开源大数据Hadoop+Hbase+Hive+mysql+Spark部署手册

第一章方案概述

本方案是一套以Hadoop分布式系统作为基础架构，搭配Hbase提供分布式存储服务，使用Spark 大数据分析引擎连接hive 数据仓库工具读取数据，将统计结果存储到 MySQL中的一个处理数据方式所搭建的平台，为提高可视化分析、语义引擎、大数据采集、大数据存取、大数据质量和大数据管理及处理能力的高可用方案。

第二章方案规划

2.1.硬件信息

主机名 CPU 内存 IP 磁盘 master 2 4 172.16.96.51 Sda:70G slave1 2 4 172.16.96.52 Sda:70G slave2 2 4 172.16.96.53 Sda:70G

2.2.软件信息

软件名称版本号备注 UOS Server V20 Hadoop 2.8.5 Hbase 2.2.4 Hive 2.3.4 Mysql 5.7 Spark 2.4.0

2.3.安装部署

2.3.1. 集群部署前的环境准备

2.3.1.1.为每台主机添加映射，/etc/hosts文件

172.16.96.51 master 172.16.96.52 slave1 172.16.96.53 slave2

2.3.1.2.免密码登录每台主机

master

ssh-keygen -t rsa -C "master"

slave1

ssh-keygen -t rsa -C "slave1"

slave2

ssh-keygen -t rsa -C "slave2" ssh-copy-id -i ~/.ssh/id_rsa.pub master ssh-copy-id -i ~/.ssh/id_rsa.pub slave1 ssh-copy-id -i ~/.ssh/id_rsa.pub slave2

2.3.1.3.时间同步

#master apt install chrony -y vim /etc/chrony/chrony.conf allow 172.16.96.0/24 #允许哪些客户端来同步主机的时间 local stratum 10 #增加，本机不同步任何主机时间，本机作为时间源 systemctl restart chronyd netstat -antulp|grep chronyd udp 0 0 127.0.0.1:323 0.0.0.0:* 6395/chronyd

输出以下信息： udp 0 0 172.16.96.51:40048 162.159.200.123:123 ESTABLISHED 6395/chronyd udp 0 0 0.0.0.0:123 0.0.0.0:* 6395/chronyd udp6 0 0 ::1:323 :::* 6395/chronyd

#slave1与slave2操作一致

apt install chrony -y vim /etc/chrony/chrony.conf

#pool 2.debian.pool.ntp.org #注释此行

server 172.16.96.51 iburst #将时间服务器指向我们自建的服务器，burst表示当此NTP服务器不可用时，向它发送一系列的并发包进行检测 systemctl restart chronyd chronyc sources –v

输出以下信息：

210 Number of sources = 8 MS Name/IP address Stratum Poll Reach LastRx Last sample

^- master 4 6 17 11 +32ms[ -666us] +/- 145ms ^- undefined.hostname.local> 2 6 17 10 +32ms[ -185us] +/- 127ms ^* 202.118.1.130 1 6 113 5 +3021us[ -29ms] +/- 11ms ^- time.cloudflare.com 3 6 17 11 +33ms[ +794us] +/- 139ms ^? chl.la 0 6 0 - +0ns[ +0ns] +/- 0ns ^? ntp6.flashdance.cx 0 6 0 - +0ns[ +0ns] +/- 0ns ^? tock.ntp.infomaniak.ch 0 6 0 - +0ns[ +0ns] +/- 0ns ^? time.cloudflare.com 0 6 0 - +0ns[ +0ns] +/- 0ns 2.3.1.4.三个节点安装openjdk8 apt install -y openjdk-8-jdk

#配置环境变量

cat ~./bashrc export JAVA_HOME=/usr/lib/jvm/java-1.8.0-openjdk-amd64 export PATH=$PATH:$JAVA_HOME/bin source ~/.bashrc java -version

输出以下信息：

openjdk version "1.8.0_212" OpenJDK Runtime Environment (build 1.8.0_212-8u212-b01-1~deb9u1-b01) OpenJDK 64-Bit Server VM (build 25.212-b01, mixed mode)

2.3.2 Hadoop安装部署

请到官网下载Hadoop安装包https://hadoop.apache.org/releases.html

2.3.1.5.解压Hadoop软件包

解压软件包hadoop-2.8.5.tar.gz到/opt目录

2.3.1.6.修改Hadoop配置文件

进入opt/hadoop-2.8.5/etc/hadoop文件夹下修改配置文件

#修改core-site.xml,这些xml文件，有些有，有些是带template或者default字段，将其copy成我说的文件即可

#修改core-site.xml

fs.defaultFS hdfs://master:9000 hadoop.tmp.dir /home/fay/tmp

#修改hdfs-site.xml

dfs.replication 2 dfs.permissions.enabled false dfs.datanode.max.xcievers 4096 Datanode 有一个同时处理文件的上限，至少要有4096 dfs.namenode.secondary.http-address master:9001 dfs.webhdfs.enabled true

