Skip to main content
Version: Next

Job Env Config

This document describes env configuration information, the common parameters can be used in all engines. In order to better distinguish between engine parameters, the additional parameters of other engine need to carry a prefix. In flink engine, we use flink. as the prefix. In the spark engine, we do not use any prefixes to modify parameters, because the official spark parameters themselves start with spark.

Common Parameter​

The following configuration parameters are common to all engines

job.name​

This parameter configures the task name.

jars​

Third-party packages can be loaded via jars, like jars="file://local/jar1.jar;file://local/jar2.jar"

job.mode​

You can configure whether the task is in batch mode or stream mode through job.mode, like job.mode = "BATCH" or job.mode = "STREAMING"

checkpoint.interval​

Gets the interval in which checkpoints are periodically scheduled.

In STREAMING mode, checkpoints is required, if you do not set it, it will be obtained from the application configuration file seatunnel.yaml. In BATCH mode, you can disable checkpoints by not setting this parameter.

parallelism​

This parameter configures the parallelism of source and sink.

job.retry.times​

Used to control the default retry times when a job fails. The default value is 3, and it only works in the Zeta engine.

shade.identifier​

Specify the method of encryption, if you didn't have the requirement for encrypting or decrypting config files, this option can be ignored.

For more details, you can refer to the documentation config-encryption-decryption

Here are some SeaTunnel parameter names corresponding to the names in Flink, not all of them, please refer to the official flink documentation for more.

Flink Configuration NameSeaTunnel Configuration Name
pipeline.max-parallelismflink.pipeline.max-parallelism
execution.checkpointing.modeflink.execution.checkpointing.mode
execution.checkpointing.timeoutflink.execution.checkpointing.timeout
......

Spark Engine Parameter​

Because spark configuration items have not been modified, they are not listed here, please refer to the official spark documentation.