Github user zohar-mizrahi commented on a diff in the pull request: https://github.com/apache/flink/pull/3838#discussion_r132843982 --- Diff: flink-libraries/flink-streaming-python/src/main/java/org/apache/flink/streaming/python/api/environment/PythonStreamExecutionEnvironment.java --- @@ -0,0 +1,421 @@ +/* + * 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.streaming.python.api.environment; + +import org.apache.flink.annotation.PublicEvolving; +import org.apache.flink.api.common.JobExecutionResult; +import org.apache.flink.api.common.cache.DistributedCache; +import org.apache.flink.api.java.tuple.Tuple2; +import org.apache.flink.api.java.typeutils.TypeExtractor; +import org.apache.flink.configuration.Configuration; +import org.apache.flink.core.fs.FileSystem; +import org.apache.flink.core.fs.Path; +import org.apache.flink.runtime.filecache.FileCache; +import org.apache.flink.streaming.api.CheckpointingMode; +import org.apache.flink.streaming.api.environment.LocalStreamEnvironment; +import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment; +import org.apache.flink.streaming.api.functions.source.SourceFunction; +import org.apache.flink.streaming.python.api.datastream.PythonDataStream; +import org.apache.flink.streaming.python.api.functions.PythonGeneratorFunction; +import org.apache.flink.streaming.python.api.functions.PythonIteratorFunction; +import org.apache.flink.streaming.python.api.functions.UtilityFunctions; +import org.apache.flink.streaming.python.util.serialization.PyObjectSerializer; +import org.python.core.PyObject; +import org.python.core.PyString; +import org.python.core.PyInteger; +import org.python.core.PyLong; +import org.python.core.PyUnicode; +import org.python.core.PyTuple; +import org.python.core.PyObjectDerived; +import org.python.core.PyInstance; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.io.IOException; +import java.net.URI; +import java.net.URISyntaxException; +import java.nio.file.Paths; +import java.util.Collection; +import java.util.Iterator; +import java.util.Random; + + +/** + * A thin wrapper layer over {@link StreamExecutionEnvironment}. + * + * <p>The PythonStreamExecutionEnvironment is the context in which a streaming program is executed. + * </p> + * + * <p>The environment provides methods to control the job execution (such as setting the parallelism + * or the fault tolerance/checkpointing parameters) and to interact with the outside world + * (data access).</p> + */ +@PublicEvolving +public class PythonStreamExecutionEnvironment { + private static final Logger LOG = LoggerFactory.getLogger(PythonStreamExecutionEnvironment.class); + private final StreamExecutionEnvironment env; + + /** + * A thin wrapper layer over {@link StreamExecutionEnvironment#getExecutionEnvironment()}. In addition it takes + * care for required Jython serializers registration. + * + * @return The python execution environment of the context in which the program is + * executed. + */ + public static PythonStreamExecutionEnvironment get_execution_environment() { + return new PythonStreamExecutionEnvironment(StreamExecutionEnvironment.getExecutionEnvironment()); + } + + /** + * Creates a {@link LocalStreamEnvironment}. The local execution environment + * will run the program in a multi-threaded fashion in the same JVM as the + * environment was created in. The default parallelism of the local + * environment is the number of hardware contexts (CPU cores / threads), + * unless it was specified differently by {@link #setParallelism(int)}. + * + * @param configuration + * Pass a custom configuration into the cluster + * @return A local execution environment with the specified parallelism. + */ + public static PythonStreamExecutionEnvironment create_local_execution_environment(Configuration config) { + return new PythonStreamExecutionEnvironment(new LocalStreamEnvironment(config)); + } + + /** + * A thin wrapper layer over {@link StreamExecutionEnvironment#createLocalEnvironment(int, Configuration)} + * + * @param parallelism + * The parallelism for the local environment. + * @param config + * Pass a custom configuration into the cluster + * @return A local python execution environment with the specified parallelism. + */ + public static PythonStreamExecutionEnvironment create_local_execution_environment(int parallelism, Configuration config) { + return new PythonStreamExecutionEnvironment( + StreamExecutionEnvironment.createLocalEnvironment(parallelism, config)); + } + + /** + * A thin wrapper layer over {@link StreamExecutionEnvironment#createRemoteEnvironment(java.lang.String, int, java.lang.String...)