nullCount = 0, avgLen = 4, maxLen = 4), + attr("f1_fk3") -> ColumnStat(distinctCount = 100, min = Some(1), max = Some(50), + nullCount = 0, avgLen = 4, maxLen = 4), + attr("f1_c1") -> ColumnStat(distinctCount = 100, min = Some(1), max = Some(50), + nullCount = 0, avgLen = 4, maxLen = 4), + attr("f1_c2") -> ColumnStat(distinctCount = 100, min = Some(1), max = Some(50), + nullCount = 0, avgLen = 4, maxLen = 4), + + // D1 (dimension) + attr("d1_pk") -> ColumnStat(distinctCount = 100, min = Some(1), max = Some(100), + nullCount = 0, avgLen = 4, maxLen = 4), + attr("d1_c2") -> ColumnStat(distinctCount = 50, min = Some(1), max = Some(20), + nullCount = 0, avgLen = 4, maxLen = 4), + attr("d1_c3") -> ColumnStat(distinctCount = 50, min = Some(1), max = Some(20), + nullCount = 0, avgLen = 4, maxLen = 4), + + // D2 (dimension) + attr("d2_pk") -> ColumnStat(distinctCount = 20, min = Some(1), max = Some(5), + nullCount = 0, avgLen = 4, maxLen = 4), + attr("d2_c2") -> ColumnStat(distinctCount = 10, min = Some(1), max = Some(5), + nullCount = 0, avgLen = 4, maxLen = 4), + attr("d2_c3") -> ColumnStat(distinctCount = 10, min = Some(1), max = Some(5), + nullCount = 0, avgLen = 4, maxLen = 4), + + // D3 (dimension) + attr("d3_pk") -> ColumnStat(distinctCount = 10, min = Some(1), max = Some(5), + nullCount = 0, avgLen = 4, maxLen = 4), + attr("d3_c2") -> ColumnStat(distinctCount = 5, min = Some(1), max = Some(5), + nullCount = 0, avgLen = 4, maxLen = 4), + attr("d3_c3") -> ColumnStat(distinctCount = 5, min = Some(1), max = Some(5), + nullCount = 0, avgLen = 4, maxLen = 4), + + // T1 + attr("t1_c1") -> ColumnStat(distinctCount = 20, min = Some(1), max = Some(5), + nullCount = 1, avgLen = 4, maxLen = 4), + attr("t1_c2") -> ColumnStat(distinctCount = 10, min = Some(3), max = Some(5), + nullCount = 1, avgLen = 4, maxLen = 4), + attr("t1_c3") -> ColumnStat(distinctCount = 10, min = Some(3), max = Some(5), + nullCount = 1, avgLen = 4, maxLen = 4), + + // T2 + attr("t2_c1") -> ColumnStat(distinctCount = 5, min = Some(1), max = Some(3), + nullCount = 1, avgLen = 4, maxLen = 4), + attr("t2_c2") -> ColumnStat(distinctCount = 5, min = Some(3), max = Some(3), + nullCount = 1, avgLen = 4, maxLen = 4), + attr("t2_c3") -> ColumnStat(distinctCount = 5, min = Some(3), max = Some(3), + nullCount = 1, avgLen = 4, maxLen = 4), + + // T3 + attr("t3_c1") -> ColumnStat(distinctCount = 5, min = Some(1), max = Some(3), + nullCount = 1, avgLen = 4, maxLen = 4), + attr("t3_c2") -> ColumnStat(distinctCount = 5, min = Some(3), max = Some(3), + nullCount = 1, avgLen = 4, maxLen = 4), + attr("t3_c3") -> ColumnStat(distinctCount = 5, min = Some(3), max = Some(3), + nullCount = 1, avgLen = 4, maxLen = 4), + + // T4 + attr("t4_c1") -> ColumnStat(distinctCount = 5, min = Some(1), max = Some(3), + nullCount = 1, avgLen = 4, maxLen = 4), + attr("t4_c2") -> ColumnStat(distinctCount = 5, min = Some(3), max = Some(3), + nullCount = 1, avgLen = 4, maxLen = 4), + attr("t4_c3") -> ColumnStat(distinctCount = 5, min = Some(3), max = Some(3), + nullCount = 1, avgLen = 4, maxLen = 4), + + // T5 + attr("t5_c1") -> ColumnStat(distinctCount = 5, min = Some(1), max = Some(3), + nullCount = 1, avgLen = 4, maxLen = 4), + attr("t5_c2") -> ColumnStat(distinctCount = 5, min = Some(3), max = Some(3), + nullCount = 1, avgLen = 4, maxLen = 4), + attr("t5_c3") -> ColumnStat(distinctCount = 5, min = Some(3), max = Some(3), + nullCount = 1, avgLen = 4, maxLen = 4), + + // T6 + attr("t6_c1") -> ColumnStat(distinctCount = 5, min = Some(1), max = Some(3), + nullCount = 1, avgLen = 4, maxLen = 4), + attr("t6_c2") -> ColumnStat(distinctCount = 5, min = Some(3), max = Some(3), + nullCount = 1, avgLen = 4, maxLen = 4), + attr("t6_c3") -> ColumnStat(distinctCount = 5, min = Some(3), max = Some(3), + nullCount = 1, avgLen = 4, maxLen = 4) + + )) + + private val nameToAttr: Map[String, Attribute] = columnInfo.map(kv => kv._1.name -> kv._1) + private val nameToColInfo: Map[String, (Attribute, ColumnStat)] = + columnInfo.map(kv => kv._1.name -> kv) + + private val f1 = StatsTestPlan( + outputList = Seq("f1_fk1", "f1_fk2", "f1_fk3", "f1_c1", "f1_c2").map(nameToAttr), + rowCount = 1000, + size = Some(1000 * (8 + 4 * 5)), + attributeStats = AttributeMap(Seq("f1_fk1", "f1_fk2", "f1_fk3", "f1_c1", "f1_c2") + .map(nameToColInfo))) + + private val d1 = StatsTestPlan( + outputList = Seq("d1_pk", "d1_c2", "d1_c3").map(nameToAttr), + rowCount = 100, + size = Some(3000), + attributeStats = AttributeMap(Seq("d1_pk", "d1_c2", "d1_c3").map(nameToColInfo))) + + private val d2 = StatsTestPlan( + outputList = Seq("d2_pk", "d2_c2", "d2_c3").map(nameToAttr), + rowCount = 20, + size = Some(3000), + attributeStats = AttributeMap(Seq("d2_pk", "d2_c2", "d2_c3").map(nameToColInfo))) + + private val d3 = StatsTestPlan( + outputList = Seq("d3_pk", "d3_c2", "d3_c3").map(nameToAttr), + rowCount = 10, + size = Some(3000), + attributeStats = AttributeMap(Seq("d3_pk", "d3_c2", "d3_c3").map(nameToColInfo))) + + private val t1 = StatsTestPlan( + outputList = Seq("t1_c1", "t1_c2", "t1_c3").map(nameToAttr), + rowCount = 50, + size = Some(3000), + attributeStats = AttributeMap(Seq("t1_c1", "t1_c2", "t1_c3").map(nameToColInfo))) + + private val t2 = StatsTestPlan( + outputList = Seq("t2_c1", "t2_c2", "t2_c3").map(nameToAttr), + rowCount = 10, + size = Some(3000), + attributeStats = AttributeMap(Seq("t2_c1", "t2_c2", "t2_c3").map(nameToColInfo))) + + private val t3 = StatsTestPlan( + outputList = Seq("t3_c1", "t3_c2", "t3_c3").map(nameToAttr), + rowCount = 10, + size = Some(3000), + attributeStats = AttributeMap(Seq("t3_c1", "t3_c2", "t3_c3").map(nameToColInfo))) + + private val t4 = StatsTestPlan( + outputList = Seq("t4_c1", "t4_c2", "t4_c3").map(nameToAttr), + rowCount = 10, + size = Some(3000), + attributeStats = AttributeMap(Seq("t4_c1", "t4_c2", "t4_c3").map(nameToColInfo))) + + private val t5 = StatsTestPlan( + outputList = Seq("t5_c1", "t5_c2", "t5_c3").map(nameToAttr), + rowCount = 10, + size = Some(3000), + attributeStats = AttributeMap(Seq("t5_c1", "t5_c2", "t5_c3").map(nameToColInfo))) + + private val t6 = StatsTestPlan( + outputList = Seq("t6_c1", "t6_c2", "t6_c3").map(nameToAttr), + rowCount = 10, + size = Some(3000), + attributeStats = AttributeMap(Seq("t6_c1", "t6_c2", "t6_c3").map(nameToColInfo))) + + test("Test 1: Star query with two dimensions and two regular tables") { + + // d1 t1 + // \ / + // f1 + // / \ + // d2 t2 + // + // star: {f1, d1, d2} + // non-star: {t1, t2} + // + // level 0: (t2 ), (d2 ), (f1 ), (d1 ), (t1 ) + // level 1: {f1 d1 }, {d2 f1 } + // level 2: {d2 f1 d1 } + // level 3: {t2 d1 d2 f1 }, {t1 d1 d2 f1 } + // level 4: {f1 t1 t2 d1 d2 } + // + // Number of generated plans: 11 (vs. 20 w/o filter) + val query = + f1.join(t1).join(t2).join(d1).join(d2) + .where((nameToAttr("f1_c1") === nameToAttr("t1_c1")) && + (nameToAttr("f1_c2") === nameToAttr("t2_c1")) && + (nameToAttr("f1_fk1") === nameToAttr("d1_pk")) && + (nameToAttr("f1_fk2") === nameToAttr("d2_pk"))) + + val expected = + f1.join(d2, Inner, Some(nameToAttr("f1_fk2") === nameToAttr("d2_pk"))) + .join(d1, Inner, Some(nameToAttr("f1_fk1") === nameToAttr("d1_pk"))) + .join(t2, Inner, Some(nameToAttr("f1_c2") === nameToAttr("t2_c1"))) + .join(t1, Inner, Some(nameToAttr("f1_c1") === nameToAttr("t1_c1"))) + + assertEqualPlans(query, expected) + } + + test("Test 2: Star with a linear branch") { + // + // t1 d1 - t2 - t3 + // \ / + // f1 + // | + // d2 + // + // star: {d1, f1, d2} + // non-star: {t2, t1, t3} + // + // level 0: (f1 ), (d2 ), (t3 ), (d1 ), (t1 ), (t2 ) + // level 1: {t3 t2 }, {f1 d2 }, {f1 d1 } + // level 2: {d2 f1 d1 } + // level 3: {t1 d1 f1 d2 }, {t2 d1 f1 d2 } + // level 4: {d1 t2 f1 t1 d2 }, {d1 t3 t2 f1 d2 } + // level 5: {d1 t3 t2 f1 t1 d2 } + // + // Number of generated plans: 15 (vs 24) + val query = + d1.join(t1).join(t2).join(f1).join(d2).join(t3) + .where((nameToAttr("d1_pk") === nameToAttr("f1_fk1")) && + (nameToAttr("t1_c1") === nameToAttr("f1_c1")) && + (nameToAttr("d2_pk") === nameToAttr("f1_fk2")) && + (nameToAttr("f1_fk2") === nameToAttr("d2_pk")) && + (nameToAttr("d1_c2") === nameToAttr("t2_c1")) && + (nameToAttr("t2_c2") === nameToAttr("t3_c1"))) + + val expected = + f1.join(d2, Inner, Some(nameToAttr("f1_fk2") === nameToAttr("d2_pk"))) + .join(d1, Inner, Some(nameToAttr("f1_fk1") === nameToAttr("d1_pk"))) + .join(t3.join(t2, Inner, Some(nameToAttr("t2_c2") === nameToAttr("t3_c1"))), Inner, + Some(nameToAttr("d1_c2") === nameToAttr("t2_c1"))) + .join(t1, Inner, Some(nameToAttr("t1_c1") === nameToAttr("f1_c1"))) + + assertEqualPlans(query, expected) + } + + test("Test 3: Star with derived branches") { + // t3 t2 + // | | + // d1 - t4 - t1 + // | + // f1 + // | + // d2 + // + // star: (d1 f1 d2 ) + // non-star: (t4 t1 t2 t3 ) + // + // level 0: (t1 ), (t3 ), (f1 ), (d1 ), (t2 ), (d2 ), (t4 ) + // level 1: {f1 d2 }, {t1 t4 }, {t1 t2 }, {f1 d1 }, {t3 t4 } + // level 2: {d1 f1 d2 }, {t2 t1 t4 }, {t1 t3 t4 } + // level 3: {t4 d1 f1 d2 }, {t3 t4 t1 t2 } + // level 4: {d1 f1 t4 d2 t3 }, {d1 f1 t4 d2 t1 } + // level 5: {d1 f1 t4 d2 t1 t2 }, {d1 f1 t4 d2 t1 t3 } + // level 6: {d1 f1 t4 d2 t1 t2 t3 } + // + // Number of generated plans: 22 (vs. 34) + val query = + d1.join(t1).join(t2).join(t3).join(t4).join(f1).join(d2) + .where((nameToAttr("t1_c1") === nameToAttr("t2_c1")) && + (nameToAttr("t3_c1") === nameToAttr("t4_c1")) && + (nameToAttr("t1_c2") === nameToAttr("t4_c2")) && + (nameToAttr("d1_c2") === nameToAttr("t4_c3")) && + (nameToAttr("f1_fk1") === nameToAttr("d1_pk")) && + (nameToAttr("f1_fk2") === nameToAttr("d2_pk"))) + + val expected = + f1.join(d2, Inner, Some(nameToAttr("f1_fk2") === nameToAttr("d2_pk"))) + .join(d1, Inner, Some(nameToAttr("f1_fk1") === nameToAttr("d1_pk"))) + .join(t3.join(t4, Inner, Some(nameToAttr("t3_c1") === nameToAttr("t4_c1"))), Inner, + Some(nameToAttr("t3_c1") === nameToAttr("t4_c1"))) + .join(t1.join(t2, Inner, Some(nameToAttr("t1_c1") === nameToAttr("t2_c1"))), Inner, + Some(nameToAttr("t1_c2") === nameToAttr("t4_c2"))) + + assertEqualPlans(query, expected) + } + + test("Test 4: Star with several branches") { + // + // d1 - t3 - t4 + // | + // f1 - d3 - t1 - t2 + // | + // d2 - t5 - t6 + // + // star: {d1 f1 d2 d3 } + // non-star: {t5 t3 t6 t2 t4 t1} + // + // level 0: (t4 ), (d2 ), (t5 ), (d3 ), (d1 ), (f1 ), (t2 ), (t6 ), (t1 ), (t3 ) + // level 1: {t5 t6 }, {t4 t3 }, {d3 f1 }, {t2 t1 }, {d2 f1 }, {d1 f1 } + // level 2: {d2 d1 f1 }, {d2 d3 f1 }, {d3 d1 f1 } + // level 3: {d2 d1 d3 f1 } + // level 4: {d1 t3 d3 f1 d2 }, {d1 d3 f1 t1 d2 }, {d1 t5 d3 f1 d2 } + // level 5: {d1 t5 d3 f1 t1 d2 }, {d1 t3 t4 d3 f1 d2 }, {d1 t5 t6 d3 f1 d2 }, + // {d1 t5 t3 d3 f1 d2 }, {d1 t3 d3 f1 t1 d2 }, {d1 t2 d3 f1 t1 d2 } + // level 6: {d1 t5 t3 t4 d3 f1 d2 }, {d1 t3 t2 d3 f1 t1 d2 }, {d1 t5 t6 d3 f1 t1 d2 }, + // {d1 t5 t3 d3 f1 t1 d2 }, {d1 t5 t2 d3 f1 t1 d2 }, ... + // ... + // level 9: {d1 t5 t3 t6 t2 t4 d3 f1 t1 d2 } + // + // Number of generated plans: 46 (vs. 82) + val query = + d1.join(t3).join(t4).join(f1).join(d2).join(t5).join(t6).join(d3).join(t1).join(t2) + .where((nameToAttr("d1_c2") === nameToAttr("t3_c1")) && + (nameToAttr("t3_c2") === nameToAttr("t4_c2")) && + (nameToAttr("d1_pk") === nameToAttr("f1_fk1")) && + (nameToAttr("f1_fk2") === nameToAttr("d2_pk")) && + (nameToAttr("d2_c2") === nameToAttr("t5_c1")) && + (nameToAttr("t5_c2") === nameToAttr("t6_c2")) && + (nameToAttr("f1_fk3") === nameToAttr("d3_pk")) && + (nameToAttr("d3_c2") === nameToAttr("t1_c1")) && + (nameToAttr("t1_c2") === nameToAttr("t2_c2"))) + + val expected = + f1.join(d3, Inner, Some(nameToAttr("f1_fk3") === nameToAttr("d3_pk"))) + .join(d1, Inner, Some(nameToAttr("f1_fk1") === nameToAttr("d1_pk"))) + .join(d2, Inner, Some(nameToAttr("f1_fk2") === nameToAttr("d2_pk"))) + .join(t4.join(t3, Inner, Some(nameToAttr("t3_c2") === nameToAttr("t4_c2"))), Inner, + Some(nameToAttr("d1_c2") === nameToAttr("t3_c1"))) + .join(t2.join(t1, Inner, Some(nameToAttr("t1_c2") === nameToAttr("t2_c2"))), Inner, + Some(nameToAttr("d3_c2") === nameToAttr("t1_c1"))) + .join(t5.join(t6, Inner, Some(nameToAttr("t5_c2") === nameToAttr("t6_c2"))), Inner, + Some(nameToAttr("d2_c2") === nameToAttr("t5_c1"))) + + assertEqualPlans(query, expected) + } + + test("Test 5: RI star only") { + // d1 + // | + // f1 + // / \ + // d2 d3 + // + // star: {f1, d1, d2, d3} + // non-star: {} + // level 0: (d1), (f1), (d2), (d3) + // level 1: {f1 d3 }, {f1 d2 }, {d1 f1 } + // level 2: {d1 f1 d2 }, {d2 f1 d3 }, {d1 f1 d3 } + // level 3: {d1 d2 f1 d3 } + // Number of generated plans: 11 (= 11) + val query = + d1.join(d2).join(f1).join(d3) + .where((nameToAttr("f1_fk1") === nameToAttr("d1_pk")) && + (nameToAttr("f1_fk2") === nameToAttr("d2_pk")) && + (nameToAttr("f1_fk3") === nameToAttr("d3_pk"))) + + val expected = + f1.join(d3, Inner, Some(nameToAttr("f1_fk3") === nameToAttr("d3_pk"))) + .join(d2, Inner, Some(nameToAttr("f1_fk2") === nameToAttr("d2_pk"))) + .join(d1, Inner, Some(nameToAttr("f1_fk1") === nameToAttr("d1_pk"))) + + assertEqualPlans(query, expected) + } + + test("Test 6: No RI star") { --- End diff -- Can you also add a test for multi-star?
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