RussellSpitzer commented on a change in pull request #2757: URL: https://github.com/apache/iceberg/pull/2757#discussion_r664655115
########## File path: spark3/src/test/java/org/apache/iceberg/spark/sql/TestTimestampWithoutZone.java ########## @@ -0,0 +1,193 @@ +/* + * 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.iceberg.spark.sql; + +import java.sql.Timestamp; +import java.util.Arrays; +import java.util.List; +import java.util.Map; +import java.util.stream.Collectors; +import org.apache.iceberg.AssertHelpers; +import org.apache.iceberg.Schema; +import org.apache.iceberg.Table; +import org.apache.iceberg.catalog.TableIdentifier; +import org.apache.iceberg.relocated.com.google.common.base.Joiner; +import org.apache.iceberg.relocated.com.google.common.collect.ImmutableList; +import org.apache.iceberg.relocated.com.google.common.collect.ImmutableMap; +import org.apache.iceberg.spark.SparkCatalogTestBase; +import org.apache.iceberg.spark.SparkSessionCatalog; +import org.apache.iceberg.spark.SparkUtil; +import org.apache.iceberg.types.Type; +import org.apache.iceberg.types.Types; +import org.apache.spark.sql.util.CaseInsensitiveStringMap; +import org.joda.time.DateTime; +import org.junit.After; +import org.junit.Assert; +import org.junit.Before; +import org.junit.Test; +import org.junit.runners.Parameterized; + +public class TestTimestampWithoutZone extends SparkCatalogTestBase { + + private static final String newTableName = "created_table"; + private final Map<String, String> config; + + private static final Schema schema = new Schema( + Types.NestedField.required(1, "id", Types.LongType.get()), + Types.NestedField.required(2, "ts", Types.TimestampType.withoutZone()), + Types.NestedField.required(3, "tsz", Types.TimestampType.withZone()) + ); + + private final List<Object[]> values = ImmutableList.of( + row(1L, toTimestamp("2021-01-01T00:00:00.0"), toTimestamp("2021-02-01T00:00:00.0")), + row(2L, toTimestamp("2021-01-01T00:00:00.0"), toTimestamp("2021-02-01T00:00:00.0")), + row(3L, toTimestamp("2021-01-01T00:00:00.0"), toTimestamp("2021-02-01T00:00:00.0")) + ); + + @Parameterized.Parameters(name = "catalogName = {0}, implementation = {1}, config = {2}") + public static Object[][] parameters() { + return new Object[][]{{"spark_catalog", + SparkSessionCatalog.class.getName(), + ImmutableMap.of( + "type", "hive", + "default-namespace", "default", + "parquet-enabled", "true", + "cache-enabled", "false" + )} + }; + } + + public TestTimestampWithoutZone(String catalogName, String implementation, Map<String, String> config) { + super(catalogName, implementation, config); + this.config = config; + } + + @Before + public void createTables() { + spark.conf().set(SparkUtil.HANDLE_TIMESTAMP_WITHOUT_TIMEZONE, "false"); + validationCatalog.createTable(tableIdent, schema); + } + + @After + public void removeTables() { + validationCatalog.dropTable(tableIdent, true); + sql("DROP TABLE IF EXISTS %s", newTableName); + } + + @Test + public void testWriteTimestampWithoutZoneError() { + String errorMessage = String.format("Write operation performed on a timestamp without timezone field while " + + "'%s' set to false should throw exception", SparkUtil.HANDLE_TIMESTAMP_WITHOUT_TIMEZONE); + Runnable insert = () -> sql("INSERT INTO %s VALUES %s", tableName, rowToSqlValues(values)); Review comment: Instead of using the rowToSqlValues function, it may be simpler to just do a spark.createDataset(values).write command. That way we don't have to worry about string building -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: issues-unsubscr...@iceberg.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@iceberg.apache.org For additional commands, e-mail: issues-h...@iceberg.apache.org
