==作者：YB-Chi==

[toc]

知识点

用spark-submit命令提交任务运行，具体使用查看：spark-submit –help

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.
  --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.

  --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: 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.

  --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.

问题记录

Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources

当前的集群的可用资源不能满足应用程序所请求的资源。我spark submit的时候给的资源太大了

资源分2类： cores 和 ram
Core代表对执行可用的executor slots
Ram代表每个Worker上被需要的空闲内存来运行你的Application。
解决方法：
应用不要请求多余空闲可用资源的
关闭掉已经执行结束的Application

spark-submit执行命令

spark-submit --master spark://FJ-DCLOUD-HDP01:7077 --conf "spark.scheduler.mode=FAIR" --total-executor-cores 8 --driver-memory 20g --executor-memory 20g /home/yarn/dev/cyb/a.jar 

a.jar不需要jar包   所要用的jar包放到spark服务器的lib下  例如：
/home/yarn/spark-1.5.2-bin-hadoop2.6/lib
命令会默认读取改路径下的jar
关于此设置的配置 见下条

spark-submit指定服务器jar包配置

[yarn@EPRI-DCLOUD-ETL01 conf]$ pwd
/home/yarn/spark-1.5.2-bin-hadoop2.6/conf
[root@EPRI-DCLOUD-ETL01 conf]# ls
docker.properties.template  fairscheduler.xml.template  hive-site.xml  log4j.properties  metrics.properties.template  slaves  spark-defaults.conf  spark-env.sh
[root@EPRI-DCLOUD-ETL01 conf]# vi spark-env.sh 

export SPARK_YARN_MODE=true
export MASTER=yarn-client
export JAVA_HOME=/usr/java/jdk1.7.0_55
export SCALA_HOME=/usr/share/scala-2.11.6
export SPARK_MASTER_IP=EPRI-DCLOUD-HDP01
export SPARK_CLASSPATH=$SPARK_CLASSPATH:/usr/share/spark-1.5.2-bin-hadoop2.6/lib/*:/usr/share/hadoop-2.6.0/*:/usr/share/hadoop-2.6.0/etc/*:/usr/share/hadoop-2.6.0/lib/*
export HADOOP_HOME=/usr/share/hadoop-2.6.0export HADOOP_CONF_DIR=/usr/share/hadoop-2.6.0/etc/hadoop