一、hadoop 简介

hadoop是一个由Apache基金会所开发的分布式系统基础架构。用户能够在不理解分布式底层细节的状况下，开发分布式程序。充分利用集群的威力进行高速运算和存储。

龙芯3A2000上运行Hadoop

hadoop实现了一个分布式文件系统（hadoop Distributed File System），简称HDFS。HDFS有高容错性的特点，并且设计用来部署在低廉的（low-cost）硬件上；而且它提供高吞吐量（high throughput）来拜访应用程序的数据，适宜那些有着超大数据集（large data set）的应用程序。HDFS放宽了（relax）POSIX的要求，能够以流的模式拜访（streaming access）文件系统中的数据。

hadoop的框架最外围的设计就是：HDFS和MapReduce。HDFS为海量的数据提供了存储，则MapReduce为海量的数据提供了计算。

hadoop是一个可能对大量数据进行分布式解决的软件框架, 它以一种牢靠、高效、可伸缩的形式进行数据处理。保护多个工作数据正本，确保可能针对失败的节点从新散布解决。并行工作形式，进步处理速度,之处解决PB级数据。
hadoop是一个可能让用户轻松架构和应用的分布式计算平台。用户能够轻松地在hadoop上开发和运行解决海量数据的应用程序。它次要有以下几个长处：

高可靠性: hadoop按位存储和解决数据的能力值得人们信赖。
高扩展性: hadoop是在可用的计算机集簇间调配数据并实现计算工作的，这些集簇能够不便地扩大到数以千计的节点中。
高效性: hadoop可能在节点之间动静地挪动数据，并保障各个节点的动态平衡，因而处理速度十分快。
高容错性:hadoop可能主动保留数据的多个正本，并且可能主动将失败的工作重新分配。

低成本: 与一体机、商用数据仓库以及QlikView、Yonghong Z-Suite等数据集市相比，hadoop是开源的，我的项目的软件老本因而会大大降低。

   本文次要波及以下内容：hadoop源码编译，hadoop在分布式计算云存储系统中的部署和利用,同时也将记录hadoop搭建过程的FAQ和绝对解决方案。

hadoop 集群(cluster) 反对如下3种操作模式：

Local/Standalone Mode：实现下载后，默认状况下hadoop 被配置为Standalone 模式，作为单个Java
Pseudo Distributed Mode
此种模式下,每个hadoop 守护过程,如hdfs,yarn,MapReduce 等分布式部署在不同的机器上，别离作为独立的Java 过程，这种模式有助于开发。
Fully Distributed Mode
齐全分布式部署，须要至多2台机器，作为一个集群，稍后进行详解。

二、移植环境

首先给出本机的软硬件信息，

软件环境：

(1)loongnix1.0 零碎（2016.8.10版本）。下载地址 www.loongnix.org
(2)内核版本:3.10.84-all
(3)JDK版本:1.8.0_25-rc16-b17 or later
(4)MAVEN:3.2.2 or later

硬件环境:

(1)开发板类型: Loongson-3B-780E-2w-V0.2-demo
(2)固件版本: loongson-PMON-V3.3.0

本例中应用的hadoop的版本为2.7.2, hadoop 源码下载地址，参见附录中的”hadoop downloads” 链接。hadoop 编译依赖findbugs和cmake软件包，倡议在编译前通过yum 命令进行主动装置,装置形式如下:

[hadoop@localhost log]$ sudo yum -y install java-1.8.0-openjdk-devel java-1.8.0-openjdk-headless \ java-1.8.0-openjdk findbugs cmake  protobuf-compiler

实现装置后，须要设置如下环境变量，倡议将以下内容追加到/et c/profile文件,并用source 命令使其失效。

export FINDBUGS_HOME=/usr/share/findbugsexport MAVEN_HOME=/usr/share/mavenexport MAVEN_OPTS="-Xms256m -Xmx512m"export JAVA_HOME=/usr/lib/jvm/java-1.8.0-openjdk-1.8.0.25-5.rc16.fc21.loongson.mPATH=/usr/lib64/ccache:/usr/local/bin:/bin:/usr/bin:/usr/local/sbin:/usr/sbin:/hexport PATH=$PATH:$JAVA_HOME/bin:$MAVEN_HOME/bin

