操作系統： MAC OS X

一、準備

1、 JDK 1.8

　　下載地址：http://www.oracle.com/technetwork/java/javase/downloads/jdk8-downloads-2133151.html

2、Hadoop CDH

　　下載地址：https://archive.cloudera.com/cdh5/cdh/5/

　　本次安裝版本：hadoop-2.6.0-cdh5.9.2.tar.gz

二、配置SSH（免密碼登錄）

1、打開iTerm2 終端，輸入：ssh-keygen -t rsa ，回車，next -- 生成秘鑰
2、cat id_rsa_xxx.pub >> authorized_keys -- 用於授權你的公鑰到本地可以無密碼登錄
3、chmod 600 authorized_keys -- 賦權限
4、ssh localhost -- 免密碼登錄，如果顯示最後一次登錄時間，則登錄成功

三、配置Hadoop&環境變量

1、創建hadoop目錄&解壓

　　mkdir -p work/install/hadoop-cdh5.9.2 -- hadoop 主目錄
　　mkdir -p work/install/hadoop-cdh5.9.2/current/tmp work/install/hadoop-cdh5.9.2/current/nmnode work/install/hadoop-cdh5.9.2/current/dtnode -- hadoop 臨時、名稱節點、數據節點目錄

　　tar -xvf hadoop-2.6.0-cdh5.9.2.tar.gz -- 解壓包

2、配置 .bash_profile 環境變量

1 HADOOP_HOME="/Users/kimbo/work/install/hadoop-cdh5.9.2/hadoop-2.6.0-cdh5.9.2"
2 
3 JAVA_HOME="/Library/Java/JavaVirtualMachines/jdk1.8.0_152.jdk/Contents/Home"
4 HADOOP_HOME="/Users/kimbo/work/install/hadoop-cdh5.9.2/hadoop-2.6.0-cdh5.9.2"
5 
6 PATH="/usr/local/bin:~/cmd:$JAVA_HOME/bin:$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$PATH
 
"
7 CLASSPATH=".:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar"
8 
9 export JAVA_HOME PATH CLASSPATH HADOOP_HOME

　　source .bash_profile -- 生效環境變量

3、修改配置文件（重點）

　　cd $HADOOP_HOME/etc/hadoop

• core-site.xml

<configuration>
  <property>
    <name>hadoop.tmp.dir</name>
    <value>/Users/zhangshaosheng/work/install/hadoop-cdh5.9.2/current/tmp</value>
  </property>
  <property>
    <name>fs.defaultFS</name>
    <value>hdfs://localhost:8020</value>
  </property>
  <property>
    <name>fs.trash.interval</name>
    <value>4320</value>
    <description> 3 days = 60min*24h*3day </description>
  </property>
</configuration>

• hdfs-site.xml

 1 <configuration>
 2   <property>
 3     <name>dfs.namenode.name.dir</name>
 4     <value>/Users/zhangshaosheng/work/install/hadoop-cdh5.9.2/current/nmnode</value>
 5   </property>
 6   <property>
 7     <name>dfs.datanode.data.dir</name>
 8     <value>/Users/zhangshaosheng/work/install/hadoop-cdh5.9.2/current/dtnode</value>
 9   </property>
10   <property>
11     <name>dfs.datanode.http.address</name>
12     <value>localhost:50075</value>
13   </property>
14   <property>
15     <name>dfs.replication</name>
16     <value>1</value>
17   </property>
18   <property>
19     <name>dfs.permissions.enabled</name>
20     <value>false</value>
21   </property>
22 </configuration>

