大数据时代之hadoop(一)：hadoop安装

“兵马未动，粮草先行”，要想深入的了解hadoop，我觉得启动或停止hadoop的脚本是必须要先了解的。说到底，hadoop就是一个分布式存储和计算框架，但是这个分布式环境是如何启动，管理的呢，我就带着大家先从脚本入手吧。说实话，hadoop的启动脚本写的真好，里面考虑的地方非常周全（比如说路径中有空格，软连接等）。

1、hadoop脚本简单介绍

   hadoop的脚本分布在$HADOOP_HOME下面的bin目录下和conf文件夹下，主要介绍如下：

bin目录下
        hadoop                 hadoop底层核心脚本，所有分布式程序最终都是通过这个脚本启动的。
hadoop-config.sh       基本别的脚本都会内嵌调用这个脚本，这个脚本作用就是解析命令行可选参数（--config ：hadoop conf文件夹路径 和--hosts）
hadoop-daemon.sh       启动或停止本机command参数所指定的分布式程序，通过调用hadoop脚本实现。
hadoop-daemons.sh      启动所有机器上的hadoop分布式程序，通过调用slaves.sh实现。
slaves.sh              在所有的机器上运行一组指定的命令（通过ssh无密码登陆），供上层使用。
start-dfs.sh           在本机启动namenode，在slaves机器上启动datanode，在master机器上启动secondarynamenode，通过调用hadoop-daemon.sh和hadoop-daemons.sh实现。
start-mapred.sh        在本机启动jobtracker，在slaves机器上启动tasktracker，通过调用hadoop-daemon.sh和hadoop-daemons.sh实现。
start-all.sh           启动所有分布式hadoop程序，通过调用start-dfs.sh和start-mapred.sh实现。
start-balancer.sh      启动hadoop分布式环境复杂均衡调度程序，平衡各节点存储和处理能力。
还有几个stop 脚本，就不用详细说了。

conf目录下
hadoop-env.sh          配置hadoop运行时所需要的一些参数变量，比如JAVA_HOME,HADOOP_LOG_DIR,HADOOP_PID_DIR等。

2、脚本的魅力（详细解释）

2.1、hadoop-config.sh

#软连接解析this="$0"while [ -h "$this" ]; do  ls=`ls -ld "$this"`  link=`expr "$ls" : ‘.*-> \(.*\)$‘`  if expr "$link" : ‘.*/.*‘ > /dev/null; then    this="$link"  else    this=`dirname "$this"`/"$link"  fidone#绝对路径解析# convert relative path to absolute pathbin=`dirname "$this"`script=`basename "$this"`bin=`cd "$bin"; pwd`this="$bin/$script"# the root of the Hadoop installationexport HADOOP_HOME=`dirname "$this"`/..

#check to see if the conf dir is given as an optional argumentif [ $# -gt 1 ]then    if [ "--config" = "$1" ]	  then	      shift	      confdir=$1	      shift	      HADOOP_CONF_DIR=$confdir    fifi

#check to see it is specified whether to use the slaves or the# masters fileif [ $# -gt 1 ]then    if [ "--hosts" = "$1" ]    then        shift        slavesfile=$1        shift        export HADOOP_SLAVES="${HADOOP_CONF_DIR}/$slavesfile"    fifi

# if no args specified, show usageif [ $# = 0 ]; then  echo "Usage: hadoop [--config confdir] COMMAND"  echo "where COMMAND is one of:"  echo "  namenode -format     format the DFS filesystem"  echo "  secondarynamenode    run the DFS secondary namenode"  echo "  namenode             run the DFS namenode"  echo "  datanode             run a DFS datanode"  echo "  dfsadmin             run a DFS admin client"  echo "  mradmin              run a Map-Reduce admin client"  echo "  fsck                 run a DFS filesystem checking utility"  echo "  fs                   run a generic filesystem user client"  echo "  balancer             run a cluster balancing utility"  echo "  jobtracker           run the MapReduce job Tracker node"   echo "  pipes                run a Pipes job"  echo "  tasktracker          run a MapReduce task Tracker node"   echo "  job                  manipulate MapReduce jobs"  echo "  queue                get information regarding JobQueues"   echo "  version              print the version"  echo "  jar <jar>            run a jar file"  echo "  distcp <srcurl> <desturl> copy file or directories recursively"  echo "  archive -archiveName NAME <src>* <dest> create a hadoop archive"  echo "  daemonlog            get/set the log level for each daemon"  echo " or"  echo "  CLASSNAME            run the class named CLASSNAME"  echo "Most commands print help when invoked w/o parameters."  exit 1fi