Build From Scratch：首先解压源码到自定义目录(本例采纳/usr/local)利用mvn

clean package -Pdist,native,src -DskipTests -Dtar 命令进行编译。tar xvf hadoop-2.7.2.src.gz -C mkdir /usr/local/cd  /usr/local/hadoop-2.7.2mvn clean package -Pdist,native,src -DskipTests -Dtar

三、注意事项

(1)本例中采纳/usr/local 作为工作目录须要root权限
(2)编译过程报错,可参见对应FAQ,问题解决后，通过mvn package -Pdist,native,src -DskipTests -Dtar 命令再次启动编译。
(3)FAQ的标识由序号(从001开始)和模块名组成,其中者通过冒号距离。模块名源自maven Reactor 波及的modules名称。

四、FAQ

001:Apache hadoop Common

终端报错:

 ## A fatal error has been detected by the Java Runtime Environment:##  SIGSEGV (0xb) at pc=0x000000ffe18f46fc, pid=5300, tid=1099154321904## JRE version: OpenJDK Runtime Environment (8.0_25-b17) (build 1.8.0_25-rc16-b17)# Java VM: OpenJDK 64-Bit Server VM (25.25-b02 mixed mode linux- compressed oops)# Problematic frame:# J 62748 C2 scala.tools.asm.ClassWriter.get(Lscala/tools/asm/Item;)Lscala/tools/asm/Item; (49 bytes) @ 0x000000ffe18f46fc [0x000000ffe18f46a0+0x5c]## Failed to write core dump. Core dumps have been disabled. To enable core dumping, try "ulimit -c unlimited" before starting Java again## If you would like to submit a bug report, please visit:#   http://bugreport.sun.com/bugreport/crash.jsp#

解决办法:

此问题与JDK的并行GC相干,编译hadoop和spark均有遇到,目前的解决办法:调整/etc/profile 文件MAVEN_OPTS 环境变量为如下内容:

export MAVEN_OPTS="-Xms3560m -Xmx3560m -XX:-UseParallelGC -XX:-UseParallelOldGC"002: any-modules

终端景象: maven 编译过程中构件(xxx.jar和xxx.pom) 无奈下载。
解决办法: 关上maven 配置文件的代理设置选项,并重新安装ca-certificates

为maven 设置代理

<proxies>    <!-- proxy     | Specification for one proxy, to be used in connecting to the network.     |-->    <proxy>      <id>proxy01</id>      <active>true</active>      <protocol>http</protocol>      <host>ip_address</host>      <port>port</port>      <nonProxyHosts>localhost</nonProxyHosts>    </proxy>    <proxy>      <id>proxy02</id>      <active>true</active>      <protocol>https</protocol>      <host>ip_address</host>      <port>port</port>      <nonProxyHosts>localhost</nonProxyHosts>    </proxy>  </proxies>

重新安装ca-certificates

Sudo yum -y install ca-certificates

注意事项: 凡呈现Maven 编译过程构件无奈下载，均可参考本FAQ内容进行适当批改。

五、编译后果

Maven编译通过后，将在终端显示hadoop 的maven Reactor(本次编译的所有maven 模块)和编译工夫信息。上面给出的时耗信息，防御参考不同软硬件平台将会产生差别。

