docs/ops/cli.zh.md

title: “命令行界面” nav-title: CLI nav-parent_id: ops nav-pos: 6

Flink provides a Command-Line Interface (CLI) to run programs that are packaged as JAR files, and control their execution. The CLI is part of any Flink setup, available in local single node setups and in distributed setups. It is located under <flink-home>/bin/flink and connects by default to the running Flink master (JobManager) that was started from the same installation directory.

The command line can be used to

submit jobs for execution,
cancel a running job,
provide information about a job,
list running and waiting jobs,
trigger and dispose savepoints, and

A prerequisite to using the command line interface is that the Flink master (JobManager) has been started (via <flink-home>/bin/start-cluster.sh) or that a YARN environment is available.

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Examples

作业提交示例

这些示例是关于如何通过脚本提交一个作业

Run example program with no arguments:

./bin/flink run ./examples/batch/WordCount.jar

Run example program with arguments for input and result files:

./bin/flink run ./examples/batch/WordCount.jar \
                     --input file:///home/user/hamlet.txt --output file:///home/user/wordcount_out

Run example program with parallelism 16 and arguments for input and result files:

./bin/flink run -p 16 ./examples/batch/WordCount.jar \
                     --input file:///home/user/hamlet.txt --output file:///home/user/wordcount_out

Run example program with flink log output disabled:

    ./bin/flink run -q ./examples/batch/WordCount.jar

Run example program in detached mode:

    ./bin/flink run -d ./examples/batch/WordCount.jar

Run example program on a specific JobManager:

./bin/flink run -m myJMHost:8081 \
                       ./examples/batch/WordCount.jar \
                       --input file:///home/user/hamlet.txt --output file:///home/user/wordcount_out

Run example program with a specific class as an entry point:

./bin/flink run -c org.apache.flink.examples.java.wordcount.WordCount \
                       ./examples/batch/WordCount.jar \
                       --input file:///home/user/hamlet.txt --output file:///home/user/wordcount_out

Run example program using a per-job YARN cluster with 2 TaskManagers:

./bin/flink run -m yarn-cluster  \
                       ./examples/batch/WordCount.jar \
                       --input hdfs:///user/hamlet.txt --output hdfs:///user/wordcount_out

提交一个Python Table的作业:
```
./bin/flink run -py WordCount.py
```

提交一个有多个依赖的Python Table的作业:

./bin/flink run -py examples/python/table/batch/word_count.py \
                        -pyfs file:///user.txt,hdfs:///$namenode_address/username.txt

提交一个有多个依赖的Python Table的作业，Python作业的主入口通过pym选项指定:
```
./bin/flink run -pym batch.word_count -pyfs examples/python/table/batch
```

提交一个指定并发度为16的Python Table的作业:

./bin/flink run -p 16 -py examples/python/table/batch/word_count.py

提交一个关闭flink日志输出的Python Table的作业:

./bin/flink run -q -py examples/python/table/batch/word_count.py

提交一个运行在detached模式下的Python Table的作业:

./bin/flink run -d -py examples/python/table/batch/word_count.py

提交一个运行在指定JobManager上的Python Table的作业:

./bin/flink run -m myJMHost:8081 \
                    -py examples/python/table/batch/word_count.py

提交一个运行在有两个TaskManager的per-job YARN cluster的Python Table的作业:

./bin/flink run -m yarn-cluster \
                         -py examples/python/table/batch/word_count.py

作业管理示例

Display the optimized execution plan for the WordCount example program as JSON:

./bin/flink info ./examples/batch/WordCount.jar \
                        --input file:///home/user/hamlet.txt --output file:///home/user/wordcount_out

List scheduled and running jobs (including their JobIDs):
```
./bin/flink list
```
List scheduled jobs (including their JobIDs):
```
./bin/flink list -s
```
List running jobs (including their JobIDs):
```
./bin/flink list -r
```
List all existing jobs (including their JobIDs):
```
./bin/flink list -a
```

List running Flink jobs inside Flink YARN session:

./bin/flink list -m yarn-cluster -yid <yarnApplicationID> -r

Cancel a job:
```
./bin/flink cancel <jobID>
```
Cancel a job with a savepoint (deprecated; use “stop” instead):
```
./bin/flink cancel -s [targetDirectory] <jobID>
```
Gracefully stop a job with a savepoint (streaming jobs only):
```
./bin/flink stop [-p targetDirectory] [-d] <jobID>
```

Savepoints

Savepoints are controlled via the command line client:

Trigger a Savepoint

{% highlight bash %} ./bin/flink savepoint [savepointDirectory] {% endhighlight %}

This will trigger a savepoint for the job with ID jobId, and returns the path of the created savepoint. You need this path to restore and dispose savepoints.

