centos7无cm安装hadoop+spark

配置内核参数后重启生效
# echo 'vm.swappiness=10'>> /etc/sysctl.conf

安装JDK8
# rpm -ivh jdk-8u211-linux-x64.rpm
# vi /etc/profile
export JAVA_HOME=/usr/java/jdk1.8.0_211-amd64
export CLASSPATH=.:$JAVA_HIOME/jre/lib/rt.jar:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar
# source /etc/profile

总结
1.无CM使用rpm的方式安装CDH6.2.0与之前安装CDH5.10.0基本没有太大的区别。
2.此安装方式需要下载相关的所有rpm包到服务器，然后制作本地的yum源进行安装，下载的包的总大小在4.3G左右。
3.同样的在安装过程中需要最先安装Zookeeper。

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3.1 Zookeeper
1.在所有节点安装Zookeeper
# yum -y install zookeeper

2.创建数据目录并修改属主
# mkdir -p /var/lib/zookeeper
# chown -R zookeeper /var/lib/zookeeper

3.修改配置文件/etc/zookeeper/conf/zoo.cfg
maxClientCnxns=60
tickTime=2000
initLimit=10
syncLimit=5
dataDir=/var/lib/zookeeper
clientPort=2181
dataLogDir=/var/lib/zookeeper
minSessionTimeout=4000
maxSessionTimeout=40000
server.1=gp-mdw:3181:4181
server.2=gp-data-1:3181:4181
server.3=gp-data-2:3181:4181

4.所有节点创建myid文件并修改属主
【gp-mdw】# echo 1 > /var/lib/zookeeper/myid
【gp-mdw】# chown zookeeper:zookeeper myid
ssh gp-data-1 -e "echo 2 > /var/lib/zookeeper/myid"
ssh gp-data-2 -e "echo 3 > /var/lib/zookeeper/myid"

5.所有节点启动Zookeeper
【gp-data-2】# /usr/lib/zookeeper/bin/zkServer.sh start
【gp-data-1】# /usr/lib/zookeeper/bin/zkServer.sh start
【gp-mdw】 # /usr/lib/zookeeper/bin/zkServer.sh start

查看所有节点启动状态，三个节点均启动成功
# /usr/lib/zookeeper/bin/zkServer.sh status
JMX enabled by default
Using config: /usr/lib/zookeeper/bin/../conf/zoo.cfg
Mode: follower

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3.2 HDFS
1.在所有节点安装HDFS必需的包，由于只有三个节点，所以三个节点都安装DataNode
yum -y install hadoop hadoop-hdfs hadoop-client hadoop-doc hadoop-debuginfo hadoop-hdfs-datanode
2.在一个节点安装NameNode以及SecondaryNameNode
yum -y install hadoop-hdfs-namenode hadoop-hdfs-secondarynamenode

3.创建数据目录并修改属主和权限
所有节点创建DataNode的目录
mkdir -p /data0/dfs/dn
chown -R hdfs:hadoop /data0/dfs/dn
chmod 700 /data0/dfs/dn

NameNode和SecondaryNameNode节点创建数据目录
mkdir -p /data0/dfs/nn
chown -R hdfs:hadoop /data0/dfs/nn
chmod 700 /data0/dfs/nn
mkdir -p /data0/dfs/snn
chown -R hdfs:hadoop /data0/dfs/snn
chmod 700 /data0/dfs/snn

4.修改配置文件
# /etc/hadoop/conf/core-site.xml
<configuration>
<property>
<name>fs.defaultFS</name>
<value>hdfs://gp-mdw:8020</value>
</property>
<property>
<name>fs.trash.interval</name>
<value>1</value>
</property>
<property>
<name>io.compression.codecs</name>
<value>org.apache.hadoop.io.compress.DefaultCodec,org.apache.hadoop.io.compress.GzipCodec,org.apache.hadoop.io.compress.BZip2Codec,org.apache.hadoop.io.compress.DeflateCodec,org.apache.hadoop.io.compress.SnappyCodec,org.apache.hadoop.io.compress.Lz4Codec</value>
</property>
</configuration>

