spark-submit參數說明--on YARN

示例： spark-submit [--option value] <application jar> [application arguments]

參數名稱	含義
--master MASTER_URL	yarn
--deploy-mode DEPLOY_MODE	Driver程序運行的地方：client、cluster
--class CLASS_NAME	The FQCN of the class containing the main method of the application. For example, org.apache.spark.examples.SparkPi.   應用程序主類名稱，含包名
--name NAME	應用程序名稱
--jars JARS	Driver和Executor依賴的第三方jar包
--properties-file FILE	應用程序屬性的文件路徑，默認是conf/spark-defaults.conf
如下設置Driver
--driver-cores NUM	Driver程序使用的CPU核數(只用於cluster)，默認爲1
--driver-memory MEM	Driver程序使用內存大小
--driver-library-path	Driver程序的庫路徑
--driver-class-path	Driver程序的類路徑
--driver-java-options
如下設置Executor
--num-executors NUM	The total number of YARN containers to allocate for this application. Alternatively, you can use the spark.executor.instances configuration parameter.   啓動的executor的數量，默認爲2
--executor-cores NUM	Number of processor cores to allocate on each executor   每一個executor使用的CPU核數，默認爲1
--executor-memory MEM	The maximum heap size to allocate to each executor. Alternatively, you can use the spark.executor.memory configuration parameter.   每一個executor內存大小，默認爲1G
--queue QUEUE_NAME	The YARN queue to submit to.     提交應用程序給哪一個YARN的隊列，默認是default隊列
--archives ARCHIVES
--files FILES	用逗號隔開的要放置在每一個executor工做目錄的文件列表

 

1.部署模式概述

   In YARN, each application instance has an ApplicationMaster process, which is the first container started for that application.

  The application is responsible for requesting resources from the ResourceManager, and, when allocated them, instructing NodeManagers to start containers on its behalf.

  ApplicationMasters obviate the need for an active client — the process starting the application can terminate and coordination continues from a process managed by YARN running on the cluster.

2.部署模式：Cluster

 In cluster mode, the driver runs in the ApplicationMaster on a cluster host chosen by YARN.

 This means that the same process, which runs in a YARN container, is responsible for both driving the application and requesting resources from YARN.

 The client that launches the application doesn't need to continue running for the entire lifetime of the application.

  Cluster mode is not well suited to using Spark interactively.

  Spark applications that require user input, such as spark-shell and pyspark, need the Spark driver to run inside the client process that initiates the Spark application.

3.部署模式：Client

  In client mode, the driver runs on the host where the job is submitted.

  The ApplicationMaster is merely present to request executor containers from YARN.

  The client communicates with those containers to schedule work after they start:

 

4.參考文檔：

https://www.cloudera.com/documentation/enterprise/5-4-x/topics/cdh_ig_running_spark_on_yarn.html

http://spark.apache.org/docs/1.3.0/running-on-yarn.html