[INFO] ------------------------------------------------------------------------[INFO] Reactor Summary:[INFO][INFO] Apache hadoop Main ................................. SUCCESS [ 10.769 s][INFO] Apache hadoop Project POM .......................... SUCCESS [  8.793 s][INFO] Apache hadoop Annotations .......................... SUCCESS [ 18.834 s][INFO] Apache hadoop Assemblies ........................... SUCCESS [  2.414 s][INFO] Apache hadoop Project Dist POM ..................... SUCCESS [  9.653 s][INFO] Apache hadoop Maven Plugins ........................ SUCCESS [ 25.215 s][INFO] Apache hadoop MiniKDC .............................. SUCCESS [ 20.682 s][INFO] Apache hadoop Auth ................................. SUCCESS [ 26.240 s][INFO] Apache hadoop Auth Examples ........................ SUCCESS [ 23.112 s][INFO] Apache hadoop Common ............................... SUCCESS [45:23 min][INFO] Apache hadoop NFS .................................. SUCCESS [ 45.079 s][INFO] Apache hadoop KMS .................................. SUCCESS [01:27 min][INFO] Apache hadoop Common Project ....................... SUCCESS [  1.104 s][INFO] Apache hadoop HDFS ................................. SUCCESS [21:45 min][INFO] Apache hadoop HttpFS ............................... SUCCESS [02:13 min][INFO] Apache hadoop HDFS BookKeeper Journal .............. SUCCESS [ 47.832 s][INFO] Apache hadoop HDFS-NFS ............................. SUCCESS [ 34.029 s][INFO] Apache hadoop HDFS Project ......................... SUCCESS [  1.075 s][INFO] hadoop-yarn ........................................ SUCCESS [  1.354 s][INFO] hadoop-yarn-api .................................... SUCCESS [07:20 min][INFO] hadoop-yarn-common ................................. SUCCESS [35:51 min][INFO] hadoop-yarn-server ................................. SUCCESS [  1.020 s][INFO] hadoop-yarn-server-common .......................... SUCCESS [01:42 min][INFO] hadoop-yarn-server-nodemanager ..................... SUCCESS [01:58 min][INFO] hadoop-yarn-server-web-proxy ....................... SUCCESS [ 25.288 s][INFO] hadoop-yarn-server-applicationhistoryservice ....... SUCCESS [01:05 min][INFO] hadoop-yarn-server-resourcemanager ................. SUCCESS [02:52 min][INFO] hadoop-yarn-server-tests ........................... SUCCESS [ 40.356 s][INFO] hadoop-yarn-client ................................. SUCCESS [ 54.780 s][INFO] hadoop-yarn-server-sharedcachemanager .............. SUCCESS [ 24.110 s][INFO] hadoop-yarn-applications ........................... SUCCESS [  1.017 s][INFO] hadoop-yarn-applications-distributedshell .......... SUCCESS [ 21.223 s][INFO] hadoop-yarn-applications-unmanaged-am-launcher ..... SUCCESS [ 17.608 s][INFO] hadoop-yarn-site ................................... SUCCESS [  1.145 s][INFO] hadoop-yarn-registry ............................... SUCCESS [ 42.659 s][INFO] hadoop-yarn-project ................................ SUCCESS [ 34.614 s][INFO] hadoop-mapreduce-client ............................ SUCCESS [  1.905 s][INFO] hadoop-mapreduce-client-core ....................... SUCCESS [33:18 min][INFO] hadoop-mapreduce-client-common ..................... SUCCESS [32:57 min][INFO] hadoop-mapreduce-client-shuffle .................... SUCCESS [ 28.868 s][INFO] hadoop-mapreduce-client-app ........................ SUCCESS [01:00 min][INFO] hadoop-mapreduce-client-hs ......................... SUCCESS [ 46.223 s][INFO] hadoop-mapreduce-client-jobclient .................. SUCCESS [ 29.643 s][INFO] hadoop-mapreduce-client-hs-plugins ................. SUCCESS [ 15.580 s][INFO] Apache hadoop MapReduce Examples ................... SUCCESS [ 40.229 s][INFO] hadoop-mapreduce ................................... SUCCESS [ 24.719 s][INFO] Apache hadoop MapReduce Streaming .................. SUCCESS [ 33.669 s][INFO] Apache hadoop Distributed Copy ..................... SUCCESS [ 59.792 s][INFO] Apache hadoop Archives ............................. SUCCESS [ 19.986 s][INFO] Apache hadoop Rumen ................................ SUCCESS [ 47.303 s][INFO] Apache hadoop Gridmix .............................. SUCCESS [ 30.258 s][INFO] Apache hadoop Data Join ............................ SUCCESS [ 22.306 s][INFO] Apache hadoop Ant Tasks ............................ SUCCESS [ 19.212 s][INFO] Apache hadoop Extras ............................... SUCCESS [ 27.362 s][INFO] Apache hadoop Pipes ................................ SUCCESS [  6.723 s][INFO] Apache hadoop OpenStack support .................... SUCCESS [ 34.857 s][INFO] Apache hadoop Amazon Web Services support .......... SUCCESS [ 37.631 s][INFO] Apache hadoop Azure support ........................ SUCCESS [ 30.848 s][INFO] Apache hadoop Client ............................... SUCCESS [01:02 min][INFO] Apache hadoop Mini-Cluster ......................... SUCCESS [  3.409 s][INFO] Apache hadoop Scheduler Load Simulator ............. SUCCESS [ 33.821 s][INFO] Apache hadoop Tools Dist ........................... SUCCESS [ 55.501 s][INFO] Apache hadoop Tools ................................ SUCCESS [  0.768 s][INFO] Apache hadoop Distribution ......................... SUCCESS [03:44 min][INFO] ------------------------------------------------------------------------[INFO] BUILD SUCCESS[INFO] ------------------------------------------------------------------------[INFO] Total time: 03:33 h[INFO] Finished at: 2016-08-01T14:22:17+08:00[INFO] Final Memory: 125M/3096M[INFO] ------------------------------------------------------------------------

