spark-submit详细参数说明在spark命令⾏输⼊
./bin/spark-submit --help
可以看到spark-submit的所⽤参数如下：
Usage: spark-submit [options] <app jar | python file | R file> [app arguments]
Usage: spark-submit --kill [submission ID] --master [spark://...]
Usage: spark-submit --status [submission ID] --master [spark://...]
Usage: spark-submit run-example [options] example-class [example args]
Options:
--master MASTER_URL        spark://host:port, mesos://host:port, yarn,
k8s://host:port, or local (Default: 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 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.
-
-exclude-packages          Comma-separated list of groupId:artifactId, to exclude while
resolving the dependencies provided in --packages to avoid
dependency conflicts.
--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. File paths of these files
in executors can be accessed (fileName).
--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 f.
--driver-memory MEM        Memory for driver (e.g. 1000M, 2G) (Default: 1024M).
--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.
This argument does not work with --principal / --keytab.
-
-help, -h                  Show this help message and exit.
--verbose, -v              Print additional debug output.
--version,                  Print the version of current Spark.
Cluster deploy mode only:
--driver-cores NUM          Number of cores used by the driver, only in cluster mode
(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.
参数名
参数说明--master
master 的地址，提交任务到哪⾥执⾏，例如 spark://host:port,  yarn,  local --deploy-mode
在本地 (client) 启动 driver 或在 cluster 上启动，默认是 client --class
应⽤程序的主类，仅针对 java 或 scala 应⽤--name
应⽤程序的名称--jars
⽤逗号分隔的本地 jar 包，设置后，这些 jar 将包含在 driver 和 executor 的 classpath 下--packages
包含在driver 和executor 的 classpath 中的 jar 的 maven 坐标--exclude-packages
为了避免冲突 ⽽指定不包含的 package --repositories  远程 repository
--conf PROP=VALUE  指定 spark 配置属性的值，
例如 -aJavaOptions="-XX:MaxPermSize=256m"--properties-file  加载的配置⽂件，默认为 f
--driver-memory  Driver内存，默认 1G
--driver-java-options  传给 driver 的额外的 Java 选项
--driver-library-path  传给 driver 的额外的库路径
--driver-class-path  传给 driver 的额外的类路径
--driver-cores  Driver 的核数，默认是1。在 yarn 或者 standalone 下使⽤
--executor-memory  每个 executor 的内存，默认是1G
--total-executor-cores  所有 executor 总共的核数。仅仅在 mesos 或者 standalone 下使⽤
--num-executors
启动的 executor 数量。默认为2。在 yarn 下使⽤  --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:
--queue QUEUE_NAME          The YARN queue to submit to (Default: "default").  --num-executors NUM        Number of executors to launch (Default: 2).
If dynamic allocation is enabled, the initial number of
executors will be at least NUM.
submitting
--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.
1.
2.
相关意义如下：
--num-executors 启动的 executor 数量。默认为2。在 yarn 下使⽤
--executor-core 每个 executor 的核数。在yarn或者standalone下使⽤

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