SPARK提交job的几种模式

末蓝、 2022-06-06 05:10 222阅读 0赞

**常见语法：**

./bin/spark-submit \
      --class <main-class>   --master <master-url> \   --deploy-mode <deploy-mode> \   --conf <key>=<value> \   ... # other options
      <application-jar> \
      [application-arguments]

**几个常见的例子**

# Run application locally on 8 cores
    ./bin/spark-submit \
      --class org.apache.spark.examples.SparkPi \   --master local[8] \ /path/to/examples.jar \
      100
    
    # Run on a Spark Standalone cluster in client deploy mode
    ./bin/spark-submit \
      --class org.apache.spark.examples.SparkPi \   --master spark://207.184.161.138:7077 \   --executor-memory 20G \   --total-executor-cores 100 \ /path/to/examples.jar \
      1000
    
    # Run on a Spark Standalone cluster in cluster deploy mode with supervise
    ./bin/spark-submit \
      --class org.apache.spark.examples.SparkPi \   --master spark://207.184.161.138:7077 \   --deploy-mode cluster   --supervise   --executor-memory 20G \   --total-executor-cores 100 \ /path/to/examples.jar \
      1000
    
    # Run on a YARN cluster
    export HADOOP_CONF_DIR=XXX
    ./bin/spark-submit \
      --class org.apache.spark.examples.SparkPi \   --master yarn-cluster \ # can also be `yarn-client` for client mode   --executor-memory 20G \   --num-executors 50 \ /path/to/examples.jar \
      1000
    
    # Run a Python application on a Spark Standalone cluster
    ./bin/spark-submit \
      --master spark://207.184.161.138:7077 \   examples/src/main/python/pi.py \
      1000

**master的几种方式**  
![这里写图片描述][SouthEast]

**client与cluster有什么区别**

client就是driver就在本机上运行，提交后不能退出程序。  
cluster是driver也在集群上，本机只是提交一个任务，提交任务后就可以关闭窗口了。

**spark-submit完整的提交文档**

hadoop@gdc-nn01-logtest:~/spark$ bin/spark-submit
    Usage: spark-submit [options]  [app arguments]
    Usage: spark-submit --kill [submission ID] --master [spark://...]
    Usage: spark-submit --status [submission ID] --master [spark://...]
    
    Options:
      --master MASTER_URL spark://host:port, mesos://host:port, yarn, or local.
      --deploy-mode DEPLOY_MODE Whether to launch the driver program locally ("client") or
                                  on one of the worker machines inside the cluster ("cluster")
                                  (Default: client).
      --class CLASS_NAME Your application's main class (for Java / Scala apps).
      --name NAME A name of your application.
      --jars JARS Comma-separated list of local jars to include on the driver
                                  and executor classpaths.
      --packages Comma-separated list of maven coordinates of jars to include
                                  on the driver and executor classpaths. Will search the local
                                  maven repo, then maven central and any additional remote
                                  repositories given by --repositories. The format for the
                                  coordinates should be groupId:artifactId:version.
      --repositories Comma-separated list of additional remote repositories to
                                  search for the maven coordinates given with --packages.
      --py-files PY_FILES Comma-separated list of .zip, .egg, or .py files to place
                                  on the PYTHONPATH for Python apps.
      --files FILES Comma-separated list of files to be placed in the working
                                  directory of each executor.
    
      --conf PROP=VALUE Arbitrary Spark configuration property.
      --properties-file FILE Path to a file from which to load extra properties. If not
                                  specified, this will look for conf/spark-defaults.conf.
    
      --driver-memory MEM Memory for driver (e.g. 1000M, 2G) (Default: 512M).
      --driver-java-options Extra Java options to pass to the driver.
      --driver-library-path Extra library path entries to pass to the driver.
      --driver-class-path Extra class path entries to pass to the driver. Note that
                                  jars added with --jars are automatically included in the
                                  classpath.
    
      --executor-memory MEM Memory per executor (e.g. 1000M, 2G) (Default: 1G).
    
      --proxy-user NAME User to impersonate when submitting the application.
    
      --help, -h Show this help message and exit
      --verbose, -v Print additional debug output
      --version, Print the version of current Spark
    
     Spark standalone with cluster deploy mode only:
      --driver-cores NUM Cores for driver (Default: 1).
    
     Spark standalone or Mesos with cluster deploy mode only:
      --supervise If given, restarts the driver on failure.
      --kill SUBMISSION_ID If given, kills the driver specified.
      --status SUBMISSION_ID If given, requests the status of the driver specified.
    
     Spark standalone and Mesos only:
      --total-executor-cores NUM Total cores for all executors.
    
     Spark standalone and YARN only:
      --executor-cores NUM Number of cores per executor. (Default: 1 in YARN mode,
                                  or all available cores on the worker in standalone mode)
    
     YARN-only:
      --driver-cores NUM Number of cores used by the driver, only in cluster mode
                                  (Default: 1).
      --queue QUEUE_NAME The YARN queue to submit to (Default: "default").
      --num-executors NUM Number of executors to launch (Default: 2).
      --archives ARCHIVES Comma separated list of archives to be extracted into the
                                  working directory of each executor.
      --principal PRINCIPAL Principal to be used to login to KDC, while running on
                                  secure HDFS.
      --keytab KEYTAB The full path to the file that contains the keytab for the
                                  principal specified above. This keytab will be copied to
                                  the node running the Application Master via the Secure
                                  Distributed Cache, for renewing the login tickets and the
                                  delegation tokens periodically.
    
    15/07/22 11:03:25 INFO util.Utils: Shutdown hook called

[SouthEast]: /images/20220606/a788e26ede704ee3884de3bf488d94aa.png