wombatu-kun commented on code in PR #19217: URL: https://github.com/apache/hudi/pull/19217#discussion_r3695303480
########## hudi-integ-test/src/test/java/org/apache/hudi/integ2/testcontainers/trino/ITTestTrinoCustomType.java: ########## @@ -0,0 +1,369 @@ +/* + * 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.hudi.integ2.testcontainers.trino; + +import org.apache.hudi.integ2.testcontainers.ITTestBaseTestcontainers; +import org.apache.hudi.integ2.testcontainers.ITTestCustomTypeHiveSync; + +import org.junit.jupiter.api.AfterAll; +import org.junit.jupiter.api.BeforeAll; +import org.junit.jupiter.api.Test; +import org.junit.jupiter.api.TestInstance; + +import static org.apache.hudi.integ2.testcontainers.TestcontainersConfig.Paths; + +/** + * Trino read coverage for Hudi's custom logical types (BLOB struct, VECTOR + * fixed_len_byte_array, VARIANT), complementing {@link ITTestCustomTypeHiveSync} + * which asserts the same fixtures round-trip through the Hive serde. A flip in + * either direction (e.g. VECTOR decoded as array<float> instead of + * binary, BLOB struct field projection broken, VARIANT row count off) shows up + * here. + * + * <p>This test reuses the same {@code sparksql-*-sql.commands} fixtures that + * {@code ITTestCustomTypeHiveSync} drives, so the two tests can run in either + * order without cross-contamination (each has its own {@code @BeforeAll} that + * re-seeds, and an {@code @AfterAll} that cleans up). + * + * <p>VARIANT seeding and tests only fire on a Spark 4.x compose; on Spark 3.5 + * the BLOB and VECTOR coverage still runs. + */ +@TestInstance(TestInstance.Lifecycle.PER_CLASS) +public class ITTestTrinoCustomType extends ITTestBaseTestcontainers { + + private static final String BLOB_TEST_PATH = "/user/hive/warehouse/blob_test"; + private static final String BLOB_TEST_DF_PATH = "/user/hive/warehouse/blob_test_df"; + private static final String VECTOR_TEST_PATH = "/user/hive/warehouse/vector_test"; + private static final String VARIANT_TEST_PATH = "/user/hive/warehouse/variant_test"; + private static final String SPARKSQL_BLOB_TYPE_SQL_COMMANDS = + Paths.DEMO_DIR + "/sparksql-blob-type-sql.commands"; + private static final String SPARKSQL_BLOB_TYPE_DF_COMMANDS = + Paths.DEMO_DIR + "/sparksql-blob-type-df.commands"; + private static final String SPARKSQL_VECTOR_TYPE_SQL_COMMANDS = + Paths.DEMO_DIR + "/sparksql-vector-type-sql.commands"; + private static final String SPARKSQL_VARIANT_TYPE_SQL_COMMANDS = + Paths.DEMO_DIR + "/sparksql-variant-type-sql.commands"; + + @BeforeAll + public void setupOnce() throws Exception { + assumeTrinoProfile(); + initializeServices(); + waitForHdfs(); + sparkAdhoc1.executeShellCommand("/bin/bash " + Paths.DEMO_SETUP).expectToSucceed(); + sparkAdhoc1.executeSQLFile(SPARKSQL_BLOB_TYPE_SQL_COMMANDS) + .expectToSucceed() + .assertStdOutContainsLine("BLOB_SQL_TEST_SUCCESS"); + // The DF fixture writes blob_test_df with the INLINE branch of the BLOB struct + // (data field non-null, reference null). The SQL fixture exercises only the + // OUT_OF_LINE branch, so seeding both gives Trino read coverage of both shapes. + sparkAdhoc1.executeSQLFile(SPARKSQL_BLOB_TYPE_DF_COMMANDS) + .expectToSucceed() + .assertStdOutContainsLine("BLOB_DF_TEST_SUCCESS"); + sparkAdhoc1.executeSQLFile(SPARKSQL_VECTOR_TYPE_SQL_COMMANDS) + .expectToSucceed() + .assertStdOutContainsLine("VECTOR_SQL_TEST_SUCCESS"); + if (isSpark4Compose()) { + // VARIANT type is Spark 4.x only - guard the seed so the BLOB/VECTOR + // coverage still runs on a Spark 3.5 stack. + sparkAdhoc1.executeSQLFile(SPARKSQL_VARIANT_TYPE_SQL_COMMANDS) + .expectToSucceed() + .assertStdOutContainsLine("VARIANT_SQL_TEST_SUCCESS"); + } + trino.waitUntilReady(); + } + + @AfterAll + public void clean() throws Exception { + // -f silently skips non-existent paths so the variant_test cleanup is safe + // even on Spark 3.5 runs where the table was never created. + sparkAdhoc1.executeShellCommand("hdfs dfs -rm -R -f " Review Comment: `clean` runs even when `assumeTrinoProfile` aborted `setupOnce` - JUnit invokes `@AfterAll` regardless - so `sparkAdhoc1` is still null