3、根据cmd设置运行时class

# figure out which class to runif [ "$COMMAND" = "namenode" ] ; then  CLASS=‘org.apache.hadoop.hdfs.server.namenode.NameNode‘  HADOOP_OPTS="$HADOOP_OPTS $HADOOP_NAMENODE_OPTS"elif [ "$COMMAND" = "secondarynamenode" ] ; then  CLASS=‘org.apache.hadoop.hdfs.server.namenode.SecondaryNameNode‘  HADOOP_OPTS="$HADOOP_OPTS $HADOOP_SECONDARYNAMENODE_OPTS"elif [ "$COMMAND" = "datanode" ] ; then  CLASS=‘org.apache.hadoop.hdfs.server.datanode.DataNode‘  HADOOP_OPTS="$HADOOP_OPTS $HADOOP_DATANODE_OPTS"elif [ "$COMMAND" = "fs" ] ; then  CLASS=org.apache.hadoop.fs.FsShell  HADOOP_OPTS="$HADOOP_OPTS $HADOOP_CLIENT_OPTS"elif [ "$COMMAND" = "dfs" ] ; then  CLASS=org.apache.hadoop.fs.FsShell  HADOOP_OPTS="$HADOOP_OPTS $HADOOP_CLIENT_OPTS"elif [ "$COMMAND" = "dfsadmin" ] ; then  CLASS=org.apache.hadoop.hdfs.tools.DFSAdmin  HADOOP_OPTS="$HADOOP_OPTS $HADOOP_CLIENT_OPTS"elif [ "$COMMAND" = "mradmin" ] ; then  CLASS=org.apache.hadoop.mapred.tools.MRAdmin  HADOOP_OPTS="$HADOOP_OPTS $HADOOP_CLIENT_OPTS"elif [ "$COMMAND" = "fsck" ] ; then  CLASS=org.apache.hadoop.hdfs.tools.DFSck  HADOOP_OPTS="$HADOOP_OPTS $HADOOP_CLIENT_OPTS"elif [ "$COMMAND" = "balancer" ] ; then  CLASS=org.apache.hadoop.hdfs.server.balancer.Balancer  HADOOP_OPTS="$HADOOP_OPTS $HADOOP_BALANCER_OPTS"elif [ "$COMMAND" = "jobtracker" ] ; then  CLASS=org.apache.hadoop.mapred.JobTracker  HADOOP_OPTS="$HADOOP_OPTS $HADOOP_JOBTRACKER_OPTS"elif [ "$COMMAND" = "tasktracker" ] ; then  CLASS=org.apache.hadoop.mapred.TaskTracker  HADOOP_OPTS="$HADOOP_OPTS $HADOOP_TASKTRACKER_OPTS"elif [ "$COMMAND" = "job" ] ; then  CLASS=org.apache.hadoop.mapred.JobClientelif [ "$COMMAND" = "queue" ] ; then  CLASS=org.apache.hadoop.mapred.JobQueueClientelif [ "$COMMAND" = "pipes" ] ; then  CLASS=org.apache.hadoop.mapred.pipes.Submitter  HADOOP_OPTS="$HADOOP_OPTS $HADOOP_CLIENT_OPTS"elif [ "$COMMAND" = "version" ] ; then  CLASS=org.apache.hadoop.util.VersionInfo  HADOOP_OPTS="$HADOOP_OPTS $HADOOP_CLIENT_OPTS"elif [ "$COMMAND" = "jar" ] ; then  CLASS=org.apache.hadoop.util.RunJarelif [ "$COMMAND" = "distcp" ] ; then  CLASS=org.apache.hadoop.tools.DistCp  CLASSPATH=${CLASSPATH}:${TOOL_PATH}  HADOOP_OPTS="$HADOOP_OPTS $HADOOP_CLIENT_OPTS"elif [ "$COMMAND" = "daemonlog" ] ; then  CLASS=org.apache.hadoop.log.LogLevel  HADOOP_OPTS="$HADOOP_OPTS $HADOOP_CLIENT_OPTS"elif [ "$COMMAND" = "archive" ] ; then  CLASS=org.apache.hadoop.tools.HadoopArchives  CLASSPATH=${CLASSPATH}:${TOOL_PATH}  HADOOP_OPTS="$HADOOP_OPTS $HADOOP_CLIENT_OPTS"elif [ "$COMMAND" = "sampler" ] ; then  CLASS=org.apache.hadoop.mapred.lib.InputSampler  HADOOP_OPTS="$HADOOP_OPTS $HADOOP_CLIENT_OPTS"else  CLASS=$COMMANDfi