本例的编译后果位于/usr/local/hadoop-2.7.2/hadoop-dist/target/目录，源码包和二进制包别离为hadoop-2.7.2-src.tar.gz和hadoop-2.7.2.tar.gz。至此hadoop编译完结。

六、Hadoop 集群搭建测试

本节采纳hadoop ”Fully Distributed Mode” 工作模式,在IP地址别离为10.20.42.22(slave1),10.20.42.22(slave2),10.20.42.199(master)的机器上部署3节点的hadoop集群。

设置SSH免明码登录

SSH免明码登录，假如应用root用户，在每台服务器都生成公钥，再合并到authorized_keys，具体操作如下：
(1)fadora21默认没有启动ssh无密登录，批改/etc/ssh/sshd_config正文掉以下2行。(每台机器都要设置)

RSAAuthentication yes

PubkeyAuthentication yes

(2)在集群中的每台机器上，关上shell终端输出命令，ssh-keygen -t rsa，生成key，不要输出明码，始终回车，/root就会生成.ssh文件夹,这个文件个别是暗藏的。(每台服务器都要设置)

(3)合并slave节点的公钥到authorized_keys文件。在Master服务器，进入/root/.ssh目录，应用如下命令:
cat id_rsa.pub>> authorized_keys
ssh root@10.20.42.22 cat ~/.ssh/id_rsa.pub>> authorized_keys
ssh root@10.20.42.10 cat ~/.ssh/id_rsa.pub>> authorized_keys

(4)把Master服务器的authorized_keys、known_hosts复制到Slave服务器的/root/.ssh目录

(5)终端输出ssh root@10.20.42.22和ssh root@10.20.42.10进行验证是否免密登陆配置胜利

搭建hadoop 3节点集群

搭建思路:筹备1台主服务器和2台从服务器，从主服务器能够ssh免密登录从服务器器。hadoop压缩包采纳上节编译后果:hadoop-2.7.2.tar.gz。 3台服务器的概要信息如下:

Master 10.20.42.199Slave1 10.20.42.22Slave2 10.20.42.10

搭建前提: 服务器须要装置JDK并设置好JAVA_HOM等环境变量。可参考上面的例子:

