lihaosky commented on code in PR #27310: URL: https://github.com/apache/flink/pull/27310#discussion_r2670084894
########## flink-table/flink-table-planner/src/test/java/org/apache/flink/table/planner/plan/nodes/exec/batch/MLPredictBatchRestoreTest.java: ########## @@ -0,0 +1,72 @@ +/* + * 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.flink.table.planner.plan.nodes.exec.batch; + +import org.apache.flink.configuration.ConfigOption; +import org.apache.flink.table.api.config.ExecutionConfigOptions; +import org.apache.flink.table.planner.plan.nodes.exec.testutils.BatchRestoreTestBase; +import org.apache.flink.table.planner.plan.utils.ExecNodeMetadataUtil; +import org.apache.flink.table.test.program.TableTestProgram; + +import org.junit.jupiter.api.Test; + +import java.util.Arrays; +import java.util.HashSet; +import java.util.List; +import java.util.Objects; +import java.util.stream.Collectors; + +import static org.apache.flink.table.planner.plan.nodes.exec.stream.MLPredictTestPrograms.ASYNC_UNORDERED_ML_PREDICT; +import static org.apache.flink.table.planner.plan.nodes.exec.stream.MLPredictTestPrograms.SYNC_ML_PREDICT; +import static org.apache.flink.table.planner.plan.nodes.exec.stream.MLPredictTestPrograms.SYNC_ML_PREDICT_WITH_RUNTIME_CONFIG; +import static org.assertj.core.api.Assertions.assertThat; + +/** Restore tests for {@link BatchExecMLPredictTableFunction}. */ +public class MLPredictBatchRestoreTest extends BatchRestoreTestBase { + + public MLPredictBatchRestoreTest() { + super(BatchExecMLPredictTableFunction.class); + } + + @Test + public void testExecNodeMetadataContainsRequiredOptions() { + assertThat( + new HashSet<>( + Arrays.asList( + Objects.requireNonNull( + ExecNodeMetadataUtil.consumedOptions( + BatchExecMLPredictTableFunction.class))))) + .isEqualTo( + Arrays.asList( + ExecutionConfigOptions + .TABLE_EXEC_ASYNC_ML_PREDICT_MAX_CONCURRENT_OPERATIONS, + ExecutionConfigOptions.TABLE_EXEC_ASYNC_ML_PREDICT_TIMEOUT, + ExecutionConfigOptions + .TABLE_EXEC_ASYNC_ML_PREDICT_OUTPUT_MODE) + .stream() + .map(ConfigOption::key) + .collect(Collectors.toSet())); + } + + @Override + public List<TableTestProgram> programs() { + return List.of( + SYNC_ML_PREDICT, ASYNC_UNORDERED_ML_PREDICT, SYNC_ML_PREDICT_WITH_RUNTIME_CONFIG); Review Comment: These are in semantic test. I'll add a batch semantic test ########## flink-table/flink-table-planner/src/test/java/org/apache/flink/table/planner/runtime/stream/table/AsyncMLPredictITCase.java: ########## @@ -18,271 +18,36 @@ package org.apache.flink.table.planner.runtime.stream.table; -import org.apache.flink.core.testutils.FlinkAssertions; -import org.apache.flink.table.api.config.ExecutionConfigOptions; -import org.apache.flink.table.planner.factories.TestValuesModelFactory; -import org.apache.flink.table.planner.factories.TestValuesTableFactory; -import org.apache.flink.table.planner.runtime.utils.StreamingWithStateTestBase; -import org.apache.flink.testutils.junit.extensions.parameterized.ParameterizedTestExtension; -import org.apache.flink.testutils.junit.extensions.parameterized.Parameters; -import org.apache.flink.types.Row; -import org.apache.flink.util.CollectionUtil; +import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment; +import org.apache.flink.table.api.EnvironmentSettings; +import org.apache.flink.table.api.TableEnvironment; +import org.apache.flink.table.api.bridge.java.StreamTableEnvironment; +import org.apache.flink.table.planner.runtime.utils.MLPredictITCaseBase; import org.junit.jupiter.api.BeforeEach; -import org.junit.jupiter.api.TestTemplate; -import org.junit.jupiter.api.extension.ExtendWith; -import