【Spark】在Standalone运行模式下的配置模板

#!/usr/bin/env bash

# This file is sourced when running various Spark programs.
# Copy it as spark-env.sh and edit that to configure Spark for your site.

# Options read when launching programs locally with
# ./bin/run-example or ./bin/spark-submit
# – HADOOP_CONF_DIR, to point Spark towards Hadoop configuration files
# – SPARK_LOCAL_IP, to set the IP address Spark binds to on this node
# – SPARK_PUBLIC_DNS, to set the public dns name of the driver program
# – SPARK_CLASSPATH, default classpath entries to append

# Options read by executors and drivers running inside the cluster
# – SPARK_LOCAL_IP, to set the IP address Spark binds to on this node
# – SPARK_PUBLIC_DNS, to set the public DNS name of the driver program
# – SPARK_CLASSPATH, default classpath entries to append
# – SPARK_LOCAL_DIRS, storage directories to use on this node for shuffle and RDD data
# – MESOS_NATIVE_JAVA_LIBRARY, to point to your libmesos.so if you use Mesos

# Options read in YARN client mode
# – HADOOP_CONF_DIR, to point Spark towards Hadoop configuration files
# – SPARK_EXECUTOR_INSTANCES, Number of workers to start (Default: 2)
# – SPARK_EXECUTOR_CORES, Number of cores for the workers (Default: 1).
# – SPARK_EXECUTOR_MEMORY, Memory per Worker (e.g. 1000M, 2G) (Default: 1G)
# – SPARK_DRIVER_MEMORY, Memory for Master (e.g. 1000M, 2G) (Default: 1G)
# – SPARK_YARN_APP_NAME, The name of your application (Default: Spark)
# – SPARK_YARN_QUEUE, The hadoop queue to use for allocation requests (Default: ‘default’)
# – SPARK_YARN_DIST_FILES, Comma separated list of files to be distributed with the job.
# – SPARK_YARN_DIST_ARCHIVES, Comma separated list of archives to be distributed with the job.

# Options for the daemons used in the standalone deploy mode
SPARK_MASTER_IP=tts.node4
SPARK_MASTER_PORT=7077
SPARK_WORKER_CORES=6
SPARK_WORKER_MEMORY=2g
HADOOP_HOME=/appl/hadoop-2.7.0
HADOOP_CONF_DIR=/appl/hadoop-2.7.0/etc/hadoop
SPARK_PID_DIR=/appl/spark-1.5.2-bin-hadoop2.6/tmp
SPARK_CLASSPATH=/appl/scripts/jars/play-json_2.10-2.3.9.jar:/appl/hadoop-2.7.0/apache-hive-1.2.1-bin/lib/mysql-connector-java-5.1.36.jar
#SPARK_WORKER_INSTANCES=5
#SPARK_WORKER_CORES=4
JAVA_HOME=/usr/java/jdk1.7.0_55
#SPARK_CLASSPATH=$SPARK_CLASSPATH:/appl/hbase-1.1.3/conf/:/appl/spark-1.5.2-bin-hadoop2.6/lib/hbase/*
SPARK_MASTER_OPTS="-Dspark.deploy.defaultCores=2"

# – SPARK_MASTER_IP, to bind the master to a different IP address or hostname
# – SPARK_MASTER_PORT / SPARK_MASTER_WEBUI_PORT, to use non-default ports for the master
# – SPARK_MASTER_OPTS, to set config properties only for the master (e.g. "-Dx=y")
# – SPARK_WORKER_CORES, to set the number of cores to use on this machine
# – SPARK_WORKER_MEMORY, to set how much total memory workers have to give executors (e.g. 1000m, 2g)
# – SPARK_WORKER_PORT / SPARK_WORKER_WEBUI_PORT, to use non-default ports for the worker
# – SPARK_WORKER_INSTANCES, to set the number of worker processes per node
# – SPARK_WORKER_DIR, to set the working directory of worker processes
# – SPARK_WORKER_OPTS, to set config properties only for the worker (e.g. "-Dx=y")
# – SPARK_DAEMON_MEMORY, to allocate to the master, worker and history server themselves (default: 1g).
# – SPARK_HISTORY_OPTS, to set config properties only for the history server (e.g. "-Dx=y")
# – SPARK_SHUFFLE_OPTS, to set config properties only for the external shuffle service (e.g. "-Dx=y")
# – SPARK_DAEMON_JAVA_OPTS, to set config properties for all daemons (e.g. "-Dx=y")
# – SPARK_PUBLIC_DNS, to set the public dns name of the master or workers

# Generic options for the daemons used in the standalone deploy mode
# – SPARK_CONF_DIR      Alternate conf dir. (Default: ${SPARK_HOME}/conf)
# – SPARK_LOG_DIR       Where log files are stored.  (Default: ${SPARK_HOME}/logs)
# – SPARK_PID_DIR       Where the pid file is stored. (Default: /tmp)
# – SPARK_IDENT_STRING  A string representing this instance of spark. (Default: $USER)
# – SPARK_NICENESS      The scheduling priority for daemons. (Default: 0)

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One thought on “【Spark】在Standalone运行模式下的配置模板

  • 2016-10-27 at 18:27
    Permalink

    I want to send you an award for most helpful inentret writer.

    Reply

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