# vi /etc/hadoop/conf/hdfs-site.xml
<configuration>
<property>
<name>dfs.namenode.name.dir</name>
<value>file:///data0/dfs/nn</value>
</property>
<property>
<name>dfs.datanode.data.dir</name>
<value>file:///data0/dfs/dn</value>
</property>
<property>
<name>dfs.namenode.servicerpc-address</name>
<value>gp-mdw:8022</value>
</property>
<property>
<name>dfs.https.address</name>
<value>gp-mdw:9871</value>
</property>
<property>
<name>dfs.secondary.http.address</name>
<value>gp-mdw:50090</value>
</property>
<property>
<name>dfs.https.port</name>
<value>9871</value>
</property>
<property>
<name>dfs.namenode.http-address</name>
<value>gp-mdw:9870</value>
</property>
<property>
<name>dfs.replication</name>
<value>3</value>
</property>
<property>
<name>dfs.blocksize</name>
<value>134217728</value>
</property>
<property>
<name>dfs.namenode.checkpoint.dir</name>
<value>file:///data0/dfs/snn</value>
</property>
</configuration>

5.将修改的配置文件保存并同步到所有节点
scp /etc/hadoop/conf/core-site.xml gp-data-1:/etc/hadoop/conf
scp /etc/hadoop/conf/core-site.xml gp-data-2:/etc/hadoop/conf
scp /etc/hadoop/conf/hdfs-site.xml gp-data-1:/etc/hadoop/conf
scp /etc/hadoop/conf/hdfs-site.xml gp-data-2:/etc/hadoop/conf

6.格式化NameNode
sudo -u hdfs hdfs namenode -format

7.在所有节点运行命令启动HDFS
【gp-mdw】systemctl start hadoop-hdfs-namenode
【gp-mdw】systemctl start hadoop-hdfs-secondarynamenode
全部： systemctl start hadoop-hdfs-datanode
【gp-mdw】systemctl status hadoop-hdfs-namenode
【gp-mdw】systemctl status hadoop-hdfs-secondarynamenode
全部： systemctl status hadoop-hdfs-datanode

8.创建/tmp临时目录，并设置目录权限，然后使用hadoop命令查看创建的目录成功
sudo -u hdfs hadoop fs -mkdir /tmp
sudo -u hdfs hadoop fs -chmod -R 1777 /tmp

9.访问NameNode的Web UI
http://gp-mdw:8020

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3.3 Yarn
1.安装Yarn的包，在一个节点安装ResourceManager和JobHistory Server，所有节点安装NodeManager
【gp-mdw】 # yum -y install hadoop-yarn hadoop-yarn-resourcemanager hadoop-mapreduce-historyserver hadoop-yarn-proxyserver hadoop-mapreduce
全部： # yum -y install hadoop-yarn hadoop-yarn-nodemanager hadoop-mapreduce

2.创建目录并修改属主和权限
在所有节点创建本地目录
mkdir -p /data0/yarn/nm
chown yarn:hadoop /data0/yarn/nm
mkdir -p /data0/yarn/container-logs
chown yarn:hadoop /data0/yarn/container-logs

在HDFS上创建logs目录
sudo -u hdfs hdfs dfs -mkdir /tmp/logs
sudo -u hdfs hdfs dfs -chown mapred:hadoop /tmp/logs
sudo -u hdfs hdfs dfs -chmod 1777 /tmp/logs

在HDFS上创建/user/history目录
sudo -u hdfs hdfs dfs -mkdir -p /user
sudo -u hdfs hdfs dfs -chmod 777 /user
sudo -u hdfs hdfs dfs -mkdir -p /user/history
sudo -u hdfs hdfs dfs -chown mapred:hadoop /user/history
sudo -u hdfs hdfs dfs -chmod 1777 /user/history
sudo -u hdfs hdfs dfs -mkdir -p /user/history/done
sudo -u hdfs hdfs dfs -mkdir -p /user/history/done_intermediate
sudo -u hdfs hdfs dfs -chown -R mapred:hadoop /user/history
sudo -u hdfs hdfs dfs -chmod 771 /user/history/done
sudo -u hdfs hdfs dfs -chmod 1777 /user/history/done_intermediate

