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Spark standalone模式的安装（spark-1.6.1-bin-hadoop2.6.tgz）（master、slave1和slave2）

 

 前期博客

 Spark运行模式概述

Spark standalone简介与运行wordcount（master、slave1和slave2）

 

 

 

 

 

 

 

开篇要明白

　　（1）spark-env.sh 是环境变量配置文件

　　（2）spark-defaults.conf

　　（3）slaves 是从节点机器配置文件

　　（4）metrics.properties 是 监控

　　（5）log4j.properties 是配置日志

　　（5）fairscheduler.xml是公平调度

　　（6）docker.properties 是 docker

　　（7）我这里的Spark standalone模式的安装，是master、slave1和slave2。

　　（8）Spark standalone模式的安装，其实，是可以不需安装hadoop的。（我这里是没有安装hadoop了，看到有些人写博客也没安装，也有安装的）

　　（9）为了管理，安装zookeeper，（即管理master、slave1和slave2）

 

 

 

 

 

 

 首先，说下我这篇博客的Spark standalone模式的安装情况

 

 

 

 

 

 

我的安装分区如下，四台都一样。

 

 

 

 

 

 

 

 

 

 关于如何关闭防火墙

　　我这里不多说，请移步

hadoop 50070 无法访问问题解决汇总

 

 

 

 

 

 

关于如何配置静态ip和联网

　　我这里不多说，我的是如下，请移步

CentOS 6.5静态IP的设置（NAT和桥接联网方式都适用）

 

DEVICE=eth0
HWADDR=00:0C:29:A9:45:18
TYPE=Ethernet
UUID=50fc177a-f282-4c83-bfbc-cb0f00b92507
ONBOOT=yes
NM_CONTROLLED=yes
BOOTPROTO=static

DEFROUTE=yes
PEERDNS=yes
PEERROUTES=yes
IPV4_FAILURE_FATAL=yes
IPV6INIT=no
NAME="System eth0"

IPADDR=192.168.80.10
BCAST=192.168.80.255
GATEWAY=192.168.80.2
NETMASK=255.255.255.0

DNS1=192.168.80.2
DNS2=8.8.8.8

 

 

DEVICE=eth0
HWADDR=00:0C:29:18:ED:4A
TYPE=Ethernet
UUID=b5d059e4-3b92-41ef-889b-68f2f5684fac
ONBOOT=yes
NM_CONTROLLED=yes
BOOTPROTO=static

DEFROUTE=yes
PEERDNS=yes
PEERROUTES=yes
IPV4_FAILURE_FATAL=yes
IPV6INIT=no
NAME="System eth0"
IPADDR=192.168.80.11
BCAST=192.168.80.255
GATEWAY=192.168.80.2
NETMASK=255.255.255.0

DNS1=192.168.80.2
DNS2=8.8.8.8

 

 

 

 

DEVICE=eth0
HWADDR=00:0C:29:8B:DE:B0
TYPE=Ethernet
UUID=1ba7be29-2c80-4875-8c11-1ed2a47c0a67
ONBOOT=yes
NM_CONTROLLED=yes
BOOTPROTO=static

DEFROUTE=yes
PEERDNS=yes
PEERROUTES=yes
IPV4_FAILURE_FATAL=yes
IPV6INIT=no
NAME="System eth0"
IPADDR=192.168.80.12
BCAST=192.168.80.255
GATEWAY=192.168.80.2
NETMASK=255.255.255.0

DNS1=192.168.80.2
DNS1=8.8.8.8

 

 

 

 

 

 

 

 

 

 

 

关于新建用户组和用户

　　我这里不多说，我是spark，请移步

新建用户组、用户、用户密码、删除用户组、用户（适合CentOS、Ubuntu）

 

 

 

 

关于安装ssh、机器本身、机器之间进行免密码通信和时间同步

　　我这里不多说，具体，请移步。在这一步，本人深有感受，有经验。最好建议拍快照。否则很容易出错！

　　机器本身，即master与master、slave1与slave1、slave2与slave2。

　　机器之间，即master与slave1、master与slave2。

　　　　　　　　slave1与slave2。

hadoop-2.6.0.tar.gz + spark-1.5.2-bin-hadoop2.6.tgz 的集群搭建（3节点和5节点皆适用）

hadoop-2.6.0.tar.gz的集群搭建（5节点）

 

 

 

 

 

 

 

 

 关于如何先卸载自带的openjdk，再安装

　　我这里不多说，我是jdk-8u60-linux-x64.tar.gz，请移步

　　我的jdk是安装在/usr/local/jdk下，记得赋予权限组，chown -R spark:spark jdk

Centos 6.5下的OPENJDK卸载和SUN的JDK安装、环境变量配置

 

#java
export JAVA_HOME=/usr/local/jdk/jdk1.8.0_60
export JRE_HOME=$JAVA_HOME/jre
export CLASSPATH=.:$JAVA_HOME/lib:$JRE_HOME/lib
export PATH=$PATH:$JAVA_HOME/bin