# setup ‘java.library.path‘ for native-hadoop code if necessaryJAVA_LIBRARY_PATH=‘‘if [ -d "${HADOOP_HOME}/build/native" -o -d "${HADOOP_HOME}/lib/native" ]; then#通过运行一个java 类来决定当前平台，挺有意思  JAVA_PLATFORM=`CLASSPATH=${CLASSPATH} ${JAVA} -Xmx32m org.apache.hadoop.util.PlatformName | sed -e "s/ /_/g"`    if [ -d "$HADOOP_HOME/build/native" ]; then    JAVA_LIBRARY_PATH=${HADOOP_HOME}/build/native/${JAVA_PLATFORM}/lib  fi    if [ -d "${HADOOP_HOME}/lib/native" ]; then    if [ "x$JAVA_LIBRARY_PATH" != "x" ]; then      JAVA_LIBRARY_PATH=${JAVA_LIBRARY_PATH}:${HADOOP_HOME}/lib/native/${JAVA_PLATFORM}    else      JAVA_LIBRARY_PATH=${HADOOP_HOME}/lib/native/${JAVA_PLATFORM}    fi  fifi

 # run itexec "$JAVA" $JAVA_HEAP_MAX $HADOOP_OPTS -classpath "$CLASSPATH" $CLASS "$@"

2.3、hadoop-daemon.sh       

usage="Usage: hadoop-daemon.sh [--config <conf-dir>] [--hosts hostlistfile] (start|stop) <hadoop-command> <args...>"# if no args specified, show usageif [ $# -le 1 ]; then  echo $usage  exit 1fi

    首先内嵌运行hadoop-env.sh脚本，然后设置HADOOP_PID_DIR等环境变量。

3、启动或停止程序

case $startStop in  (start)    mkdir -p "$HADOOP_PID_DIR"    if [ -f $pid ]; then    #如果程序已经启动的话，就停止，并退出。      if kill -0 `cat $pid` > /dev/null 2>&1; then        echo $command running as process `cat $pid`.  Stop it first.        exit 1      fi    fi    if [ "$HADOOP_MASTER" != "" ]; then      echo rsync from $HADOOP_MASTER      rsync -a -e ssh --delete --exclude=.svn --exclude=‘logs/*‘ --exclude=‘contrib/hod/logs/*‘ $HADOOP_MASTER/ "$HADOOP_HOME"    fi# rotate 当前已经存在的log    hadoop_rotate_log $log    echo starting $command, logging to $log    cd "$HADOOP_HOME"    #通过nohup 和bin/hadoop脚本启动相关程序    nohup nice -n $HADOOP_NICENESS "$HADOOP_HOME"/bin/hadoop --config $HADOOP_CONF_DIR $command "$@" > "$log" 2>&1 < /dev/null &    #获取新启动的进程pid并写入到pid文件中    echo $! > $pid    sleep 1; head "$log"    ;;            (stop)    if [ -f $pid ]; then      if kill -0 `cat $pid` > /dev/null 2>&1; then        echo stopping $command        kill `cat $pid`      else        echo no $command to stop      fi    else      echo no $command to stop    fi    ;;  (*)    echo $usage    exit 1    ;;esac

