hadoop+spark安装

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master: 192.168.56.102

slave:[192.168.56.106, 192.168.56.107,192.168.56.108]

下载和配置环境变量

master节点

/etc/profile

export JAVA_HOME=/usr/local/java/jdk1.7.0_75
export PATH=$JAVA_HOME/bin/:$PATH
export CLASSPATH=.:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar
export HADOOP_HOME=/home/u2/hadoop-2.6.0
export PATH=$PATH:$HADOOP_HOME/bin


export M2_HOME=/home/u2/apache-maven-3.3.1
export PATH=$M2_HOME/bin:$PATH

export SCALA_HOME=/usr/local/scala/scala-2.11.6
export PATH=$SCALA_HOME/bin:$PATH
export SPARK_HOME=/home/u2/spark-1.3.0-bin-hadoop2.4
export PATH=$SPARK_HOME/bin:$PATH

cd ~/hadoop-2.6.0/

etc/hadoop/core-site.xml

<configuration>
    <property>
        <name>hadoop.tmp.dir</name>
        <value>/home/u2/hadoopdata/tmp</value>
        <description>Abase for other temporary directories.</description>
    </property>
    <property>
        <name>fs.defaultFS</name>
        <value>hdfs://192.168.56.102:9000</value>
    </property>
    <property>
        <name>io.file.buffer.size</name>
        <value>4096</value>
    </property>
</configuration>

etc/hadoop/hdfs-site.xml

<configuration>
    <property>
    	<name>dfs.nameservices</name>
        <value>hadoop-cluster1</value>
    </property>
    <property>
        <name>dfs.namenode.secondary.http-address</name>
        <value>192.168.56.102:50090</value>
    </property>
    <property>
        <name>dfs.namenode.name.dir</name>
        <value>file:///home/u2/hadoopdata/dfs/name</value>
    </property>
    <property>
        <name>dfs.datanode.data.dir</name>
        <value>file:///home/u2/hadoopdata/dfs/data</value>
    </property>
    <property>
        <name>dfs.replication</name>
        <value>2</value>
    </property>
    <property>
        <name>dfs.webhdfs.enabled</name>
        <value>true</value>
    </property>
</configuration>

etc/hadoop/yarn-site.xml

<configuration>

<!-- Site specific YARN configuration properties -->
    <property>
        <name>yarn.nodemanager.aux-services</name>
        <value>mapreduce_shuffle</value>
    </property>
    <property>
        <name>yarn.resourcemanager.address</name>
        <value>192.168.56.102:8032</value>
    </property>
    <property>
        <name>yarn.resourcemanager.scheduler.address</name>
        <value>192.168.56.102:8030</value>
    </property>
    <property>
        <name>yarn.resourcemanager.resource-tracker.address</name>
        <value>192.168.56.102:8031</value>
    </property>
    <property>
        <name>yarn.resourcemanager.admin.address</name>
        <value>192.168.56.102:8033</value>
    </property>
    <property>
        <name>yarn.resourcemanager.webapp.address</name>
        <value>192.168.56.102:8088</value>
    </property>
</configuration>

etc/hadoop/mapred-site.xml

<configuration>
    <property>
        <name>mapreduce.framework.name</name>
        <value>yarn</value>
    </property>
    <property>
        <name>mapreduce.jobtracker.http.address</name>
        <value>192.168.56.102:50030</value>
    </property>
    <property>
        <name>mapreduce.jobhistory.address</name>
        <value>192.168.56.102:10020</value>
    </property>
    <property>
        <name>mapreduce.jobhistory.webapp.address</name>
        <value>192.168.56.102:19888</value>
    </property>
</configuration>

etc/hadoop/hadoop-env.sh 增加

export JAVA_HOME=/usr/local/java/jdk1.7.0_75

etc/hadoop/slaves

192.168.56.106
192.168.56.107
192.168.56.108

cd ~/spark-1.3.0-bin-hadoop2.4/

conf/spark-env.sh增加

export SCALA_HOME=/usr/local/scala/scala-2.11.6
export JAVA_HOME=/usr/local/java/jdk1.7.0_75
export SPARK_MASTER_IP=192.168.56.102
export SPARK_WORKER_MEMORY=1000m
export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop

conf/slaves

192.168.56.102
192.168.56.106
192.168.56.107
192.168.56.108

ssh-keygen -t rsa

ssh-copy-id -i ~/.ssh/id_rsa.pub u2@192.168.56.106

ssh-copy-id -i ~/.ssh/id_rsa.pub u2@192.168.56.107

ssh-copy-id -i ~/.ssh/id_rsa.pub u2@192.168.56.108

cd ~/

scp -r spark-1.3.0-bin-hadoop2.4 u2@192.168.56.106:~/

scp -r hadoop-2.6.0 u2@192.168.56.106:~/

scp -r spark-1.3.0-bin-hadoop2.4 u2@192.168.56.107:~/

scp -r hadoop-2.6.0 u2@192.168.56.107:~/

scp -r spark-1.3.0-bin-hadoop2.4 u2@192.168.56.108:~/

scp -r hadoop-2.6.0 u2@192.168.56.108:~/

3个slave环境变量配好。记得source /etc/profile

cd ~/hadoop-2.6.0/
./sbin/start-all.sh
cd ~/spark-1.3.0-bin-hadoop2.4/
./sbin/start-all.sh

打开http://192.168.56.102:8088/cluster/nodes

打开http://192.168.56.102:8080/

cd ~/hadoop
hdfs dfs -mkdir /input/json/
hdfs dfs -put friends_timeline.json   /input/json/friends_timeline.json

cd ~/spark-1.3.0-bin-hadoop2.4 

./bin/spark-submit --class org.apache.spark.examples.SparkPi --master yarn --deploy-mode cluster --executor-cores 1 --queue default examples/jars/spark-examples*.jar 10

./bin/spark-shell
scala>import org.apache.spark.SparkContext._ 
scala>val sqlContext = new org.apache.spark.sql.SQLContext(sc) 
scala>val table = sqlContext.jsonFile("hdfs://192.168.56.102:9000/input/json/friends_timeline") 
scala>table.printSchema()