cloud-fan commented on code in PR #45739: URL: https://github.com/apache/spark/pull/45739#discussion_r1557699328
########## sql/core/src/test/scala/org/apache/spark/sql/TPCDSCollationQueryTestSuite.scala: ########## @@ -0,0 +1,270 @@ +/* + * 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 + +import java.nio.file.{Files, Paths} +import java.util.Locale + +import org.apache.spark.{SparkConf, SparkContext} +import org.apache.spark.sql.catalyst.util.resourceToString +import org.apache.spark.sql.internal.SQLConf +import org.apache.spark.sql.test.TestSparkSession +import org.apache.spark.tags.ExtendedSQLTest +import org.apache.spark.util.Utils + +/** + * End-to-end tests to validate TPC-DS query results against collation-aware + * modified data and queries. + * + * For each collation, table schemas are replicated into two databases in such way that in first + * DB all table columns are collated with specified collation, while the second DB collates table + * columns with case-insensitive version of the collation. Tables from first DB are then populated + * with lowercase-converted data from tpc-ds kit and tables from second DB are populated with + * randomized-case data. + * + * When running arbitrary SQL query, we convert the query to lowercase for execution + * against first DB; second DB receives original query. Results should compare equal + * ignoring case. We use this method to validate collations are working with arbitrary standard + * SQL constructs. + * + * Additionally, we perform trims on string data to properly convert it from CharType + * to StringType and do sanity checks to verify that results are non-empty as expected. + * + * To run this test suite: + * {{{ + * SPARK_TPCDS_DATA=<path of TPCDS SF=1 data> + * build/sbt "sql/testOnly *TPCDSCollationQueryTestSuite" + * }}} + * + * To run a single test file upon change: + * {{{ + * SPARK_TPCDS_DATA=<path of TPCDS SF=1 data> + * build/sbt "sql/testOnly *TPCDSCollationQueryTestSuite -- -z q79" + * }}} + */ +@ExtendedSQLTest +class TPCDSCollationQueryTestSuite extends QueryTest with TPCDSBase with SQLQueryTestHelper { + + private val tpcdsDataPath = sys.env.get("SPARK_TPCDS_DATA") + + // To make output results deterministic + override protected def sparkConf: SparkConf = super.sparkConf + .set(SQLConf.SHUFFLE_PARTITIONS.key, "1") + + protected override def createSparkSession: TestSparkSession = { + new TestSparkSession(new SparkContext("local[1]", this.getClass.getSimpleName, sparkConf)) + } + + if (tpcdsDataPath.nonEmpty) { + val nonExistentTables = tableColumns.keys.filterNot { tableName => + Files.exists(Paths.get(s"${tpcdsDataPath.get}/$tableName")) + } + if (nonExistentTables.nonEmpty) { + fail(s"Non-existent TPCDS table paths found in ${tpcdsDataPath.get}: " + + nonExistentTables.mkString(", ")) + } + } + + private def withDB[T](dbName: String)(fun: => T): T = { + Utils.tryWithSafeFinally({ + spark.sql(s"USE `$dbName`") + fun + }) { + spark.sql("USE DEFAULT") + } + } + + abstract class CollationCheck( + val dbName: String, + val collation: String, + val columnTransform: String) { + + def queryTransform: String => String + } + + case class CaseInsensitiveCollationCheck( + override val dbName: String, + override val collation: String, + override val columnTransform: String) + extends CollationCheck(dbName, collation, columnTransform) { + + override def queryTransform: String => String = identity + } + + case class CaseSensitiveCollationCheck( + override val dbName: String, + override val collation: String, + override val columnTransform: String) + extends CollationCheck(dbName, collation, columnTransform) { + + override def queryTransform: String => String = _.toLowerCase(Locale.ROOT) + } + + val collateNormalize = "COLLATE_NORMALIZE" + val randomizeCase = "RANDOMIZE_CASE" + + // List of batches of runs which should yield the same result when run on a query + val checks: Seq[Seq[CollationCheck]] = Seq( + Seq( + CaseSensitiveCollationCheck("tpcds_utf8", "UTF8_BINARY", collateNormalize), + CaseInsensitiveCollationCheck("tpcds_utf8_random", "UTF8_BINARY_LCASE", randomizeCase) + ), + Seq( + CaseSensitiveCollationCheck("tpcds_unicode", "UNICODE", collateNormalize), + CaseInsensitiveCollationCheck("tpcds_unicode_random", "UNICODE_CI", randomizeCase) + ) + ) + + override def createTables(): Unit = { + // trim collated strings with udf Review Comment: there is a `rtrim` function in Spark -- This is an automated message from the Apache Git Service. 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