Spark standalone模式的安装(spark-1.6.1-bin-hadoop2.6.tgz)(master、slave1和slave2)
前期博客
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)
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
作者:大数据和人工智能躺过的坑
出处:http://www.cnblogs.com/zlslch/
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