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[SPARK-33081][SQL] Support ALTER TABLE in JDBC v2 Table Catalog: update type and nullability of columns (DB2 dialect) #29972
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113
...r-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/v2/DB2IntegrationSuite.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.jdbc.v2 | ||
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| import java.sql.Connection | ||
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| import org.scalatest.time.SpanSugar._ | ||
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| import org.apache.spark.SparkConf | ||
| import org.apache.spark.sql.AnalysisException | ||
| import org.apache.spark.sql.catalyst.parser.ParseException | ||
| import org.apache.spark.sql.execution.datasources.v2.jdbc.JDBCTableCatalog | ||
| import org.apache.spark.sql.jdbc.{DatabaseOnDocker, DockerJDBCIntegrationSuite} | ||
| import org.apache.spark.sql.test.SharedSparkSession | ||
| import org.apache.spark.sql.types._ | ||
| import org.apache.spark.tags.DockerTest | ||
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| /** | ||
| * To run this test suite for a specific version (e.g., ibmcom/db2:11.5.4.0): | ||
| * {{{ | ||
| * DB2_DOCKER_IMAGE_NAME=ibmcom/db2:11.5.4.0 | ||
| * ./build/sbt -Pdocker-integration-tests "test-only *DB2IntegrationSuite" | ||
| * }}} | ||
| */ | ||
| @DockerTest | ||
| class DB2IntegrationSuite extends DockerJDBCIntegrationSuite with SharedSparkSession { | ||
| override val db = new DatabaseOnDocker { | ||
| override val imageName = sys.env.getOrElse("DB2_DOCKER_IMAGE_NAME", "ibmcom/db2:11.5.4.0") | ||
| override val env = Map( | ||
| "DB2INST1_PASSWORD" -> "rootpass", | ||
| "LICENSE" -> "accept", | ||
| "DBNAME" -> "foo", | ||
| "ARCHIVE_LOGS" -> "false", | ||
| "AUTOCONFIG" -> "false" | ||
| ) | ||
| override val usesIpc = false | ||
| override val jdbcPort: Int = 50000 | ||
| override val privileged = true | ||
| override def getJdbcUrl(ip: String, port: Int): String = | ||
| s"jdbc:db2://$ip:$port/foo:user=db2inst1;password=rootpass;retrieveMessagesFromServerOnGetMessage=true;" //scalastyle:ignore | ||
| } | ||
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| override def sparkConf: SparkConf = super.sparkConf | ||
| .set("spark.sql.catalog.db2", classOf[JDBCTableCatalog].getName) | ||
| .set("spark.sql.catalog.db2.url", db.getJdbcUrl(dockerIp, externalPort)) | ||
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| override def dataPreparation(conn: Connection): Unit = {} | ||
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| test("SPARK-33034: ALTER TABLE ... update column type") { | ||
| withTable("db2.alt_table") { | ||
| sql("CREATE TABLE db2.alt_table (ID INTEGER) USING _") | ||
| sql("ALTER TABLE db2.alt_table ALTER COLUMN id TYPE DOUBLE") | ||
| val t = spark.table("db2.alt_table") | ||
| val expectedSchema = new StructType().add("ID", DoubleType) | ||
| assert(t.schema === expectedSchema) | ||
| // Update column type from DOUBLE to STRING | ||
| val msg1 = intercept[AnalysisException] { | ||
| sql("ALTER TABLE db2.alt_table ALTER COLUMN id TYPE VARCHAR(10)") | ||
| }.getMessage | ||
| assert(msg1.contains("Cannot update alt_table field ID: double cannot be cast to varchar")) | ||
| // Update not existing column | ||
| val msg2 = intercept[AnalysisException] { | ||
| sql("ALTER TABLE db2.alt_table ALTER COLUMN bad_column TYPE DOUBLE") | ||
| }.getMessage | ||
| assert(msg2.contains("Cannot update missing field bad_column")) | ||
| // Update column to wrong type | ||
| val msg3 = intercept[ParseException] { | ||
| sql("ALTER TABLE db2.alt_table ALTER COLUMN id TYPE bad_type") | ||
| }.getMessage | ||
| assert(msg3.contains("DataType bad_type is not supported")) | ||
| } | ||
| // Update column type in not existing table | ||
| val msg = intercept[AnalysisException] { | ||
| sql(s"ALTER TABLE db2.not_existing_table ALTER COLUMN id TYPE DOUBLE") | ||
| }.getMessage | ||
| assert(msg.contains("Table not found")) | ||
| } | ||
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| test("SPARK-33034: ALTER TABLE ... update column nullability") { | ||
| withTable("db2.alt_table") { | ||
| sql("CREATE TABLE db2.alt_table (ID STRING NOT NULL) USING _") | ||
| sql("ALTER TABLE db2.alt_table ALTER COLUMN ID DROP NOT NULL") | ||
| val t = spark.table("db2.alt_table") | ||
| val expectedSchema = new StructType().add("ID", StringType, nullable = true) | ||
| assert(t.schema === expectedSchema) | ||
| // Update nullability of not existing column | ||
| val msg = intercept[AnalysisException] { | ||
| sql("ALTER TABLE db2.alt_table ALTER COLUMN bad_column DROP NOT NULL") | ||
| }.getMessage | ||
| assert(msg.contains("Cannot update missing field bad_column")) | ||
| } | ||
| // Update column nullability in not existing table | ||
| val msg = intercept[AnalysisException] { | ||
| sql(s"ALTER TABLE db2.not_existing_table ALTER COLUMN ID DROP NOT NULL") | ||
| }.getMessage | ||
| assert(msg.contains("Table not found")) | ||
| } | ||
| } | ||
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DB2 docker test is much simpler than Oracle? aea78d2#diff-a003dfa2ba6f747fa3ac7f4563e78325R34-R54
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In Oracle docker test, it has instructions for how to build docker image. In DB2 docker test and all the other docker tests, it is assumed that the docker images are there and only has instruction for how to run the tests. That's why DB2 docker test looks much simpler.
e.g. here is what we have for MS SQL Server docker test