命令参数查看
root@redis01:/usr/local/flink-standalone# ./bin/flink run -h
Flink run 参数
1 参数必选 ： -n,--container <arg> 分配多少个yarn容器 (=taskmanager的数量) 2 参数可选 ： -D <arg> 动态属性 -d,--detached 独立运行 -jm,--jobManagerMemory <arg> JobManager的内存 [in MB] -nm,--name 在YARN上为一个自定义的应用设置一个名字 -q,--query 显示yarn中可用的资源 (内存, cpu核数) -qu,--queue <arg> 指定YARN队列. -s,--slots <arg> 每个TaskManager使用的slots数量 -tm,--taskManagerMemory <arg> 每个TaskManager的内存 [in MB] -z,--zookeeperNamespace <arg> 针对HA模式在zookeeper上创建NameSpace -id,--applicationId <yarnAppId> YARN集群上的任务id，附着到一个后台运行的yarn session中 3 run [OPTIONS] <jar-file> <arguments> run操作参数: -c,--class <classname> 如果没有在jar包中指定入口类，则需要在这里通过这个参数指定 -m,--jobmanager <host:port> 指定需要连接的jobmanager(主节点)地址，使用这个参数可以指定一个不同于配置文件中的jobmanager -p,--parallelism <parallelism> 指定程序的并行度。可以覆盖配置文件中的默认值。 4 启动一个新的yarn-session,它们都有一个y或者yarn的前缀 例如：./bin/flink run -m yarn-cluster -yn 2 ./examples/batch/WordCount.jar 连接指定host和port的jobmanager： ./bin/flink run -m SparkMaster:1234 ./examples/batch/WordCount.jar -input hdfs://hostname:port/hello.txt -output hdfs://hostname:port/result1 启动一个新的yarn-session： ./bin/flink run -m yarn-cluster -yn 2 ./examples/batch/WordCount.jar -input hdfs://hostname:port/hello.txt -output hdfs://hostname:port/result1 5 注意：命令行的选项也可以使用./bin/flink 工具获得。 6 Action "run" compiles and runs a program. Syntax: run [OPTIONS] <jar-file> <arguments> "run" action options: -c,--class <classname> 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 <url> 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 <parallelism> The parallelism with which to run the program. Optional flag to override the default value specified in the configuration. -q,--sysoutLogging If present, suppress logging output to standard out. -s,--fromSavepoint <savepointPath> Path to a savepoint to restore the job from (for example hdfs:///flink/savepoint-1537). 7 Options for yarn-cluster mode: -d,--detached If present, runs the job in detached mode -m,--jobmanager <arg> 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. -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 <arg> Attach to running YARN session -yj,--yarnjar <arg> Path to Flink jar file -yjm,--yarnjobManagerMemory <arg> Memory for JobManager Container with optional unit (default: MB) -yn,--yarncontainer <arg> Number of YARN container to allocate (=Number of Task Managers) -ynl,--yarnnodeLabel <arg> Specify YARN node label for the YARN application -ynm,--yarnname <arg> Set a custom name for the application on YARN -yq,--yarnquery Display available YARN resources (memory, cores) -yqu,--yarnqueue <arg> Specify YARN queue. -ys,--yarnslots <arg> Number of slots per TaskManager -yst,--yarnstreaming Start Flink in streaming mode -yt,--yarnship <arg> Ship files in the specified directory (t for transfer) -ytm,--yarntaskManagerMemory <arg> Memory per TaskManager Container with optional unit (default: MB) -yz,--yarnzookeeperNamespace <arg> Namespace to create the Zookeeper sub-paths for high availability mode -z,--zookeeperNamespace <arg> Namespace to create the Zookeeper sub-paths for high availability mode
root@redis01:/usr/local/flink-standalone# ./bin/flink run -h Action "run" compiles and runs a program. Syntax: run [OPTIONS] <jar-file> <arguments> "run" action options: -c,--class <classname> Class with the program entry point ("main()" method). Only needed if the JAR file does not specify the class in its manifest. -C,--classpath <url> 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 <parallelism> The parallelism with which to run the program. Optional flag to override the default value specified in the configuration. -py,--python <pythonFile> Python script with the program entry point. The dependent resources can be configured with the `--pyFiles` option. -pyarch,--pyArchives <arg> Add python archive files for job. The archive files will be extracted to the working directory of python UDF worker. For each archive file, a target directory be specified. If the target directory name is specified, the archive file will be extracted to a directory with the specified name. Otherwise, the archive file will be extracted to a directory with the same name of the archive file. The files uploaded via this option are accessible via relative path. '#' could be used as the separator of the archive file path and the target directory name. Comma (',') could be used as the separator to specify multiple archive files. This option can be used to upload the virtual environment, the data files used in Python UDF (e.g., --pyArchives