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/*
* 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.{CASE_SENSITIVE, CBO_ENABLED, JOIN_REORDER_ENABLED}
class JoinReorderSuite extends PlanTest with StatsEstimationTestBase {
override val conf = new SQLConf().copy(
CASE_SENSITIVE -> true, CBO_ENABLED -> true, JOIN_REORDER_ENABLED -> 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
}
/** Set up tables and columns for testing */
private val columnInfo: AttributeMap[ColumnStat] = AttributeMap(Seq(
attr("t1.k-1-2") -> ColumnStat(distinctCount = 2, min = Some(1), max = Some(2),
nullCount = 0, avgLen = 4, maxLen = 4),
attr("t1.v-1-10") -> ColumnStat(distinctCount = 10, min = Some(1), max = Some(10),
nullCount = 0, avgLen = 4, maxLen = 4),
attr("t2.k-1-5") -> ColumnStat(distinctCount = 5, min = Some(1), max = Some(5),
nullCount = 0, avgLen = 4, maxLen = 4),
attr("t3.v-1-100") -> ColumnStat(distinctCount = 100, min = Some(1), max = Some(100),
nullCount = 0, avgLen = 4, maxLen = 4),
attr("t4.k-1-2") -> ColumnStat(distinctCount = 2, min = Some(1), max = Some(2),
nullCount = 0, avgLen = 4, maxLen = 4),
attr("t4.v-1-10") -> ColumnStat(distinctCount = 10, min = Some(1), max = Some(10),
nullCount = 0, avgLen = 4, maxLen = 4),
attr("t5.k-1-5") -> ColumnStat(distinctCount = 5, min = Some(1), max = Some(5),
nullCount = 0, avgLen = 4, maxLen = 4),
attr("t5.v-1-5") -> ColumnStat(distinctCount = 5, min = Some(1), max = Some(5),
nullCount = 0, 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)
// Table t1/t4: big table with two columns
private val t1 = StatsTestPlan(
outputList = Seq("t1.k-1-2", "t1.v-1-10").map(nameToAttr),
rowCount = 1000,
// size = rows * (overhead + column length)
size = Some(1000 * (8 + 4 + 4)),
attributeStats = AttributeMap(Seq("t1.k-1-2", "t1.v-1-10").map(nameToColInfo)))
private val t4 = StatsTestPlan(
outputList = Seq("t4.k-1-2", "t4.v-1-10").map(nameToAttr),
rowCount = 2000,
size = Some(2000 * (8 + 4 + 4)),
attributeStats = AttributeMap(Seq("t4.k-1-2", "t4.v-1-10").map(nameToColInfo)))
// Table t2/t3: small table with only one column
private val t2 = StatsTestPlan(
outputList = Seq("t2.k-1-5").map(nameToAttr),
rowCount = 20,
size = Some(20 * (8 + 4)),
attributeStats = AttributeMap(Seq("t2.k-1-5").map(nameToColInfo)))
private val t3 = StatsTestPlan(
outputList = Seq("t3.v-1-100").map(nameToAttr),
rowCount = 100,
size = Some(100 * (8 + 4)),
attributeStats = AttributeMap(Seq("t3.v-1-100").map(nameToColInfo)))
// Table t5: small table with two columns
private val t5 = StatsTestPlan(
outputList = Seq("t5.k-1-5", "t5.v-1-5").map(nameToAttr),
rowCount = 20,
size = Some(20 * (8 + 4)),
attributeStats = AttributeMap(Seq("t5.k-1-5", "t5.v-1-5").map(nameToColInfo)))
test("reorder 3 tables") {
val originalPlan =
t1.join(t2).join(t3).where((nameToAttr("t1.k-1-2") === nameToAttr("t2.k-1-5")) &&
(nameToAttr("t1.v-1-10") === nameToAttr("t3.v-1-100")))
// The cost of original plan (use only cardinality to simplify explanation):
// cost = cost(t1 J t2) = 1000 * 20 / 5 = 4000
// In contrast, the cost of the best plan:
// cost = cost(t1 J t3) = 1000 * 100 / 100 = 1000 < 4000
// so (t1 J t3) J t2 is better (has lower cost, i.e. intermediate result size) than
// the original order (t1 J t2) J t3.
val bestPlan =
t1.join(t3, Inner, Some(nameToAttr("t1.v-1-10") === nameToAttr("t3.v-1-100")))
.join(t2, Inner, Some(nameToAttr("t1.k-1-2") === nameToAttr("t2.k-1-5")))
assertEqualPlans(originalPlan, bestPlan)
}
test("put unjoinable item at the end and reorder 3 joinable tables") {
// The ReorderJoin rule puts the unjoinable item at the end, and then CostBasedJoinReorder
// reorders other joinable items.