and the intended skip surfaces as an NPE failure, same in `ITTestTrinoStockTicks`. Early-return from `clean` when `sparkAdhoc1` is null. ########## hudi-integ-test/src/test/java/org/apache/hudi/integ2/testcontainers/trino/ITTestTrinoCustomType.java: ########## @@ -0,0 +1,369 @@ +/* + * 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.hudi.integ2.testcontainers.trino; + +import org.apache.hudi.integ2.testcontainers.ITTestBaseTestcontainers; +import org.apache.hudi.integ2.testcontainers.ITTestCustomTypeHiveSync; + +import org.junit.jupiter.api.AfterAll; +import org.junit.jupiter.api.BeforeAll; +import org.junit.jupiter.api.Test; +import org.junit.jupiter.api.TestInstance; + +import static org.apache.hudi.integ2.testcontainers.TestcontainersConfig.Paths; + +/** + * Trino read coverage for Hudi's custom logical types (BLOB struct, VECTOR + * fixed_len_byte_array, VARIANT), complementing {@link ITTestCustomTypeHiveSync} + * which asserts the same fixtures round-trip through the Hive serde. A flip in + * either direction (e.g. VECTOR decoded as array<float> instead of + * binary, BLOB struct field projection broken, VARIANT row count off) shows up + * here. + * + * <p>This test reuses the same {@code sparksql-*-sql.commands} fixtures that + * {@code ITTestCustomTypeHiveSync} drives, so the two tests can run in either + * order without cross-contamination (each has its own {@code @BeforeAll} that + * re-seeds, and an {@code @AfterAll} that cleans up). + * + * <p>VARIANT seeding and tests only fire on a Spark 4.x compose; on Spark 3.5 + * the BLOB and VECTOR coverage still runs. + */ +@TestInstance(TestInstance.Lifecycle.PER_CLASS) +public class ITTestTrinoCustomType extends ITTestBaseTestcontainers { + + private static final String BLOB_TEST_PATH = "/user/hive/warehouse/blob_test"; + private static final String BLOB_TEST_DF_PATH = "/user/hive/warehouse/blob_test_df"; + private static final String VECTOR_TEST_PATH = "/user/hive/warehouse/vector_test"; + private static final String VARIANT_TEST_PATH = "/user/hive/warehouse/variant_test"; + private static final String SPARKSQL_BLOB_TYPE_SQL_COMMANDS = + Paths.DEMO_DIR + "/sparksql-blob-type-sql.commands"; + private static final String SPARKSQL_BLOB_TYPE_DF_COMMANDS = + Paths.DEMO_DIR + "/sparksql-blob-type-df.commands"; + private static final String SPARKSQL_VECTOR_TYPE_SQL_COMMANDS = + Paths.DEMO_DIR + "/sparksql-vector-type-sql.commands"; + private static final String SPARKSQL_VARIANT_TYPE_SQL_COMMANDS = + Paths.DEMO_DIR + "/sparksql-variant-type-sql.commands"; + + @BeforeAll + public void setupOnce() throws Exception { + assumeTrinoProfile(); + initializeServices(); + waitForHdfs(); + sparkAdhoc1.executeShellCommand("/bin/bash " + Paths.DEMO_SETUP).expectToSucceed(); + sparkAdhoc1.executeSQLFile(SPARKSQL_BLOB_TYPE_SQL_COMMANDS) + .expectToSucceed() + .assertStdOutContainsLine("BLOB_SQL_TEST_SUCCESS"); + // The DF fixture writes blob_test_df with the INLINE branch of the BLOB struct + // (data field non-null, reference null). The SQL fixture exercises only the + // OUT_OF_LINE branch, so seeding both gives Trino read coverage of both shapes. + sparkAdhoc1.executeSQLFile(SPARKSQL_BLOB_TYPE_DF_COMMANDS) + .expectToSucceed() + .assertStdOutContainsLine("BLOB_DF_TEST_SUCCESS"); + sparkAdhoc1.executeSQLFile(SPARKSQL_VECTOR_TYPE_SQL_COMMANDS) + .expectToSucceed() + .assertStdOutContainsLine("VECTOR_SQL_TEST_SUCCESS"); + if (isSpark4Compose()) { + // VARIANT type is Spark 4.x only - guard the seed so the BLOB/VECTOR + // coverage still runs on a Spark 3.5 stack. + sparkAdhoc1.executeSQLFile(SPARKSQL_VARIANT_TYPE_SQL_COMMANDS) + .expectToSucceed() + .assertStdOutContainsLine("VARIANT_SQL_TEST_SUCCESS"); + } + trino.waitUntilReady(); + } + + @AfterAll + public void clean() throws Exception { + // -f silently skips non-existent paths so the variant_test cleanup is safe + // even on Spark 3.5 runs where the table was never created. + sparkAdhoc1.executeShellCommand("hdfs dfs -rm -R -f " Review Comment: +1 -- This is an automated message from the Apache Git Service. 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