Furthermore, you can optionally specify a target file system directory to store the savepoint in. The directory needs to be accessible by the JobManager.

If you don't specify a target directory, you need to have configured a default directory. Otherwise, triggering the savepoint will fail.

Trigger a Savepoint with YARN

{% highlight bash %} ./bin/flink savepoint [savepointDirectory] -yid {% endhighlight %}

This will trigger a savepoint for the job with ID jobId and YARN application ID yarnAppId, and returns the path of the created savepoint.

Everything else is the same as described in the above Trigger a Savepoint section.

Stop

Use the stop to gracefully stop a running streaming job with a savepoint.

{% highlight bash %} ./bin/flink stop [-p targetDirectory] [-d] {% endhighlight %}

A “stop” call is a more graceful way of stopping a running streaming job, as the “stop” signal flows from source to sink. When the user requests to stop a job, all sources will be requested to send the last checkpoint barrier that will trigger a savepoint, and after the successful completion of that savepoint, they will finish by calling their cancel() method. If the -d flag is specified, then a MAX_WATERMARK will be emitted before the last checkpoint barrier. This will result all registered event-time timers to fire, thus flushing out any state that is waiting for a specific watermark, e.g. windows. The job will keep running until all sources properly shut down. This allows the job to finish processing all in-flight data.

Cancel with a savepoint (deprecated)

You can atomically trigger a savepoint and cancel a job.

{% highlight bash %} ./bin/flink cancel -s [savepointDirectory] {% endhighlight %}

If no savepoint directory is configured, you need to configure a default savepoint directory for the Flink installation (see Savepoints).

The job will only be cancelled if the savepoint succeeds.

Restore a savepoint

{% highlight bash %} ./bin/flink run -s ... {% endhighlight %}

The run command has a savepoint flag to submit a job, which restores its state from a savepoint. The savepoint path is returned by the savepoint trigger command.

By default, we try to match all savepoint state to the job being submitted. If you want to allow to skip savepoint state that cannot be restored with the new job you can set the allowNonRestoredState flag. You need to allow this if you removed an operator from your program that was part of the program when the savepoint was triggered and you still want to use the savepoint.

{% highlight bash %} ./bin/flink run -s -n ... {% endhighlight %}

This is useful if your program dropped an operator that was part of the savepoint.

Dispose a savepoint

{% highlight bash %} ./bin/flink savepoint -d {% endhighlight %}

Disposes the savepoint at the given path. The savepoint path is returned by the savepoint trigger command.

If you use custom state instances (for example custom reducing state or RocksDB state), you have to specify the path to the program JAR with which the savepoint was triggered in order to dispose the savepoint with the user code class loader:

{% highlight bash %} ./bin/flink savepoint -d -j {% endhighlight %}

Otherwise, you will run into a ClassNotFoundException.

Usage

The command line syntax is as follows:

{% highlight bash %} ./flink [OPTIONS] [ARGUMENTS]

The following actions are available:

Action “run” compiles and runs a program.

