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[SPARK-25949][SQL] Add test for PullOutPythonUDFInJoinCondition #22955
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171 changes: 171 additions & 0 deletions
171
.../scala/org/apache/spark/sql/catalyst/optimizer/PullOutPythonUDFInJoinConditionSuite.scala
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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. | ||
| */ | ||
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| package org.apache.spark.sql.catalyst.optimizer | ||
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| import org.scalatest.Matchers._ | ||
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| import org.apache.spark.api.python.PythonEvalType | ||
| import org.apache.spark.sql.AnalysisException | ||
| import org.apache.spark.sql.catalyst.dsl.expressions._ | ||
| import org.apache.spark.sql.catalyst.dsl.plans._ | ||
| import org.apache.spark.sql.catalyst.expressions.PythonUDF | ||
| import org.apache.spark.sql.catalyst.plans._ | ||
| import org.apache.spark.sql.catalyst.plans.logical.{LocalRelation, LogicalPlan} | ||
| import org.apache.spark.sql.catalyst.rules.RuleExecutor | ||
| import org.apache.spark.sql.internal.SQLConf._ | ||
| import org.apache.spark.sql.types.BooleanType | ||
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| class PullOutPythonUDFInJoinConditionSuite extends PlanTest { | ||
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| object Optimize extends RuleExecutor[LogicalPlan] { | ||
| val batches = | ||
| Batch("Extract PythonUDF From JoinCondition", Once, | ||
| PullOutPythonUDFInJoinCondition) :: | ||
| Batch("Check Cartesian Products", Once, | ||
| CheckCartesianProducts) :: Nil | ||
| } | ||
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| val testRelationLeft = LocalRelation('a.int, 'b.int) | ||
| val testRelationRight = LocalRelation('c.int, 'd.int) | ||
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| // Dummy python UDF for testing. Unable to execute. | ||
| val pythonUDF = PythonUDF("pythonUDF", null, | ||
| BooleanType, | ||
| Seq.empty, | ||
| PythonEvalType.SQL_BATCHED_UDF, | ||
| udfDeterministic = true) | ||
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| val unsupportedJoinTypes = Seq(LeftOuter, RightOuter, FullOuter, LeftAnti) | ||
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| private def comparePlanWithCrossJoinEnable(query: LogicalPlan, expected: LogicalPlan): Unit = { | ||
| // AnalysisException thrown by CheckCartesianProducts while spark.sql.crossJoin.enabled=false | ||
| val exception = intercept[AnalysisException] { | ||
| Optimize.execute(query.analyze) | ||
| } | ||
| assert(exception.message.startsWith("Detected implicit cartesian product")) | ||
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| // pull out the python udf while set spark.sql.crossJoin.enabled=true | ||
| withSQLConf(CROSS_JOINS_ENABLED.key -> "true") { | ||
| val optimized = Optimize.execute(query.analyze) | ||
| comparePlans(optimized, expected) | ||
| } | ||
| } | ||
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| test("inner join condition with python udf only") { | ||
| val query = testRelationLeft.join( | ||
| testRelationRight, | ||
| joinType = Inner, | ||
| condition = Some(pythonUDF)) | ||
| val expected = testRelationLeft.join( | ||
| testRelationRight, | ||
| joinType = Inner, | ||
| condition = None).where(pythonUDF).analyze | ||
| comparePlanWithCrossJoinEnable(query, expected) | ||
| } | ||
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| test("left semi join condition with python udf only") { | ||
| val query = testRelationLeft.join( | ||
| testRelationRight, | ||
| joinType = LeftSemi, | ||
| condition = Some(pythonUDF)) | ||
| val expected = testRelationLeft.join( | ||
| testRelationRight, | ||
| joinType = Inner, | ||
| condition = None).where(pythonUDF).select('a, 'b).analyze | ||
| comparePlanWithCrossJoinEnable(query, expected) | ||
| } | ||
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| test("python udf and common condition") { | ||
| val query = testRelationLeft.join( | ||
| testRelationRight, | ||
| joinType = Inner, | ||
| condition = Some(pythonUDF && 'a.attr === 'c.attr)) | ||
| val expected = testRelationLeft.join( | ||
| testRelationRight, | ||
| joinType = Inner, | ||
| condition = Some('a.attr === 'c.attr)).where(pythonUDF).analyze | ||
| val optimized = Optimize.execute(query.analyze) | ||
| comparePlans(optimized, expected) | ||
| } | ||
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| test("python udf or common condition") { | ||
| val query = testRelationLeft.join( | ||
| testRelationRight, | ||
| joinType = Inner, | ||
| condition = Some(pythonUDF || 'a.attr === 'c.attr)) | ||
| val expected = testRelationLeft.join( | ||
| testRelationRight, | ||
| joinType = Inner, | ||
| condition = None).where(pythonUDF || 'a.attr === 'c.attr).analyze | ||
| comparePlanWithCrossJoinEnable(query, expected) | ||
| } | ||
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| test("pull out whole complex condition with multiple python udf") { | ||
| val pythonUDF1 = PythonUDF("pythonUDF1", null, | ||
| BooleanType, | ||
| Seq.empty, | ||
| PythonEvalType.SQL_BATCHED_UDF, | ||
| udfDeterministic = true) | ||
| val condition = (pythonUDF || 'a.attr === 'c.attr) && pythonUDF1 | ||
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| val query = testRelationLeft.join( | ||
| testRelationRight, | ||
| joinType = Inner, | ||
| condition = Some(condition)) | ||
| val expected = testRelationLeft.join( | ||
| testRelationRight, | ||
| joinType = Inner, | ||
| condition = None).where(condition).analyze | ||
| comparePlanWithCrossJoinEnable(query, expected) | ||
| } | ||
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| test("partial pull out complex condition with multiple python udf") { | ||
| val pythonUDF1 = PythonUDF("pythonUDF1", null, | ||
| BooleanType, | ||
| Seq.empty, | ||
| PythonEvalType.SQL_BATCHED_UDF, | ||
| udfDeterministic = true) | ||
| val condition = (pythonUDF || pythonUDF1) && 'a.attr === 'c.attr | ||
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| val query = testRelationLeft.join( | ||
| testRelationRight, | ||
| joinType = Inner, | ||
| condition = Some(condition)) | ||
| val expected = testRelationLeft.join( | ||
| testRelationRight, | ||
| joinType = Inner, | ||
| condition = Some('a.attr === 'c.attr)).where(pythonUDF || pythonUDF1).analyze | ||
| val optimized = Optimize.execute(query.analyze) | ||
| comparePlans(optimized, expected) | ||
| } | ||
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| test("throw an exception for not support join type") { | ||
| for (joinType <- unsupportedJoinTypes) { | ||
| val thrownException = the [AnalysisException] thrownBy { | ||
| val query = testRelationLeft.join( | ||
| testRelationRight, | ||
| joinType, | ||
| condition = Some(pythonUDF)) | ||
| Optimize.execute(query.analyze) | ||
| } | ||
| assert(thrownException.message.contentEquals( | ||
| s"Using PythonUDF in join condition of join type $joinType is not supported.")) | ||
| } | ||
| } | ||
| } | ||
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sorry, probably I was not clear enough in my previous comment. This UT and the following differ only for the join type. We can dedup them by doing something like:
PS nit: maybe we can also define a new
val supportedJoinTypes = Seq(Inner, LeftSemi)...There was a problem hiding this comment.
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I'm sorry for lacking of comments to your previous comment
they differ only by the join type..., they differ not only the type, but also the expected plan.