• yarn-site.xml

 1 <configuration> 
 2  <property>
 3     <name>yarn.nodemanager.aux-services</name>
 4     <value>mapreduce_shuffle</value>
 5   </property>
 6   <property>
 7     <name>yarn.log-aggregation-enable</name>
 8     <value>true</value>
 9     <description>Whether to enable log aggregation</description>
10   </property>
11   <property>
12     <name>yarn.nodemanager.remote-app-log-dir</name>
13     <value>/Users/zhangshaosheng/work/install/hadoop-cdh5.9.2/current/tmp/yarn-logs</value>
14     <description>Where to aggregate logs to.</description>
15   </property>
16   <property>
17     <name>yarn.nodemanager.resource.memory-mb</name>
18     <value>8192</value>
19     <description>Amount of physical memory, in MB, that can be allocated
20       for containers.</description>
21   </property>
22   <property>
23     <name>yarn.nodemanager.resource.cpu-vcores</name>
24     <value>2</value>
25     <description>Number of CPU cores that can be allocated
26       for containers.</description>
27   </property>
28   <property>
29     <name>yarn.scheduler.minimum-allocation-mb</name>
30     <value>1024</value>
31     <description>The minimum allocation for every container request at the RM,
32       in MBs. Memory requests lower than this won‘t take effect,
33       and the specified value will get allocated at minimum.</description>
34   </property>
35   <property>
36     <name>yarn.scheduler.maximum-allocation-mb</name>
37     <value>2048</value>
38     <description>The maximum allocation for every container request at the RM,
39       in MBs. Memory requests higher than this won‘t take effect,
40       and will get capped to this value.</description>
41   </property>
42   <property>
43     <name>yarn.scheduler.minimum-allocation-vcores</name>
44     <value>1</value>
45     <description>The minimum allocation for every container request at the RM,
46       in terms of virtual CPU cores. Requests lower than this won‘t take effect,
47       and the specified value will get allocated the minimum.</description>
48   </property>
49   <property>
50     <name>yarn.scheduler.maximum-allocation-vcores</name>
51     <value>2</value>
52     <description>The maximum allocation for every container request at the RM,
53       in terms of virtual CPU cores. Requests higher than this won‘t take effect,
54       and will get capped to this value.</description>
55   </property>
56 </configuration>

• mapred-site.xml

 1  <property>
 2     <name>mapreduce.jobtracker.address</name>
 3     <value>localhost:8021</value>
 4   </property>
 5   <property>
 6     <name>mapreduce.jobhistory.done-dir</name>
 7     <value>/Users/zhangshaosheng/work/install/hadoop-cdh5.9.2/current/tmp/job-history/</value>
 8     <description></description>
 9   </property>
10   <property>
11     <name>mapreduce.framework.name</name>
12     <value>yarn</value>
13     <description>The runtime framework for executing MapReduce jobs.
14     Can be one of local, classic or yarn.
15     </description>
16   </property>
17 
18   <property>
19     <name>mapreduce.map.cpu.vcores</name>
20     <value>1</value>
21     <description>
22         The number of virtual cores required for each map task.
23     </description>
24   </property>
25   <property>
26     <name>mapreduce.reduce.cpu.vcores</name>
27     <value>1</value>
28     <description>
29         The number of virtual cores required for each reduce task.
30     </description>
31   </property>
32 
33   <property>
34     <name>mapreduce.map.memory.mb</name>
35     <value>1024</value>
36     <description>Larger resource limit for maps.</description>
37   </property>
38   <property>
39     <name>mapreduce.reduce.memory.mb</name>
40     <value>1024</value>
41     <description>Larger resource limit for reduces.</description>
42   </property>
43 <configuration>
44   <property>
45     <name>mapreduce.map.java.opts</name>
46     <value>-Xmx768m</value>
47     <description>Heap-size for child jvms of maps.</description>
48   </property>
49   <property>
50     <name>mapreduce.reduce.java.opts</name>
51     <value>-Xmx768m</value>
52     <description>Heap-size for child jvms of reduces.</description>
53   </property>
54 
55   <property>
56     <name>yarn.app.mapreduce.am.resource.mb</name>
57     <value>1024</value>
58     <description>The amount of memory the MR AppMaster needs.</description>
59   </property>
60 </configuration>

• hadoop-env.sh

export JAVA_HOME=${JAVA_HOME} -- 添加 java環境變量

四、啟動

　　1、格式化

　　　　hdfs namenode -format

　　如果hdfs命令識別不了， 檢查環境變量，是否配置正確了。

　　2、啟動

　　　　cd $HADOOP_HOME/sbin

　　　　執行命名：start-all.sh ,按照提示，輸入密碼

五、驗證

　　1、在終端輸入： jps　

　　　　出現如下截圖，說明ok了

　　2、登錄web頁面

　　　　a）HDFS : http://localhost:50070/dfshealth.html#tab-overview

　　　　b）YARN Cluster: http://localhost:8088/cluster

　　　　c）YARN ResourceManager/NodeManager: http://localhost:8042/node

Mac Hadoop2.6（CDH5.9.2）偽分布式集群安裝