Syntax: run [OPTIONS] “run” action options: -c,--class Class with the program entry point (“main()” method or “getPlan()” method). Only needed if the JAR file does not specify the class in its manifest. -C,--classpath Adds a URL to each user code classloader on all nodes in the cluster. The paths must specify a protocol (e.g. file://) and be accessible on all nodes (e.g. by means of a NFS share). You can use this option multiple times for specifying more than one URL. The protocol must be supported by the {@link java.net.URLClassLoader}. -d,--detached If present, runs the job in detached mode -n,--allowNonRestoredState Allow to skip savepoint state that cannot be restored. You need to allow this if you removed an operator from your program that was part of the program when the savepoint was triggered. -p,--parallelism The parallelism with which to run the program. Optional flag to override the default value specified in the configuration. -py,--python 指定Python作业的入口，依赖的资源文件可以通过 --pyFiles进行指定。 -pyfs,--pyFiles 指定Python作业依赖的一些自定义的python文件，如果有多个文件，可以通过逗号(,)进行分隔。支持常用的python资源文件，例如(.py/.egg/.zip)。 (例如:--pyFiles file:///tmp/myresource.zip ,hdfs:///$namenode_address/myresource2.zip) -pym,--pyModule 指定python程序的运行的模块入口，这个选项必须配合 --pyFiles一起使用。 -q,--sysoutLogging If present, suppress logging output to standard out. -s,--fromSavepoint Path to a savepoint to restore the job from (for example hdfs:///flink/savepoint-1537). -sae,--shutdownOnAttachedExit If the job is submitted in attached mode, perform a best-effort cluster shutdown when the CLI is terminated abruptly, e.g., in response to a user interrupt, such as typing Ctrl + C. Options for yarn-cluster mode: -d,--detached If present, runs the job in detached mode -m,--jobmanager Address of the JobManager (master) to which to connect. Use this flag to connect to a different JobManager than the one specified in the configuration. -sae,--shutdownOnAttachedExit If the job is submitted in attached mode, perform a best-effort cluster shutdown when the CLI is terminated abruptly, e.g., in response to a user interrupt, such as typing Ctrl + C. -yat,--yarnapplicationType Set a custom application type for the application on YARN -yD <property=value> use value for given property -yd,--yarndetached If present, runs the job in detached mode (deprecated; use non-YARN specific option instead) -yh,--yarnhelp Help for the Yarn session CLI. -yid,--yarnapplicationId Attach to running YARN session -yj,--yarnjar Path to Flink jar file -yjm,--yarnjobManagerMemory Memory for JobManager Container with optional unit (default: MB) -ynm,--yarnname Set a custom name for the application on YARN -yq,--yarnquery Display available YARN resources (memory, cores) -yqu,--yarnqueue Specify YARN queue. -ys,--yarnslots Number of slots per TaskManager -yst,--yarnstreaming Start Flink in streaming mode -yt,--yarnship Ship files in the specified directory (t for transfer), multiple options are supported. -ytm,--yarntaskManagerMemory Memory per TaskManager Container with optional unit (default: MB) -yz,--yarnzookeeperNamespace Namespace to create the Zookeeper sub-paths for high availability mode -ynl,--yarnnodeLabel Specify YARN node label for the YARN application -z,--zookeeperNamespace Namespace to create the Zookeeper sub-paths for high availability mode

Options for default mode: -m,--jobmanager Address of the JobManager (master) to which to connect. Use this flag to connect to a different JobManager than the one specified in the configuration. -z,--zookeeperNamespace Namespace to create the Zookeeper sub-paths for high availability mode

Action “info” shows the optimized execution plan of the program (JSON).

Syntax: info [OPTIONS] “info” action options: -c,--class Class with the program entry point (“main()” method or “getPlan()” method). Only needed if the JAR file does not specify the class in its manifest. -p,--parallelism The parallelism with which to run the program. Optional flag to override the default value specified in the configuration.

Action “list” lists running and scheduled programs.

Syntax: list [OPTIONS] “list” action options: -r,--running Show only running programs and their JobIDs -s,--scheduled Show only scheduled programs and their JobIDs Options for yarn-cluster mode: -m,--jobmanager Address of the JobManager (master) to which to connect. Use this flag to connect to a different JobManager than the one specified in the configuration. -yid,--yarnapplicationId Attach to running YARN session -z,--zookeeperNamespace Namespace to create the Zookeeper sub-paths for high availability mode

Action “stop” stops a running program with a savepoint (streaming jobs only).

Syntax: stop [OPTIONS] “stop” action options: -d,--drain Send MAX_WATERMARK before taking the savepoint and stopping the pipelne. -p,--savepointPath Path to the savepoint (for example hdfs:///flink/savepoint-1537). If no directory is specified, the configured default will be used (“state.savepoints.dir”). Options for yarn-cluster mode: -m,--jobmanager Address of the JobManager (master) to which to connect. Use this flag to connect to a different JobManager than the one specified in the configuration. -yid,--yarnapplicationId Attach to running YARN session -z,--zookeeperNamespace Namespace to create the Zookeeper sub-paths for high availability mode

Action “cancel” cancels a running program.

Syntax: cancel [OPTIONS] “cancel” action options: -s,--withSavepoint DEPRECATION WARNING: Cancelling a job with savepoint is deprecated. Use “stop” instead. Trigger savepoint and cancel job. The target directory is optional. If no directory is specified, the configured default directory (state.savepoints.dir) is used. Options for yarn-cluster mode: -m,--jobmanager Address of the JobManager (master) to which to connect. Use this flag to connect to a different JobManager than the one specified in the configuration. -yid,--yarnapplicationId Attach to running YARN session -z,--zookeeperNamespace Namespace to create the Zookeeper sub-paths for high availability mode

Action “savepoint” triggers savepoints for a running job or disposes existing ones.

Syntax: savepoint [OPTIONS] [] “savepoint” action options: -d,--dispose Path of savepoint to dispose. -j,--jarfile Flink program JAR file. Options for yarn-cluster mode: -m,--jobmanager Address of the JobManager (master) to which to connect. Use this flag to connect to a different JobManager than the one specified in the configuration. -yid,--yarnapplicationId Attach to running YARN session -z,--zookeeperNamespace Namespace to create the Zookeeper sub-paths for high availability mode

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