Flink can run on a single machine, even in a single Java Virtual Machine. This allows users to test and debug Flink programs locally. This section gives an overview of the local execution mechanisms.
The local environments and executors allow you to run Flink programs in a local Java Virtual Machine, or with within any JVM as part of existing programs. Most examples can be launched locally by simply hitting the “Run” button of your IDE.
There are two different kinds of local execution supported in Flink. The
LocalExecutionEnvironment is starting the full Flink runtime, including a JobManager and a TaskManager. These include memory management and all the internal algorithms that are executed in the cluster mode.
CollectionEnvironment is executing the Flink program on Java collections. This mode will not start the full Flink runtime, so the execution is very low-overhead and lightweight. For example a
DataSet.map()-transformation will be executed by applying the
map() function to all elements in a Java list.
If you are running Flink programs locally, you can also debug your program like any other Java program. You can either use
System.out.println() to write out some internal variables or you can use the debugger. It is possible to set breakpoints within
reduce() and all the other methods.
Please also refer to the debugging section in the Java API documentation for a guide to testing and local debugging utilities in the Java API.
If you are developing your program in a Maven project, you have to add the
flink-clients module using this dependency:
LocalEnvironment is a handle to local execution for Flink programs. Use it to run a program within a local JVM - standalone or embedded in other programs.
The local environment is instantiated via the method
ExecutionEnvironment.createLocalEnvironment(). By default, it will use as many local threads for execution as your machine has CPU cores (hardware contexts). You can alternatively specify the desired parallelism. The local environment can be configured to log to the console using
In most cases, calling
ExecutionEnvironment.getExecutionEnvironment() is the even better way to go. That method returns a
LocalEnvironment when the program is started locally (outside the command line interface), and it returns a pre-configured environment for cluster execution, when the program is invoked by the command line interface.
JobExecutionResult object, which is returned after the execution finished, contains the program runtime and the accumulator results.
LocalEnvironment allows also to pass custom configuration values to Flink.
Note: The local execution environments do not start any web frontend to monitor the execution.
The execution on Java Collections using the
CollectionEnvironment is a low-overhead approach for executing Flink programs. Typical use-cases for this mode are automated tests, debugging and code re-use.
Users can use algorithms implemented for batch processing also for cases that are more interactive. A slightly changed variant of a Flink program could be used in a Java Application Server for processing incoming requests.
Skeleton for Collection-based execution
flink-examples-batch module contains a full example, called
Please note that the execution of the collection-based Flink programs is only possible on small data, which fits into the JVM heap. The execution on collections is not multi-threaded, only one thread is used.