The Master is the controlling element of the Flink Cluster. It consists of three distinct components: Flink Resource Manager, Flink Dispatcher and one Flink JobManager per running Flink Job. This guide walks you through high level and fine-grained memory configurations for the Master.
The further described memory configuration is applicable starting with the release version 1.11. If you upgrade Flink from earlier versions, check the migration guide because many changes were introduced with the 1.11 release.
Note This memory setup guide is relevant only for the Master! The Master memory components have a similar but simpler structure compared to the TaskManagers’ memory configuration.
The simplest way to set up the memory configuration is to configure the total memory for the process. If you run the Master process using local execution mode you do not need to configure memory options, they will have no effect.
The following table lists all memory components, depicted above, and references Flink configuration options which affect the size of the respective components:
|Total Process Memory||
||The total process memory size for the job manager. This includes all the memory that a job manager JVM process consumes, consisting of the total Flink memory, JVM metaspace and JVM overhead.|
|Total Flink Memory||
||The total Flink memory size for the job manager. This includes all the memory that a job manager consumes, except for JVM metaspace and JVM overhead. It consists of JVM Heap and Off-heap Memory Memory.|
||JVM Heap memory size for job manager.|
||Off-heap memory size for job manager. This option covers all off-heap memory usage including direct and native memory allocation.|
||Metaspace size of the Flink JVM process|
||Native memory reserved for other JVM overhead: e.g. thread stacks, code cache, garbage collection space etc, it is a capped fractionated component of the total process memory|
As mentioned before in the total memory description, another way to set up the memory
for the Master is to specify explicitly the JVM Heap size (
It gives more control over the available JVM Heap which is used by:
The required size of JVM Heap is mostly driven by the number of running jobs, their structure, and requirements for the mentioned user code.
The Job cache resides in the JVM Heap. It can be configured by
jobstore.cache-size which must be less than the configured or derived JVM Heap size.
Note If you have configured the JVM Heap explicitly, it is recommended to set neither total process memory nor total Flink memory. Otherwise, it may easily lead to memory configuration conflicts. The Flink scripts and CLI set the JVM Heap size via the JVM parameters -Xms and -Xmx when they start the Master process, see also JVM parameters.
The Off-heap memory component accounts for any type of JVM direct memory and native memory usage. Therefore, it is also set via the corresponding JVM argument: -XX:MaxDirectMemorySize, see also JVM parameters.
The size of this component can be configured by
option. This option can be tuned e.g. if the Master process throws ‘OutOfMemoryError: Direct buffer memory’, see
the troubleshooting guide for more information.
There can be the following possible sources of Off-heap memory consumption:
If you run Flink locally (e.g. from your IDE) without creating a cluster, then the Master memory configuration options are ignored.