#修改mapred-site.xml

mapreduce.framework.name yarn mapreduce.jobhistory.address master:10020 mapreduce.jobhistory.webapp.address master:19888

#修改yarn-site.xml

yarn.nodemanager.aux-services mapreduce_shuffle yarn.log-aggregation-enable true yarn.log-aggregation.retain-seconds 86400 yarn.resourcemanager.address master:8032 yarn.resourcemanager.scheduler.address master:8030 yarn.resourcemanager.resource-tracker.address master:8031 yarn.resourcemanager.admin.address master:8033 yarn.resourcemanager.webapp.address master:8088

#修改yarn-env.sh和hadoop-env.sh,将export JAVA_HOME=/usr/lib/jvm/java-1.8.0-openjdk-amd64放到带有java_home的位置 #修改slaves文件删掉localhost slave1 slave2

2.3.1.7.将Hadoop添加到环境变量

将hadoop添加到环境变量，修改~/.bashrc export JAVA_HOME=/usr/lib/jvm/java-1.8.0-openjdk-amd64 export HADOOP_HOME=/opt/hadoop-2.8.5 export HADOOP_COMMON_LIB_NATIVE_DIR=$HADOOP_HOME/lib/native export
HADOOP_OPTS="-Djava.library.path=$HADOOP_HOME/lib/native" export PATH=$PATH:$JAVA_HOME/bin:$HADOOP_HOME/bin:$HADOOP_HOME/sbin source ~/.bashrc #另外两台机器就简单了，直接copy过去就好 scp -r /opt root@slave1:/ scp -r /opt root@slave2:/ scp ~/.bashrc root@slave1:/root scp ~/.bashrc root@slave2:/root 2.3.1.8.初始化namenode 在master节点上初始化namenode hdfs namenode -format 输出以下内容： 21/02/27 22:03:55 INFO namenode.NameNode: STARTUP_MSG: /************************************************************ STARTUP_MSG: Starting NameNode STARTUP_MSG: user = root STARTUP_MSG: host = master/172.16.96.51 STARTUP_MSG: args = [-format] STARTUP_MSG: version = 2.8.5 STARTUP_MSG: classpath = /opt/hadoop-2.8.5/etc/hadoop:/opt/hadoop-2.8.5/share/hadoop/common/lib/jersey-server-1.9.jar:/opt/hadoop-2.8.5/share/hadoop/common/lib/commons-compres ---中间省略一部分信息 21/02/27 22:03:55 INFO namenode.NNStorageRetentionManager: Going to retain 1 images with txid >= 0 21/02/27 22:03:55 INFO util.ExitUtil: Exiting with status 0 21/02/27 22:03:55 INFO namenode.NameNode: SHUTDOWN_MSG: /************************************************************ SHUTDOWN_MSG: Shutting down NameNode at master/172.16.96.51 ************************************************************/

Starting namenodes on [master] master: starting namenode, lo

2.3.1.9.启动Hadoop

#master节点 start-dfs.sh

输出以下内容：

gging to /opt/hadoop-2.8.5/logs/hadoop-root-namenode-master.out slave2: starting datanode, logging to /opt/hadoop-2.8.5/logs/hadoop-root-datanode-slave2.out slave1: starting datanode, logging to /opt/hadoop-2.8.5/logs/hadoop-root-datanode-slave1.out Starting secondary namenodes [master] master: starting secondarynamenode, logging to /opt/hadoop-2.8.5/logs/hadoop-root-secondarynamenode-master.out

start-yarn.sh

输入以下内容：

starting yarn daemons starting resourcemanager, logging to /opt/hadoop-2.8.5/logs/yarn-root-resourcemanager-master.out slave1: starting nodemanager, logging to /opt/hadoop-2.8.5/logs/yarn-root-nodemanager-slave1.out slave2: starting nodemanager, logging to /opt/hadoop-2.8.5/logs/yarn-root-nodemanager-slave2.out

利用jps命令在master节点看到以下内容：

10755 NameNode 11300 Jps 10917 SecondaryNameNode 11049 ResourceManager

利用jps命令在两个slave节点看到以下内容：

9921 DataNode 10137 Jps 10013 NodeManager

2.3.1.10.测试Hadoop

到这里hadoop基本已经安装好了,测试一下hadoop在浏览器上输入172.16.96.51:8088

2.3.1.10.1.跑下hadoop 自带的mapreduce 用例

#matser hdfs dfs -mkdir /user hdfs dfs -mkdir /user/root hdfs dfs -put etc/hadoop input hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.8.5.jar grep input output 'dfs[a-z.]+'