 

 

 

 关于如何安装scala

　　不多说，我这里是scala-2.10.5.tgz，请移步

　　我的scala安装在/usr/local/scala，记得赋予用户组，chown -R spark:spark scala

 

hadoop-2.6.0.tar.gz + spark-1.6.1-bin-hadoop2.6.tgz的集群搭建（单节点）（CentOS系统）

#scala
export SCALA_HOME=/usr/local/scala/scala-2.10.5
export PATH=$PATH:$SCALA_HOME/bin

 

 

 

 关于如何安装spark

　　我这里不多说，请移步见

　　我的spark安装目录是在/usr/local/spark/，记得赋予用户组，chown -R spark:spark sparl

 　  只需去下面的博客，去看如何安装就好，至于spark的怎么配置。请见下面的spark  standalone模式的配置文件讲解。

hadoop-2.6.0.tar.gz + spark-1.6.1-bin-hadoop2.6.tgz的集群搭建（单节点）（CentOS系统）

#spark
export SPARK_HOME=/usr/local/spark/spark-1.6.1-bin-hadoop2.6
export PATH=$PATH:$SPARK_HOME/bin:$SPARK_HOME/sbin

 

 

 

 

 

 

关于zookeeper的安装

　　我这里不多说，请移步

hadoop-2.6.0-cdh5.4.5.tar.gz(CDH)的3节点集群搭建(含zookeeper集群安装）

 以及，之后，在spark 里怎么配置zookeeper。

Spark standalone简介与运行wordcount（master、slave1和slave2）

 

 

 

 

 

 

这里，我带大家来看官网

http://spark.apache.org/docs/latest

 

 

 

 

 

 

http://spark.apache.org/docs/latest/spark-standalone.html

 

 

http://spark.apache.org/docs/latest/spark-standalone.html#starting-a-cluster-manually

 

 

 

 

 

 

 

Spark Standalone部署配置---通过脚本启动集群

修改如下配置：

● slaves--指定在哪些节点上运行worker。

#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License.  You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#

# A Spark Worker will be started on each of the machines listed below.
slave1
slave2

 

● spark-defaults.conf---spark提交job时的默认配置

#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License.  You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#

# Default system properties included when running spark-submit.
# This is useful for setting default environmental settings.

# Example:
# spark.master                     spark://master:7077
# spark.eventLog.enabled           true
# spark.eventLog.dir               hdfs://namenode:8021/directory
# spark.serializer                 org.apache.spark.serializer.KryoSerializer
# spark.driver.memory              5g
# spark.executor.extraJavaOptions  -XX:+PrintGCDetails -Dkey=value -Dnumbers="one two three"

　　大家，可以在这个配置文件里指定好，以后每次不需在命令行下指定了。当然咯，也可以不配置啦！（我一般是这里不配置，即这个文件不动它）

 

 

 

 

spark-defaults.conf （这个作为可选可不选）（是因为或者是在spark-submit里也是可以加入的）（一般不选，不然固定死了）（我一般是这里不配置，即这个文件不动它）

spark.master                       spark://master:7077
spark.eventLog.enabled             true
spark.eventLog.dir                 hdfs://master:9000/sparkHistoryLogs
spark.eventLog.compress            true
spark.history.fs.update.interval   5
spark.history.ui.port              7777
spark.history.fs.logDirectory      hdfs://master:9000/sparkHistoryLogs

 　

 

 

 

● spark-env.sh—spark的环境变量

#!/usr/bin/env bash

#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License.  You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#

# 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 executors to start (Default: 2)
# - SPARK_EXECUTOR_CORES, Number of cores for the executors (Default: 1).
# - SPARK_EXECUTOR_MEMORY, Memory per Executor (e.g. 1000M, 2G) (Default: 1G)
# - SPARK_DRIVER_MEMORY, Memory for Driver (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, 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)



export JAVA_HOME=/usr/local/jdk/jdk1.8.0_60
export SCALA_HOME=/usr/local/scala/scala-2.10.5

export SPARK_MASTER_IP=192.168.80.10
export SPARK_WORKER_MERMORY=1G （官网上说是1g）
# SPARK_MASTER_WEBUI_PORT=8888  (这里自行可以去修改，我这里不做演示）

注意：SPARK_MASTER_PORT默认是8080，SPARK_MASTER_WEBUI_PORT默认是7077

 　　因为，我说了，我的这篇博文定位是对spark的standalone模式的安装，所以，它是可以不用安装hadoop的，所以这里就不需配置hadoop了。

你们大家若有看到这里要配置，比如HADOOP_HOME和HADOOP_CONF_DIR等。那是spark的yarn模式的安装。！！！（注意）

 

 

 

 

● 在打算作为master的节点上启动集群—sbin/start-all.sh

 

 

 

 

 

 

 

 

 

posted @ 2017-03-28 10:00  大数据和AI躺过的坑  阅读(1844)  评论(0)  编辑  收藏  举报