file:///tmp/py37.zip,file:///tmp /data.zip#data --pyExecutable py37.zip/py37/bin/python). The data files could be accessed in Python UDF, e.g.: f = open('data/data.txt', 'r'). -pyclientexec,--pyClientExecutable <arg> The path of the Python interpreter used to launch the Python process when submitting the Python jobs via "flink run" or compiling the Java/Scala jobs containing Python UDFs. -pyexec,--pyExecutable <arg> Specify the path of the python interpreter used to execute the python UDF worker (e.g.: --pyExecutable /usr/local/bin/python3). The python UDF worker depends on Python 3.6+, Apache Beam (version == 2.27.0), Pip (version >= 7.1.0) and SetupTools (version >= 37.0.0). Please ensure that the specified environment meets the above requirements. -pyfs,--pyFiles <pythonFiles> Attach custom files for job. The standard resource file suffixes such as .py/.egg/.zip/.whl or directory are all supported. These files will be added to the PYTHONPATH of both the local client and the remote python UDF worker. Files suffixed with .zip will be extracted and added to PYTHONPATH. Comma (',') could be used as the separator to specify multiple files (e.g., --pyFiles file:///tmp/myresource.zip,hdfs: ///$namenode_address/myresource2 .zip). -pym,--pyModule <pythonModule> Python module with the program entry point. This option must be used in conjunction with `--pyFiles`. -pyreq,--pyRequirements <arg> Specify a requirements.txt file which defines the third-party dependencies. These dependencies will be installed and added to the PYTHONPATH of the python UDF worker. A directory which contains the installation packages of these dependencies could be specified optionally. Use '#' as the separator if the optional parameter exists (e.g., --pyRequirements file:///tmp/requirements.txt#fil e:///tmp/cached_dir). -s,--fromSavepoint <savepointPath> 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 Generic CLI mode: -D <property=value> Allows specifying multiple generic configuration options. The available options can be found at https://nightlies.apache.org/flink/flink-docs-stable/ ops/config.html -e,--executor <arg> DEPRECATED: Please use the -t option instead which is also available with the "Application Mode". The name of the executor to be used for executing the given job, which is equivalent to the "execution.target" config option. The currently available executors are: "remote", "local", "kubernetes-session", "yarn-per-job", "yarn-session". -t,--target <arg> The deployment target for the given application, which is equivalent to the "execution.target" config option. For the "run" action the currently available targets are: "remote", "local", "kubernetes-session", "yarn-per-job", "yarn-session". For the "run-application" action the currently available targets are: "kubernetes-application", "yarn-application". Options for yarn-cluster mode: -d,--detached If present, runs the job in detached mode -m,--jobmanager <arg> Set to yarn-cluster to use YARN execution mode. -yat,--yarnapplicationType <arg> 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 <arg> Attach to running YARN session -yj,--yarnjar <arg> Path to Flink jar file -yjm,--yarnjobManagerMemory <arg> Memory for JobManager Container with optional unit (default: MB) -ynl,--yarnnodeLabel <arg> Specify YARN node label for the YARN application -ynm,--yarnname <arg> Set a custom name for the application on YARN -yq,--yarnquery Display available YARN resources (memory, cores) -yqu,--yarnqueue <arg> Specify YARN queue. -ys,--yarnslots <arg> Number of slots per TaskManager -yt,--yarnship <arg> Ship files in the specified directory (t for transfer) -ytm,--yarntaskManagerMemory <arg> Memory per TaskManager Container with optional unit (default: MB) -yz,--yarnzookeeperNamespace <arg> Namespace to create the Zookeeper sub-paths for high availability mode -z,--zookeeperNamespace <arg> Namespace to create the Zookeeper sub-paths for high availability mode Options for default mode: -D <property=value> Allows specifying multiple generic configuration options. The available options can be found at https://nightlies.apache.org/flink/flink-do cs-stable/ops/config.html -m,--jobmanager <arg> Address of the JobManager to which to connect. Use this flag to connect to a different JobManager than the one specified in the configuration. Attention: This option is respected only if the high-availability configuration is NONE. -z,--zookeeperNamespace <arg> Namespace to create the Zookeeper sub-paths for high availability mode