Using Gradle
This documentation is for an unreleased version of Apache Flink. We recommend you use the latest stable version.

How to use Gradle to configure your project #

You will likely need a build tool to configure your Flink project. This guide will show you how to do so with Gradle, an open-source general-purpose build tool that can be used to automate tasks in the development process.

Requirements #

  • Gradle 7.x
  • Java 11

Importing the project into your IDE #

Once the project folder and files have been created, we recommend that you import this project into your IDE for developing and testing.

IntelliJ IDEA supports Gradle projects via the Gradle plugin.

Eclipse does so via the Eclipse Buildship plugin (make sure to specify a Gradle version >= 3.0 in the last step of the import wizard; the shadow plugin requires it). You may also use Gradle’s IDE integration to create project files with Gradle.

Note: The default JVM heap size for Java may be too small for Flink and you have to manually increase it. In Eclipse, choose Run Configurations -> Arguments and write into the VM Arguments box: -Xmx800m. In IntelliJ IDEA recommended way to change JVM options is from the Help | Edit Custom VM Options menu. See this article for details.

Note on IntelliJ: To make the applications run within IntelliJ IDEA, it is necessary to tick the Include dependencies with "Provided" scope box in the run configuration. If this option is not available (possibly due to using an older IntelliJ IDEA version), then a workaround is to create a test that calls the application’s main() method.

Building the project #

If you want to build/package your project, go to your project directory and run the ‘gradle clean shadowJar’ command. You will find a JAR file that contains your application, plus connectors and libraries that you may have added as dependencies to the application: build/libs/<project-name>-<version>-all.jar.

Note: If you use a different class than StreamingJob as the application’s main class / entry point, we recommend you change the mainClassName setting in the build.gradle file accordingly. That way, Flink can run the application from the JAR file without additionally specifying the main class.

Adding dependencies to the project #

Specify a dependency configuration in the dependencies block of your build.gradle file.

For example, if you created your project using our Gradle build script or quickstart script, you can add the Kafka connector as a dependency like this:

build.gradle

...
dependencies {
    ...  
    flinkShadowJar "org.apache.flink:flink-connector-kafka:${flinkVersion}"
    ...
}
...

Important: Note that all these (core) dependencies should have their scope set to provided. This means that they are needed to compile against, but that they should not be packaged into the project’s resulting application JAR file. If not set to provided, the best case scenario is that the resulting JAR becomes excessively large, because it also contains all Flink core dependencies. The worst case scenario is that the Flink core dependencies that are added to the application’s JAR file clash with some of your own dependency versions (which is normally avoided through inverted classloading).

To correctly package the dependencies into the application JAR, these application dependencies must be set to the compile scope.

Packaging the application #

Depending on your use case, you may need to package your Flink application in different ways before it gets deployed to a Flink environment.

If you want to create a JAR for a Flink Job and use only Flink dependencies without any third-party dependencies (i.e. using the filesystem connector with JSON format), you do not need to create an uber/fat JAR or shade any dependencies.

You can use the command gradle clean installDist. If you are using a Gradle Wrapper, this would be ./gradlew clean installDist.

If you want to create a JAR for a Flink Job and use external dependencies not built into the Flink distribution, you can either add them to the classpath of the distribution or shade them into your uber/fat application JAR.

You can use the command gradle clean installShadowDist, which will produce a single fat JAR in /build/install/yourProject/lib. If you are using a Gradle Wrapper, this would be ./gradlew clean installShadowDist.

With the generated uber/fat JAR, you can submit it to a local or remote cluster with:

bin/flink run -c org.example.MyJob myFatJar.jar

To learn more about how to deploy Flink jobs, check out the deployment guide.