3.修改配置文件
# vi /etc/hadoop/conf/yarn-site.xml
<configuration>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
<property>
<name>yarn.nodemanager.aux-services.mapreduce_shuffle.class</name>
<value>org.apache.hadoop.mapred.ShuffleHandler</value>
</property>
<property>
<name>yarn.log-aggregation-enable</name>
<value>true</value>
</property>
<property>
<name>yarn.nodemanager.local-dirs</name>
<value>file:///data0/yarn/nm</value>
</property>
<property>
<name>yarn.nodemanager.log-dirs</name>
<value>file:///data0/yarn/container-logs</value>
</property>
<property>
<name>yarn.nodemanager.remote-app-log-dir</name>
<value>/tmp/logs</value>
</property>
<property>
<name>yarn.application.classpath</name>
<value>$HADOOP_CONF_DIR,$HADOOP_COMMON_HOME/*,$HADOOP_COMMON_HOME/lib/*,$HADOOP_HDFS_HOME/*,$HADOOP_HDFS_HOME/lib/*,$HADOOP_MAPRED_HOME/*,$HADOOP_MAPRED_HOME/lib/*,$HADOOP_YARN_HOME/*,$HADOOP_YARN_HOME/lib/*</value>
</property>
<property>
<name>yarn.resourcemanager.address</name>
<value>gp-mdw:8032</value>
</property>
<property>
<name>yarn.resourcemanager.admin.address</name>
<value>gp-mdw:8033</value>
</property>
<property>
<name>yarn.resourcemanager.scheduler.address</name>
<value>gp-mdw:8030</value>
</property>
<property>
<name>yarn.resourcemanager.resource-tracker.address</name>
<value>gp-mdw:8031</value>
</property>
<property>
<name>yarn.resourcemanager.webapp.address</name>
<value>gp-mdw:8088</value>
</property>
<property>
<name>yarn.resourcemanager.webapp.https.address</name>
<value>gp-mdw:8090</value>
</property>
</configuration>

# vi /etc/hadoop/conf/mapred-site.xml
<configuration>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
<property>
<name>mapreduce.jobhistory.address</name>
<value>gp-mdw:10020</value>
</property>
<property>
<name>mapreduce.jobhistory.webapp.address</name>
<value>gp-mdw:19888</value>
</property>
<property>
<name>mapreduce.jobhistory.webapp.https.address</name>
<value>gp-mdw:19890</value>
</property>
<property>
<name>mapreduce.jobhistory.admin.address</name>
<value>gp-mdw:10033</value>
</property>
<property>
<name>yarn.app.mapreduce.am.staging-dir</name>
<value>/user</value>
</property>
</configuration>

# /etc/hadoop/conf/core-site.xml，下面只贴出修改的部分配置
<property>
<name>hadoop.proxyuser.mapred.groups</name>
<value>*</value>
</property>
<property>
<name>hadoop.proxyuser.mapred.hosts</name>
<value>*</value>
</property>

将修改的配置文件保存并同步到所有节点
scp /etc/hadoop/conf/core-site.xml gp-data-1:/etc/hadoop/conf
scp /etc/hadoop/conf/core-site.xml gp-data-2:/etc/hadoop/conf
scp /etc/hadoop/conf/yarn-site.xml gp-data-1:/etc/hadoop/conf
scp /etc/hadoop/conf/yarn-site.xml gp-data-2:/etc/hadoop/conf
scp /etc/hadoop/conf/mapred-site.xml gp-data-1:/etc/hadoop/conf
scp /etc/hadoop/conf/mapred-site.xml gp-data-2:/etc/hadoop/conf

5.启动Yarn服务
在JobHistoryServer节点上启动mapred-historyserver
【gp-mdw】/etc/init.d/hadoop-mapreduce-historyserver start

