fix: Fallback to Spark for unsupported partitioning #759
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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.comet.exec | ||
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| import java.util.Collections | ||
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| import org.apache.spark.sql.DataFrame | ||
| import org.apache.spark.sql.connector.catalog.{Column, Identifier, InMemoryCatalog, InMemoryTableCatalog} | ||
| import org.apache.spark.sql.connector.expressions.Expressions.identity | ||
| import org.apache.spark.sql.connector.expressions.Transform | ||
| import org.apache.spark.sql.internal.SQLConf | ||
| import org.apache.spark.sql.types.{FloatType, LongType, StringType, TimestampType} | ||
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| class CometShuffle4_0Suite extends CometColumnarShuffleSuite { | ||
| override protected val asyncShuffleEnable: Boolean = false | ||
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| protected val adaptiveExecutionEnabled: Boolean = true | ||
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| override def beforeAll(): Unit = { | ||
| super.beforeAll() | ||
| spark.conf.set("spark.sql.catalog.testcat", classOf[InMemoryCatalog].getName) | ||
| } | ||
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| override def afterAll(): Unit = { | ||
| spark.sessionState.conf.unsetConf("spark.sql.catalog.testcat") | ||
| super.afterAll() | ||
| } | ||
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| private val emptyProps: java.util.Map[String, String] = { | ||
| Collections.emptyMap[String, String] | ||
| } | ||
| private val items: String = "items" | ||
| private val itemsColumns: Array[Column] = Array( | ||
| Column.create("id", LongType), | ||
| Column.create("name", StringType), | ||
| Column.create("price", FloatType), | ||
| Column.create("arrive_time", TimestampType)) | ||
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| private val purchases: String = "purchases" | ||
| private val purchasesColumns: Array[Column] = Array( | ||
| Column.create("item_id", LongType), | ||
| Column.create("price", FloatType), | ||
| Column.create("time", TimestampType)) | ||
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| protected def catalog: InMemoryCatalog = { | ||
| val catalog = spark.sessionState.catalogManager.catalog("testcat") | ||
| catalog.asInstanceOf[InMemoryCatalog] | ||
| } | ||
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| private def createTable( | ||
| table: String, | ||
| columns: Array[Column], | ||
| partitions: Array[Transform], | ||
| catalog: InMemoryTableCatalog = catalog): Unit = { | ||
| catalog.createTable(Identifier.of(Array("ns"), table), columns, partitions, emptyProps) | ||
|
There was a problem hiding this comment. Some APIs are added since Spark 3.4. One config is added since Spark 4.0. So this test is only compilable for 3.4+ and only useful for 4.0. |
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| } | ||
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| private def selectWithMergeJoinHint(t1: String, t2: String): String = { | ||
| s"SELECT /*+ MERGE($t1, $t2) */ " | ||
| } | ||
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| private def createJoinTestDF( | ||
| keys: Seq[(String, String)], | ||
| extraColumns: Seq[String] = Nil, | ||
| joinType: String = ""): DataFrame = { | ||
| val extraColList = if (extraColumns.isEmpty) "" else extraColumns.mkString(", ", ", ", "") | ||
| sql(s""" | ||
| |${selectWithMergeJoinHint("i", "p")} | ||
| |id, name, i.price as purchase_price, p.price as sale_price $extraColList | ||
| |FROM testcat.ns.$items i $joinType JOIN testcat.ns.$purchases p | ||
| |ON ${keys.map(k => s"i.${k._1} = p.${k._2}").mkString(" AND ")} | ||
| |ORDER BY id, purchase_price, sale_price $extraColList | ||
| |""".stripMargin) | ||
| } | ||
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| test("Fallback to Spark for unsupported partitioning") { | ||
| val items_partitions = Array(identity("id")) | ||
| createTable(items, itemsColumns, items_partitions) | ||
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| sql( | ||
| s"INSERT INTO testcat.ns.$items VALUES " + | ||
| "(1, 'aa', 40.0, cast('2020-01-01' as timestamp)), " + | ||
| "(3, 'bb', 10.0, cast('2020-01-01' as timestamp)), " + | ||
| "(4, 'cc', 15.5, cast('2020-02-01' as timestamp))") | ||
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| createTable(purchases, purchasesColumns, Array.empty) | ||
| sql( | ||
| s"INSERT INTO testcat.ns.$purchases VALUES " + | ||
| "(1, 42.0, cast('2020-01-01' as timestamp)), " + | ||
| "(3, 19.5, cast('2020-02-01' as timestamp)), " + | ||
| "(5, 26.0, cast('2023-01-01' as timestamp)), " + | ||
| "(6, 50.0, cast('2023-02-01' as timestamp))") | ||
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| Seq(true, false).foreach { shuffle => | ||
| withSQLConf( | ||
| SQLConf.V2_BUCKETING_ENABLED.key -> "true", | ||
| "spark.sql.sources.v2.bucketing.shuffle.enabled" -> shuffle.toString, | ||
| SQLConf.V2_BUCKETING_PUSH_PART_VALUES_ENABLED.key -> "true", | ||
| SQLConf.V2_BUCKETING_PARTIALLY_CLUSTERED_DISTRIBUTION_ENABLED.key -> "true") { | ||
| val df = createJoinTestDF(Seq("id" -> "item_id")) | ||
| checkSparkAnswer(df) | ||
| } | ||
| } | ||
| } | ||
| } | ||
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nit
s.outputPartitioning=>outputPartitioningThere was a problem hiding this comment.
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Okay.