输出以下内容

21/02/27 22:54:39 INFO client.RMProxy: Connecting to ResourceManager at master/172.16.96.51:8032 21/02/27 22:54:39 INFO input.FileInputFormat: Total input files to process : 29

---省略一部分内容

    Map input records=17
    Map output records=17
    Map output bytes=428
    Map output materialized bytes=468
    Input split bytes=127
    Combine input records=0
    Combine output records=0
    Reduce input groups=5
    Reduce shuffle bytes=468
    Reduce input records=17
    Reduce output records=17
    Spilled Records=34
    Shuffled Maps =1
    Failed Shuffles=0
    Merged Map outputs=1
    GC time elapsed (ms)=98
    CPU time spent (ms)=600
    Physical memory (bytes) snapshot=431075328
    Virtual memory (bytes) snapshot=3865038848
    Total committed heap usage (bytes)=285736960
Shuffle Errors
    BAD_ID=0
    CONNECTION=0
    IO_ERROR=0
    WRONG_LENGTH=0
    WRONG_MAP=0
    WRONG_REDUCE=0
File Input Format Counters 
    Bytes Read=650
File Output Format Counters 
    Bytes Written=326

没有报java错误，那就ok，在output目录查看下输出结果：

hdfs dfs -cat output/*‘ 6 dfs.audit.logger 4 dfs.class 3 dfs.logger 3 dfs.server.namenode. 2 dfs.audit.log.maxfilesize 2 dfs.period 2 dfs.audit.log.maxbackupindex 1 dfsmetrics.log 1 dfsadmin 1 dfs.webhdfs.enabled 1 dfs.servers 1 dfs.replication 1 dfs.permissions.enabled 1 dfs.log 1 dfs.file 1 dfs.datanode.max.xcievers 1 dfs.namenode.secondary.http

2.3.3 Hbase安装部署

官网下载软件https://hbase.apache.org

2.3.1.11.解压Hbase并配置环境变量

解压tar至/opt/目录 /opt/hbase-2.2.4/conf/下配置环境变量 #hbase-env.sh export JAVA_HOME=/usr/lib/jvm/java-1.8.0-openjdk-amd64 export HADOOP_HOME=/opt/hadop-2.8.5 export HBASE_MANAGES_ZK=true

2.3.1.12.修改相关配置文件内容

#修改hbase-site.xml文件

hbase.rootdir hdfs://master:9000/hbase hbase.cluster.distributed true hbase.zookeeper.quorum master,slave1,slave2 hbase.zookeeper.property.dataDir /var/log/zookeeper/data hbase.master master zookeeper.znode.parent /hbase hbase.unsafe.stream.capability.enforce false

#修改regionservers 删掉localhost master slave1 slave2 #创建backup-masters文件 slave1

2.3.1.13.#在～/.bashrc配置hbase环境变量

export HBASE_HOME=/opt/hbase-2.2.4 export PATH=$PATH:$JAVA_HOME/bin:$HBASE_HOME/bin:$HBASE_HOME/sbin source ~/.bashrc

2.3.1.14.将配置文件和整个目录给其它两个节点

scp -r hbase-2.2.4 root@slave1:/opt/ scp -r hbase-2.2.4 root@slave2:/opt/ scp -r /root/.bashrc root@slave1:/root/ scp -r /root/.bashrc root@slave2:/root/

2.3.1.15.启动Hbase

在hadoop起来的情况下，再启动hbase start-hbase.sh 输出以下内容： SLF4J: Class path contains multiple SLF4J bindings. SLF4J: Found binding in [jar:file:/opt/hadoop-2.8.5/share/hadoop/common/lib/slf4j-log4j12-1.7.10.jar!/org/slf4j/impl/StaticLoggerBinder.class] SLF4J: Found binding in [jar:file:/opt/hbase-2.2.4/lib/client-facing-thirdparty/slf4j-log4j12-1.7.25.jar!/org/slf4j/impl/StaticLoggerBinder.class] SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation. SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory] running master, logging to /opt/hbase-2.2.4/logs/hbase-root-master-master.out SLF4J: Class path contains multiple SLF4J bindings. SLF4J: Found binding in

----中间省略一部分内容

slave1: SLF4J: Found binding in [jar:file:/opt/hbase-2.2.4/lib/client-facing-thirdparty/slf4j-log4j12-1.7.25.jar!/org/slf4j/impl/StaticLoggerBinder.class] slave1: SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation. slave1: SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory] 2.3.1.16.查看各个节点状态利用jps命令查看下各节点状态 Jps #master，输出以下内容： 21232 Jps 10755 NameNode 10917 SecondaryNameNode 11049 ResourceManager 19673 HMaster 19785 HRegionServer 20717 QuorumPeerMain

如果HMaster没起来，可以执行cp $HBASE_HOME/lib/client-facing-thirdparty/htrace-core-3.1.0-incubating.jar $HBASE_HOME/lib/，关闭hbase再次启动查看jps

