Project: Flink (App Definition and Development / Streaming & Messaging)
File: application_parameters.md

title: "Handling Application Parameters" weight: 51 type: docs aliases: /dev/application_parameters.html <!-- 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. --> Handling Application Parameters Almost all Flink applications, both batch and streaming, rely on external configuration parameters. They are used to specify input and output sources (like paths or addresses), system parameters (parallelism, runtime configuration), and application specific parameters (typically used within user functions). Flink provides a simple utility called `ParameterTool` to provide some basic tooling for solving these problems. Please note that you don't have to use the `ParameterTool` described here. Other frameworks such as and also work well with Flink. The `ParameterTool` provides a set of predefined static methods for reading the configuration. The tool is internally expecting a `Map<String, String>`, so it's very easy to integrate it with your own configuration style. The following method will read a file and provide the key/value pairs: ```java String propertiesFilePath = "/home/sam/flink/myjob.properties"; ParameterTool parameters = ParameterTool.fromPropertiesFile(propertiesFilePath); File propertiesFile = new File(propertiesFilePath); ParameterTool parameters = ParameterTool.fromPropertiesFile(propertiesFile); InputStream propertiesFileInputStream = new FileInputStream(file); ParameterTool parameters = ParameterTool.fromPropertiesFile(propertiesFileInputStream); ``` This allows getting arguments like `--input hdfs:///mydata --elements 42` from the command line. ```java public static void main(String[] args) { ParameterTool parameters = ParameterTool.fromArgs(args); // .. regular code .. ``` When starting a JVM, you can pass system properties to it: `-Dinput=hdfs:///mydata`. You can also initialize the `ParameterTool` from these system properties: ```java ParameterTool parameters = ParameterTool.fromSystemProperties(); ``` Now that we've got the parameters from somewhere (see above) we can use them in various ways. Directly from the `ParameterTool` The `ParameterTool` itself has methods for accessing the values. ```java ParameterTool parameters = // ... parameters.getRequired("input"); parameters.get("output", "myDefaultValue"); parameters.getLong("expectedCount", -1L); parameters.getNumberOfParameters(); // .. there are more methods available. ``` You can use the return values of these methods directly in the `main()` method of the client submitting the application. For example, you could set the parallelism of a operator like this: ```java ParameterTool parameters = ParameterTool.fromArgs(args); int parallelism = parameters.get("mapParallelism", 2); DataStream<Tuple2<String, Integer>> counts = text.flatMap(new Tokenizer()).setParallelism(parallelism); ``` Since the `ParameterTool` is serializable, you can pass it to the functions itself: ```java ParameterTool parameters = ParameterTool.fromArgs(args); DataStream<Tuple2<String, Integer>> counts = text.flatMap(new Tokenizer(parameters)); ``` and then use it inside the function for getting values from the command line. Parameters registered as global job parameters in the `ExecutionConfig` can be accessed as configuration values from the JobManager web interface and in all functions defined by the user. Register the parameters globally: ```java ParameterTool parameters = ParameterTool.fromArgs(args); // set up the execution environment final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment(); env.getConfig().setGlobalJobParameters(parameters); ``` Access them in any rich user function: ```java public static final class Tokenizer extends RichFlatMapFunction<String, Tuple2<String, Integer>> { @Override public void flatMap(String value, Collector<Tuple2<String, Integer>> out) { ParameterTool parameters = ParameterTool.fromMap(getRuntimeContext().getGlobalJobParameters()); parameters.getRequired("input"); // .. do more .. ``` {{< top >}}