| title | nav-title | nav-parent_id | nav-pos |
|---|---|---|---|
Command-Line Interface |
CLI |
ops |
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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These examples about how to submit a job in CLI.
-
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 -yn 2 \ ./examples/batch/WordCount.jar \ --input hdfs:///user/hamlet.txt --output hdfs:///user/wordcount_out
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Run Python Table program:
./bin/flink run -py examples/python/table/batch/word_count.py -j <path/to/flink-table.jar> -
Run Python Table program with pyFiles:
./bin/flink run -py examples/python/table/batch/word_count.py -j <path/to/flink-table.jar> \ -pyfs file:///user.txt,hdfs:///$namenode_address/username.txt -
Run Python Table program with pyFiles and pyModule:
./bin/flink run -pym batch.word_count -pyfs examples/python/table/batch -j <path/to/flink-table.jar> -
Run Python Table program with parallelism 16:
./bin/flink run -p 16 -py examples/python/table/batch/word_count.py -j <path/to/flink-table.jar> -
Run Python Table program with flink log output disabled:
./bin/flink run -q -py examples/python/table/batch/word_count.py -j <path/to/flink-table.jar> -
Run Python Table program in detached mode:
./bin/flink run -d -py examples/python/table/batch/word_count.py -j <path/to/flink-table.jar> -
Run Python Table program on a specific JobManager:
./bin/flink run -m myJMHost:8081 \ -py examples/python/table/batch/word_count.py \ -j <path/to/flink-table.jar> -
Run Python Table program using a per-job YARN cluster with 2 TaskManagers:
./bin/flink run -m yarn-cluster -yn 2 \ -py examples/python/table/batch/word_count.py \ -j <path/to/flink-table.jar>
These examples about how to manage a job in CLI.
-
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:
./bin/flink cancel -s [targetDirectory] <jobID> -
Stop a job with a savepoint (streaming jobs only):
./bin/flink stop -s [targetDirectory] -d <jobID>
NOTE: The difference between cancelling and stopping a (streaming) job is the following:
On a cancel call, the operators in a job immediately receive a cancel() method call to cancel them as
soon as possible.
If operators are not not stopping after the cancel call, Flink will start interrupting the thread periodically
until it stops.
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.
Savepoints are controlled via the command line client:
{% 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.
{% 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.
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.
{% 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.
{% 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.
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 Python script with the program entry
point.The dependent resources can be
configured with the --pyFiles option.
-pyfs,--pyFiles Attach custom python files for job.
Comma can be used as the separator to
specify multiple files. The standard
python resource file suffixes such as
.py/.egg/.zip are all supported.
(eg:--pyFiles file:///tmp/myresource.zip
,hdfs:///$namenode_address/myresource2.zip)
-pym,--pyModule Python module with the program entry
point. This option must be used in
conjunction with --pyFiles.
-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.
-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)
-yn,--yarncontainer Number of YARN container to allocate
(=Number of Task Managers)
-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
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 "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. -s,--withSavepoint 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 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 "cancel" cancels a running program.
Syntax: cancel [OPTIONS] "cancel" action options: -s,--withSavepoint 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
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 "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
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 {% endhighlight %}
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