2.4、slaves.sh

      在所有的机器上运行一组指定的命令（通过ssh无密码登陆），供上层使用。

1、声明使用方法

usage="Usage: slaves.sh [--config confdir] command..."# if no args specified, show usageif [ $# -le 0 ]; then  echo $usage  exit 1fi

# If the slaves file is specified in the command line,# then it takes precedence over the definition in # hadoop-env.sh. Save it here.HOSTLIST=$HADOOP_SLAVESif [ -f "${HADOOP_CONF_DIR}/hadoop-env.sh" ]; then  . "${HADOOP_CONF_DIR}/hadoop-env.sh"fiif [ "$HOSTLIST" = "" ]; then  if [ "$HADOOP_SLAVES" = "" ]; then    export HOSTLIST="${HADOOP_CONF_DIR}/slaves"  else    export HOSTLIST="${HADOOP_SLAVES}"  fifi

#挺重要，里面技术含量也挺高，对远程主机文件进行去除特殊字符和删除空行；对命令行进行空格替换，并通过ssh在目标主机执行命令；最后等待命令在所有目标主机执行完后，退出。for slave in `cat "$HOSTLIST"|sed  "s/#.*$//;/^$/d"`; do ssh $HADOOP_SSH_OPTS $slave $"${@// /\\ }"    2>&1 | sed "s/^/$slave: /" & if [ "$HADOOP_SLAVE_SLEEP" != "" ]; then   sleep $HADOOP_SLAVE_SLEEP fidonewait

2.5、hadoop-daemons.sh

# Run a Hadoop command on all slave hosts.usage="Usage: hadoop-daemons.sh [--config confdir] [--hosts hostlistfile] [start|stop] command args..."# if no args specified, show usageif [ $# -le 1 ]; then  echo $usage  exit 1fi

 #通过salves.sh来实现 exec "$bin/slaves.sh" --config $HADOOP_CONF_DIR cd "$HADOOP_HOME" \; "$bin/hadoop-daemon.sh" --config $HADOOP_CONF_DIR "$@"

      在本机（调用此脚本的主机）启动namenode，在slaves机器上启动datanode，在master机器上启动secondarynamenode，通过调用hadoop-daemon.sh和hadoop-daemons.sh实现。

1、声明使用方式

# Start hadoop dfs daemons.# Optinally upgrade or rollback dfs state.# Run this on master node.usage="Usage: start-dfs.sh [-upgrade|-rollback]"

# start dfs daemons# start namenode after datanodes, to minimize time namenode is up w/o data# note: datanodes will log connection errors until namenode starts#在本机（调用此脚本的主机）启动namenode"$bin"/hadoop-daemon.sh --config $HADOOP_CONF_DIR start namenode $nameStartOpt#在slaves机器上启动datanode"$bin"/hadoop-daemons.sh --config $HADOOP_CONF_DIR start datanode $dataStartOpt#在master机器上启动secondarynamenode"$bin"/hadoop-daemons.sh --config $HADOOP_CONF_DIR --hosts masters start secondarynamenode

2.7、start-mapred.sh 

 # start mapred daemons# start jobtracker first to minimize connection errors at startup#在本机（调用此脚本的主机）启动jobtracker"$bin"/hadoop-daemon.sh --config $HADOOP_CONF_DIR start jobtracker#在master机器上启动tasktracker"$bin"/hadoop-daemons.sh --config $HADOOP_CONF_DIR start tasktracker

其他的脚本就都已经非常简单了，不用再详细说明了，只要看下，大致都能看懂。

对了，最后再说下hadoop的脚本里面用的shell解释器的声明吧。

#!/usr/bin/env bash

大数据时代之hadoop(二)：hadoop脚本解析