} + * + * @param host + * The host name or address of the master (JobManager), where the + * program should be executed. + * @param port + * The port of the master (JobManager), where the program should + * be executed. + * @param jar_files + * The JAR files with code that needs to be shipped to the + * cluster. If the program uses user-defined functions, + * user-defined input formats, or any libraries, those must be + * provided in the JAR files. + * @return A remote environment that executes the program on a cluster. + */ + public static PythonStreamExecutionEnvironment create_remote_execution_environment( + String host, int port, String... jar_files) { + return new PythonStreamExecutionEnvironment( + StreamExecutionEnvironment.createRemoteEnvironment(host, port, jar_files)); + } + + /** + * A thin wrapper layer over {@link StreamExecutionEnvironment#createRemoteEnvironment( + * java.lang.String, int, Configuration, java.lang.String...)} + * + * @param host + * The host name or address of the master (JobManager), where the + * program should be executed. + * @param port + * The port of the master (JobManager), where the program should + * be executed. + * @param config + * The configuration used by the client that connects to the remote cluster. + * @param jar_files + * The JAR files with code that needs to be shipped to the + * cluster. If the program uses user-defined functions, + * user-defined input formats, or any libraries, those must be + * provided in the JAR files. + * @return A remote environment that executes the program on a cluster. + * + */ + public static PythonStreamExecutionEnvironment create_remote_execution_environment( + String host, int port, Configuration config, String... jar_files) { + return new PythonStreamExecutionEnvironment( + StreamExecutionEnvironment.createRemoteEnvironment(host, port, config, jar_files)); + } + + /** + * A thin wrapper layer over {@link StreamExecutionEnvironment#createRemoteEnvironment( + * java.lang.String, int, int, java.lang.String...)} + * + * @param host + * The host name or address of the master (JobManager), where the + * program should be executed. + * @param port + * The port of the master (JobManager), where the program should + * be executed. + * @param parallelism + * The parallelism to use during the execution. + * @param jar_files + * The JAR files with code that needs to be shipped to the + * cluster. If the program uses user-defined functions, + * user-defined input formats, or any libraries, those must be + * provided in the JAR files. + * @return A remote environment that executes the program on a cluster. + */ + public static PythonStreamExecutionEnvironment create_remote_execution_environment( + String host, int port, int parallelism, String... jar_files) { + return new PythonStreamExecutionEnvironment( + StreamExecutionEnvironment.createRemoteEnvironment(host, port, parallelism, jar_files)); + } + + private PythonStreamExecutionEnvironment(StreamExecutionEnvironment env) { + this.env = env; + this.registerJythonSerializers(); + } + + private void registerJythonSerializers() { + this.env.registerTypeWithKryoSerializer(PyString.class, PyObjectSerializer.class); + this.env.registerTypeWithKryoSerializer(PyInteger.class, PyObjectSerializer.class); + this.env.registerTypeWithKryoSerializer(PyLong.class, PyObjectSerializer.class); + this.env.registerTypeWithKryoSerializer(PyUnicode.class, PyObjectSerializer.class); + this.env.registerTypeWithKryoSerializer(PyTuple.class, PyObjectSerializer.class); + this.env.registerTypeWithKryoSerializer(PyObjectDerived.class, PyObjectSerializer.class); + this.env.registerTypeWithKryoSerializer(PyInstance.class, PyObjectSerializer.class); + } + + public PythonDataStream create_python_source(SourceFunction<Object> src) throws Exception { --- End diff -- Probably yes. All Jython user-defined functions/Classes are generated under `org.python.proxies` scope. So, using the class canonical name, we can identify these functions. WDYT?
--- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---