val originalPlan =
t1.join(t2).join(t4).join(t3).where((nameToAttr("t1.k-1-2") === nameToAttr("t2.k-1-5")) &&
(nameToAttr("t1.v-1-10") === nameToAttr("t3.v-1-100")))
val bestPlan =
t1.join(t3, Inner, Some(nameToAttr("t1.v-1-10") === nameToAttr("t3.v-1-100")))
.join(t2, Inner, Some(nameToAttr("t1.k-1-2") === nameToAttr("t2.k-1-5")))
.join(t4)
assertEqualPlans(originalPlan, bestPlan)
}
test("reorder 3 tables with pure-attribute project") {
val originalPlan =
t1.join(t2).join(t3).where((nameToAttr("t1.k-1-2") === nameToAttr("t2.k-1-5")) &&
(nameToAttr("t1.v-1-10") === nameToAttr("t3.v-1-100")))
.select(nameToAttr("t1.v-1-10"))
val bestPlan =
t1.join(t3, Inner, Some(nameToAttr("t1.v-1-10") === nameToAttr("t3.v-1-100")))
.select(nameToAttr("t1.k-1-2"), nameToAttr("t1.v-1-10"))
.join(t2, Inner, Some(nameToAttr("t1.k-1-2") === nameToAttr("t2.k-1-5")))
.select(nameToAttr("t1.v-1-10"))
assertEqualPlans(originalPlan, bestPlan)
}
test("reorder 3 tables - one of the leaf items is a project") {
val originalPlan =
t1.join(t5).join(t3).where((nameToAttr("t1.k-1-2") === nameToAttr("t5.k-1-5")) &&
(nameToAttr("t1.v-1-10") === nameToAttr("t3.v-1-100")))
.select(nameToAttr("t1.v-1-10"))
// Items: t1, t3, project(t5.k-1-5, t5)
val bestPlan =
t1.join(t3, Inner, Some(nameToAttr("t1.v-1-10") === nameToAttr("t3.v-1-100")))
.select(nameToAttr("t1.k-1-2"), nameToAttr("t1.v-1-10"))
.join(t5.select(nameToAttr("t5.k-1-5")), Inner,
Some(nameToAttr("t1.k-1-2") === nameToAttr("t5.k-1-5")))
.select(nameToAttr("t1.v-1-10"))
assertEqualPlans(originalPlan, bestPlan)
}
test("don't reorder if project contains non-attribute") {
val originalPlan =
t1.join(t2, Inner, Some(nameToAttr("t1.k-1-2") === nameToAttr("t2.k-1-5")))
.select((nameToAttr("t1.k-1-2") + nameToAttr("t2.k-1-5")) as "key", nameToAttr("t1.v-1-10"))
.join(t3, Inner, Some(nameToAttr("t1.v-1-10") === nameToAttr("t3.v-1-100")))
.select("key".attr)
assertEqualPlans(originalPlan, originalPlan)
}
test("reorder 4 tables (bushy tree)") {
val originalPlan =
t1.join(t4).join(t2).join(t3).where((nameToAttr("t1.k-1-2") === nameToAttr("t4.k-1-2")) &&
(nameToAttr("t1.k-1-2") === nameToAttr("t2.k-1-5")) &&
(nameToAttr("t4.v-1-10") === nameToAttr("t3.v-1-100")))
// The cost of original plan (use only cardinality to simplify explanation):
// cost(t1 J t4) = 1000 * 2000 / 2 = 1000000, cost(t1t4 J t2) = 1000000 * 20 / 5 = 4000000,
// cost = cost(t1 J t4) + cost(t1t4 J t2) = 5000000
// In contrast, the cost of the best plan (a bushy tree):
// cost(t1 J t2) = 1000 * 20 / 5 = 4000, cost(t4 J t3) = 2000 * 100 / 100 = 2000,
// cost = cost(t1 J t2) + cost(t4 J t3) = 6000 << 5000000.
val bestPlan =
t1.join(t2, Inner, Some(nameToAttr("t1.k-1-2") === nameToAttr("t2.k-1-5")))
.join(t4.join(t3, Inner, Some(nameToAttr("t4.v-1-10") === nameToAttr("t3.v-1-100"))),
Inner, Some(nameToAttr("t1.k-1-2") === nameToAttr("t4.k-1-2")))
assertEqualPlans(originalPlan, bestPlan)
}
test("keep the order of attributes in the final output") {
val outputLists = Seq("t1.k-1-2", "t1.v-1-10", "t3.v-1-100").permutations
while (outputLists.hasNext) {
val expectedOrder = outputLists.next().map(nameToAttr)
val expectedPlan =
t1.join(t3, Inner, Some(nameToAttr("t1.v-1-10") === nameToAttr("t3.v-1-100")))
.join(t2, Inner, Some(nameToAttr("t1.k-1-2") === nameToAttr("t2.k-1-5")))
.select(expectedOrder: _*)
// The plan should not change after optimization
assertEqualPlans(expectedPlan, expectedPlan)
}
}
private def assertEqualPlans(
originalPlan: LogicalPlan,
groundTruthBestPlan: LogicalPlan): Unit = {
val optimized = Optimize.execute(originalPlan.analyze)
val expected = groundTruthBestPlan.analyze
compareJoinOrder(optimized, expected)
}
}
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