java.util.Arrays; -import java.util.Collection; -import java.util.Collections; -import java.util.HashMap; -import java.util.List; -import java.util.Map; -import java.util.concurrent.TimeoutException; +/** ITCase for async ML_PREDICT in stream mode. */ +public class AsyncMLPredictITCase extends MLPredictITCaseBase { -import static org.assertj.core.api.Assertions.assertThatList; -import static org.assertj.core.api.Assertions.assertThatThrownBy; - -/** ITCase for async ML_PREDICT. */ -@ExtendWith(ParameterizedTestExtension.class) -public class AsyncMLPredictITCase extends StreamingWithStateTestBase { - - private final Boolean objectReuse; - private final ExecutionConfigOptions.AsyncOutputMode asyncOutputMode; - - public AsyncMLPredictITCase( - StateBackendMode backend, - Boolean objectReuse, - ExecutionConfigOptions.AsyncOutputMode asyncOutputMode) { - super(backend); - - this.objectReuse = objectReuse; - this.asyncOutputMode = asyncOutputMode; - } - - private final List<Row> data = - Arrays.asList( - Row.of(1L, 12, "Julian"), - Row.of(2L, 15, "Hello"), - Row.of(3L, 15, "Fabian"), - Row.of(8L, 11, "Hello world"), - Row.of(9L, 12, "Hello world!")); - - private final List<Row> dataWithNull = - Arrays.asList( - Row.of(15L, null, "Hello"), - Row.of(3L, 15, "Fabian"), - Row.of(11L, null, "Hello world"), - Row.of(9L, 12, "Hello world!")); - - private final Map<Row, List<Row>> id2features = new HashMap<>(); - - { - id2features.put(Row.of(1L), Collections.singletonList(Row.of("x1", 1, "z1"))); - id2features.put(Row.of(2L), Collections.singletonList(Row.of("x2", 2, "z2"))); - id2features.put(Row.of(3L), Collections.singletonList(Row.of("x3", 3, "z3"))); - id2features.put(Row.of(8L), Collections.singletonList(Row.of("x8", 8, "z8"))); - id2features.put(Row.of(9L), Collections.singletonList(Row.of("x9", 9, "z9"))); - } - - private final Map<Row, List<Row>> idLen2features = new HashMap<>(); - - { - idLen2features.put( - Row.of(15L, null), Collections.singletonList(Row.of("x1", 1, "zNull15"))); - idLen2features.put(Row.of(15L, 15), Collections.singletonList(Row.of("x1", 1, "z1515"))); - idLen2features.put(Row.of(3L, 15), Collections.singletonList(Row.of("x2", 2, "z315"))); - idLen2features.put( - Row.of(11L, null), Collections.singletonList(Row.of("x3", 3, "zNull11"))); - idLen2features.put(Row.of(11L, 11), Collections.singletonList(Row.of("x3", 3, "z1111"))); - idLen2features.put(Row.of(9L, 12), Collections.singletonList(Row.of("x8", 8, "z912"))); - idLen2features.put(Row.of(12L, 12), Collections.singletonList(Row.of("x8", 8, "z1212"))); - } - - private final Map<Row, List<Row>> content2vector = new HashMap<>(); - - { - content2vector.put( - Row.of("Julian"), - Collections.singletonList(Row.of((Object) new Float[] {1.0f, 2.0f, 3.0f}))); - content2vector.put( - Row.of("Hello"), - Collections.singletonList(Row.of((Object) new Float[] {2.0f, 3.0f, 4.0f}))); - content2vector.put( - Row.of("Fabian"), - Collections.singletonList(Row.of((Object) new Float[] {3.0f, 4.0f, 5.0f}))); - content2vector.put( - Row.of("Hello world"), - Collections.singletonList(Row.of((Object) new Float[] {4.0f, 5.0f, 6.0f}))); - content2vector.put( - Row.of("Hello world!"), - Collections.singletonList(Row.of((Object) new Float[] {5.0f, 6.0f, 7.0f}))); - } + private StreamExecutionEnvironment env; @BeforeEach - public void before() { + @Override + public void before() throws Exception { + env = StreamExecutionEnvironment.getExecutionEnvironment(); + env.setParallelism(4); + env.getConfig().enableObjectReuse(); super.before(); - if (objectReuse) { - env().getConfig().enableObjectReuse(); - } else { - env().getConfig().disableObjectReuse(); - } - tEnv().getConfig() - .set( - ExecutionConfigOptions.TABLE_EXEC_ASYNC_ML_PREDICT_OUTPUT_MODE, - asyncOutputMode); - - createScanTable("src", data); - createScanTable("nullable_src", dataWithNull); - - tEnv().executeSql( - String.format( - "CREATE MODEL m1\n" - + "INPUT (a BIGINT)\n" - + "OUTPUT (x STRING, y INT, z STRING)\n" - + "WITH (\n" - + " 'provider' = 'values'," - + " 'async' = 'true'," - + " 'data-id' = '%s'" - + ")", - TestValuesModelFactory.registerData(id2features))); - tEnv().executeSql( - String.format( - "CREATE MODEL m2\n" - + "INPUT (a BIGINT, b INT)\n" - + "OUTPUT (x STRING, y INT, z STRING)\n" - + "WITH (\n" - + " 'provider' = 'values'," - + " 'async' = 'true'," - + " 'data-id' = '%s'" - + ")", - TestValuesModelFactory.registerData(idLen2features))); - tEnv().executeSql( - String.format( - "CREATE MODEL m3\n" - + "INPUT (content STRING)\n" - + "OUTPUT (vector ARRAY<FLOAT>)\n" - + "WITH (\n" - + " 'provider' = 'values'," - + " 'data-id' = '%s'," - + " 'latency' = '1000'," - + " 'async' = 'true'" - + ")", - TestValuesModelFactory.registerData(content2vector))); - } - - @TestTemplate - public void testAsyncMLPredict() { - assertThatList( - CollectionUtil.iteratorToList( - tEnv().executeSql( - "SELECT id, z FROM ML_PREDICT(TABLE src, MODEL m1, DESCRIPTOR(`id`))") - .collect())) - .containsExactlyInAnyOrder( - Row.of(1L, "z1"), - Row.of(2L, "z2"), - Row.of(3L, "z3"), - Row.of(8L, "z8"), - Row.of(9L, "z9")); - } - - @TestTemplate - public void testAsyncMLPredictWithMultipleFields() { - assertThatList( - CollectionUtil.iteratorToList( - tEnv().executeSql( - "SELECT id, len, z FROM ML_PREDICT(TABLE nullable_src, MODEL m2, DESCRIPTOR(`id`, `len`))") - .collect())) - .containsExactlyInAnyOrder( - Row.of(3L, 15, "z315"), - Row.of(9L, 12, "z912"), - Row.of(11L, null, "zNull11"), - Row.of(15L, null, "zNull15")); - } - - @TestTemplate - public void testAsyncMLPredictWithConstantValues() { - assertThatList( - CollectionUtil.iteratorToList( - tEnv().executeSql( - "WITH v(id) AS (SELECT * FROM (VALUES (CAST(1 AS BIGINT)), (CAST(2 AS BIGINT)))) " - + "SELECT * FROM ML_PREDICT(INPUT => TABLE v, MODEL => MODEL `m1`, ARGS => DESCRIPTOR(`id`))") - .collect())) - .containsExactlyInAnyOrder(Row.of(1L, "x1", 1, "z1"), Row.of(2L, "x2", 2, "z2")); - } - - @TestTemplate - public void testAsyncPredictWithRuntimeConfig() { - assertThatThrownBy( - () -> - tEnv().executeSql( - "SELECT id, vector FROM ML_PREDICT(TABLE src, MODEL m3, DESCRIPTOR(`content`), MAP['timeout', '1ms'])") - .await()) - .satisfies( - FlinkAssertions.anyCauseMatches( - TimeoutException.class, "Async function call has timed out.")); } - private void createScanTable(String tableName, List<Row> data) { - String dataId = TestValuesTableFactory.registerData(data); - tEnv().executeSql( - String.format( - "CREATE TABLE `%s`(\n" - + " id BIGINT," - + " len INT," - + " content STRING," - + " PRIMARY KEY (`id`) NOT ENFORCED" - + ") WITH (" - + " 'connector' = 'values'," - + " 'data-id' = '%s'" - + ")", - tableName, dataId)); + @Override + protected TableEnvironment getTableEnvironment() { + EnvironmentSettings settings = EnvironmentSettings.newInstance().inStreamingMode().build(); + return StreamTableEnvironment.create(env, settings); } - @Parameters(name = "backend = {0}, objectReuse = {1}, asyncOutputMode = {2}") - public static Collection<Object[]> parameters() { Review Comment: I'm following `VectorSearchITCaseBase` which doesn't have these. Probably because there's no `BatchWithStateTestBase` -- 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: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