在RM节点启动ResourceManager
【gp-mdw】systemctl start hadoop-yarn-resourcemanager
【gp-mdw】systemctl status hadoop-yarn-resourcemanager

在NM节点启动NodeManager
【全部】systemctl start hadoop-yarn-nodemanager
【全部】systemctl status hadoop-yarn-nodemanager

6.访问Yarn服务的Web UI
Yarn的管理页面
JobHistory的管理页面
查看在线的节点
<name>mapreduce.jobhistory.address</name>
<value>gp-mdw:10020</value>
<name>mapreduce.jobhistory.webapp.address</name>
<value>gp-mdw:19888</value>
<name>mapreduce.jobhistory.webapp.https.address</name>
<value>gp-mdw:19890</value>
<name>mapreduce.jobhistory.admin.address</name>
<value>gp-mdw:10033</value>

7.运行MR示例程序
使用root用户运行示例程序，所以要先创建root用户的目录
sudo -u hdfs hdfs dfs -mkdir /user/root
sudo -u hdfs hdfs dfs -chown root:root /user/root
运行MR示例程序，运行成功
hadoop jar /usr/lib/hadoop-mapreduce/hadoop-mapreduce-examples.jar pi 5 5

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3.4 Spark
1.安装Spark所需的包
【gp-mdw】yum -y install spark-core spark-master spark-worker spark-history-server spark-python

2.创建目录并修改属主和权限
sudo -u hdfs hadoop fs -mkdir /user/spark
sudo -u hdfs hadoop fs -mkdir /user/spark/applicationHistory
sudo -u hdfs hadoop fs -chown -R spark:spark /user/spark
sudo -u hdfs hadoop fs -chmod 1777 /user/spark/applicationHistory

3.修改配置文件/etc/spark/conf/spark-defaults.conf
spark.eventLog.enabled=true
spark.eventLog.dir=hdfs://gp-mdw:8020/user/spark/applicationHistory
spark.yarn.historyServer.address=http://gp-mdw:18088

4.启动spark-history-server
【gp-mdw】systemctl start spark-history-server
【gp-mdw】systemctl status spark-history-server
访问Web UI

//5.修改配置文件并同步到所有节点
//scp /etc/spark/conf/spark-defaults.conf gp-data-1:/etc/spark/conf
//scp /etc/spark/conf/spark-defaults.conf gp-data-2:/etc/spark/conf

6.测试Spark使用
spark-submit --class org.apache.spark.examples.SparkPi --master local /usr/lib/spark/examples/jars/spark-examples_2.11-2.4.0-cdh6.3.2.jar
2020-03-15 10:01:56 INFO DAGScheduler:57 - Job 0 finished: reduce at SparkPi.scala:38, took 1.052675 s
Pi is roughly 3.143435717178586

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由于centos7原本就安装了Python2，而且这个Python2不能被删除，因为有很多系统命令，比如yum都要用到。
安装python3.7之前需要先安装一些依赖
yum -y install zlib-devel bzip2-devel openssl-devel openssl-static ncurses-devel sqlite-devel readline-devel tk-devel gdbm-devel db4-devel libpcap-devel xz-devel libffi-devel lzma gcc
wget https://www.python.org/ftp/python/3.7.7/Python-3.7.7.tar.xz

mkdir /usr/local/python3

然后解压压缩包，进入该目录，安装Python3
tar -xvJf Python-3.7.7.tar.xz
cd Python-3.7.7
./configure --prefix=/usr/local/python3 --enable-shared
make && make install

最后创建软链接
ln -s /usr/local/python3/bin/python3 /usr/bin/python3
ln -s /usr/local/python3/bin/pip3 /usr/bin/pip3

在命令行中输入python3测试
# echo "/usr/local/python3/lib" > /etc/ld.so.conf.d/python3-x86_64.conf
# ldconfig -v

# vi /etc/profile
export PYSPARK_PYTHON=/usr/bin/python3
export PYSPARK_DRIVER_PYTHON=/usr/bin/python3
# source /etc/profile
# pyspark 调用的是就是python3.7

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