#编辑/etc/profile 文件并设置JAVA_HOME等环境变量  vi /etc/profileexport JAVA_HOME=/usr/lib/jvm/java-1.8.0-openjdk-1.8.0.25-6.b17.rc16.fc21.loongson.mips64elexport CLASSPATH=.:$JAVA_HOME/jre/lib/rt.jar:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jarexport PATH=$PATH:$JAVA_HOME/bin #使环境变量失效 并且验证jdk 是否失效source /etc/profile && java -version

开始搭建

解压hadoop-2.7.2.tar.gz 软件包,笔者的工作目录为/home/loongson/,没有非凡阐明上面的配置文件均来自master服务器。

(1)解压hadoop软件包: tar -xvf hadoop-2.7.2.tar.gz -C /home/loongson

(2)在/home/loongson/hadoop-2.7.2目录下手动创立tmp、hdfs、hdfs/data、hdfs/name文件夹。

(3)配置/home/hadoop/hadoop-2.7.2/etc/hadoop目录下的core-site.xml(ip设置成master的地址)

   <configuration>        <property>        <name>fs.defaultFS</name>        <value>hdfs://10.20.42.199:9000</value>        </property>        <property>        <name>hadoop.tmp.dir</name>        <value>file:/home/loongson/hadoop/tmp</value>        </property>        <property>        <name>io.file.buffer.size</name>        <value>131702</value>        </property>    </configuration>

(4)配置/home/loongson/hadoop-2.7.2/etc/hadoop目录下的hdfs-site.xml(ip设置成master的地址)

 <configuration>        <property>        <name>dfs.namenode.name.dir</name>        <value>file:/home/loongson/hadoop/dfs/name</value>        </property>        <property>        <name>dfs.datanode.data.dir</name>        <value>file:/home/loongson/hadoop/dfs/data</value>        </property>        <property>        <name>dfs.replication</name>        <value>2</value>        </property>        <property>        <name>dfs.namenode.secondary.http-address</name>        <value>10.20.42.199:9001</value>        </property>        <property>        <name>dfs.webhdfs.enabled</name>        <value>true</value>        </property>    </configuration>

(5)配置/home/loongson/hadoop-2.7.2/etc/hadoop目录下的mapred-site.xml.template(ip设置成master的地址)

  <configuration>        <property>        <name>mapreduce.framework.name</name>        <value>yarn</value>        </property>        <property>        <name>mapreduce.jobhistory.address</name>        <value>10.20.42.199:10020</value>        </property>        <property>        <name>mapreduce.jobhistory.webapp.address</name>        <value>10.20.42.199:19888</value>        </property>    </configuration>

(6)配置/home/loongson/hadoop-2.7.2/etc/hadoop目录下的yarn-site.xml(ip设置成master的地址)

   <configuration>        <property>        <name>yarn.nodemanager.aux-services</name>        <value>mapreduce_shuffle</value>        </property>        <property>        <name>yarn.nodemanager.auxservices.mapreduce.shuffle.class</name>        <value>org.apache.hadoop.mapred.ShuffleHandler</value>        </property>        <property>        <name>yarn.resourcemanager.address</name>        <value>10.20.42.199:8032</value>        </property>        <property>        <name>yarn.resourcemanager.scheduler.address</name>        <value>10.20.42.199:8030</value>        </property>        <property>        <name>yarn.resourcemanager.resource-tracker.address</name>        <value>10.20.42.199:8031</value>        </property>        <property>        <name>yarn.resourcemanager.admin.address</name>        <value>10.20.42.199:8033</value>        </property>        <property>        <name>yarn.resourcemanager.webapp.address</name>        <value>10.20.42.199:8088</value>        </property>        <property>        <name>yarn.nodemanager.resource.memory-mb</name>        <value>768</value>        </property>    </configuration>

(7)批改位于/home/loongson/hadoop-2.7.2/etc/hadoop目录hadoop-env.sh,yarn-env.sh中的JAVA_HOME等环境变量。

export JAVA_HOME=/usr/lib/jvm/java-1.8.0-openjdk-1.8.0.25-6.b17.rc16.fc21.loongson.mips64el

(8)配置/home/loongson/hadoop-2.7.2/etc/hadoop目录下的slaves文件，减少2个从slave节点，

10.20.42.1010.20.42.22

(9)将上述配置好的Hadoop-2.7.2(位于master机器上)应用scp复制到各个slave节点对应地位上

scp -r /home/loongson/hadoop-2.7.2 10.20.42.10:/home/loongsonscp -r /home/loongson/hadoop-2.7.2 10.20.42.22:/home/loongson

(10)在Master服务器启动hadoop，从节点会主动启动，进入/home/loongson/hadoop-2.7.2目录

(1)敞开机器防火墙:service iptables stop (主从都设置)(2)初始化node节点:bin/hdfs namenode -format(3)启动全副node: sbin/start-all.sh

This script is Deprecated. Instead use start-dfs.sh and start-yarn.sh16/09/02 08:49:56 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicableStarting namenodes on [hadoop-master-001]hadoop-master-001: starting namenode, logging to /home/loongson/hadoop-2.7.2/logs/hadoop-root-namenode-        localhost.localdomain.out        10.20.42.22: starting datanode, logging to /home/loongson/hadoop-2.7.2/logs/hadoop-root-datanode-localhost.localdomain.out        10.20.42.22: /home/loongson/hadoop-2.7.2/bin/hdfs: /usr/lib/jvm/java-1.8.0-openjdk-1.8.0.25-6.b17.rc16.fc21.loongson.mips64el        10.20.42.22: /home/loongson/hadoop-2.7.2/bin/hdfs: line 304: /usr/lib/jvm/java-1.8.0-        openjdk-1.8.0.25-6.b17.rc16.fc21.loongson.mips64el/bin/java: 胜利        10.20.42.10: starting datanode, logging to /home/loongson/hadoop-2.7.2/logs/hadoop-root-datanode-localhost.localdomain.out        Starting secondary namenodes [hadoop-master-001]        hadoop-master-001: secondarynamenode running as process 18418. Stop it first.        16/09/02 08:50:33 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java         classes where applicable        starting yarn daemons        resourcemanager running as process 16937. Stop it first.        10.20.42.10: starting nodemanager, logging to /home/loongson/hadoop-2.7.2/logs/yarn-root-nodemanager-localhost.localdomain.out        10.20.42.22: starting nodemanager, logging to /home/loongson/hadoop-2.7.2/logs/yarn-root-nodemanager-localhost.localdomain.out        10.20.42.22: /home/loongson/hadoop-2.7.2/bin/yarn: /usr/lib/jvm/java-1.8.0-openjdk-1.8.0.25-6.b17.rc16.fc21.loongson.mips64el        10.20.42.22: /home/loongson/hadoop-2.7.2/bin/yarn: line 333: /usr/lib/jvm/java-1.8.0-        openjdk-1.8.0.25-6.b17.rc16.fc21.loongson.mips64el/bin/java: 胜利

(4)暂停全副节点的命令: sbin/stop-all.sh

(5)输出jps命令: 如果从节点和主节点显示相似如下,阐明节点搭建胜利

  master:    32497 OServerMain    3506 SecondaryNameNode    3364 DataNode    5654 Jps    2582 OGremlinConsole    16937 ResourceManager    3263 NameNode    slaves:    21580 Jps    20622 DataNode

(11)从浏览器拜访: http://10.20.42.199:8088/或http://10.20.42.199:50070/ 查看hadop运行状况。上面给出从浏览器关上，看到的hadoop的运行状况截图:
Hadoop运行预览和概要信息:

Hadoop运行状况:

七、下载成品

如果感觉下面的移植过程太简单，笔者曾经筹备好了移植完的二进制，能够间接下载运行：
http://www.loongnix.org/index.php/Apache_hadoop-2.7.2

八、总结

hadoop-2.7.2 在loongnix1.0 零碎上正确实现源码编译和搭建小集群测试，能够作为开发者移植hadoop和进行集群测试的示范过程。

文章来源于龙芯开源社区