#slave节点查看 9921 DataNode 20694 HRegionServer 20790 HMaster #这个是slave1，因为前面配置了backup-masters,slave2没有这个 20588 HQuorumPeer 21036 Jps 10013 NodeManager

2.3.1.17.进入Hbase数据库

hbase shell SLF4J: Class path contains multiple SLF4J bindings. SLF4J: Found binding in [jar:file:/opt/hadoop-2.8.5/share/hadoop/common/lib/slf4j-log4j12-1.7.10.jar!/org/slf4j/impl/StaticLoggerBinder.class] SLF4J: Found binding in [jar:file:/opt/hbase-2.2.4/lib/client-facing-thirdparty/slf4j-log4j12-1.7.25.jar!/org/slf4j/impl/StaticLoggerBinder.class] SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation. SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory] HBase Shell Use "help" to get list of supported commands. Use "exit" to quit this interactive shell. For Reference, please visit: http://hbase.apache.org/2.0/book.html#shell Version 2.2.4, r67779d1a325a4f78a468af3339e73bf075888bac, 2020年 03月 11日星期三 12:57:39 CST Took 0.0024 seconds hbase(main):001:0> list TABLE 0 row(s) Took 0.4137 seconds => [] hbase(main):002:0> create 'hello','world' Created table hello Took 1.3559 seconds => Hbase::Table - hello hbase(main):003:0> list TABLE hello 1 row(s) Took 0.0109 seconds => ["hello"]

2.3.1.18.进入Hbase首页

进入Hbase首页可以查看各种信息： http://172.16.96.51:16010/master-status

2.3.4 Hive 安装部署

官网下载安装包https://hive.apache.org

2.3.1.19.Hive安装mysql作为元数据库

#安装mysql apt install mysql-server-5.7 -y mysqld --initialize systemctl restart mysql.service grep 'password' /var/log/mysql/error.log 输出以下内容： 2021-02-27T18:04:51.766751Z 4 [Note] Access denied for user 'root'@'localhost' (using password: YES) 2021-02-27T18:04:55.296064Z 5 [Note] Access denied for user 'root'@'localhost' (using password: YES) 2021-02-27T18:05:09.316319Z 6 [Note] Access denied for user 'root'@'localhost' (using password: YES) 2021-02-27T18:05:21.250506Z 7 [Note] Access denied for user 'root'@'localhost' (using password: YES) 2021-02-27T18:05:39.867338Z 8 [Note] Access denied for user 'root'@'localhost' (using password: YES) 2021-02-27T18:06:43.216458Z 1 [Note] A temporary password is generated for root@localhost: SkWzvjuVa9*g #数据库初始化密码

2.3.1.20.Mysql相关配置

mysqladmin -uroot -p password Enter password: New password: Confirm new password: Warning: Since password will be sent to server in plain text, use ssl connection to ensure password safety.

2.3.1.21.创建Hive数据库

mysql -puosuos mysql: [Warning] Using a password on the command line interface can be insecure. Welcome to the MySQL monitor. Commands end with ; or \g. Your MySQL connection id is 10 Server version: 5.7.26-1 (Uos)

Oracle is a registered trademark of Oracle Corporation and/or its affiliates. Other names may be trademarks of their respective owners. Type 'help;' or '\h' for help. Type '\c' to clear the current input statement.

mysql> create database hive; Query OK, 1 row affected (0.01 sec) mysql> grant all privileges on hive.* to 'root'@'localhost' identified by 'uosuos'; Query OK, 0 rows affected, 1 warning (0.00 sec)

mysql> flush privileges; Query OK, 0 rows affected (0.00 sec)

2.3.1.22.安装Hive

安装hive进行相关配置，将hive包解压至/opt下 ln -s apache-hive-2.3.4-bin/ hive 2.3.1.23.配置环境变量 echo -e '##################HIVE环境变量配置#############\nexport HIVE_HOME=/opt/hive\nexport PATH=$HIVE_HOME/bin:$PATH' >> ~/.bashrc&& source ~/.bashrc&&tail -3 ~/.bashrc

##################HIVE环境变量配置############# export HIVE_HOME=/opt/hive export PATH=$HIVE_HOME/bin:$PATH

2.3.1.24.配置Hive

hive/conf/下配置hive,创建出hive-site.xml

javax.jdo.option.ConnectionUserName root

javax.jdo.option.ConnectionPassword uosuos

javax.jdo.option.ConnectionURLmysql jdbc:mysql://127.0.0.1:3306/hive?useSSL=false

javax.jdo.option.ConnectionDriverName com.mysql.cj.jdbc.Driver hive.support.concurrency true

#拷贝mysql connector拷贝到hive的lib包中,uos系统使用的是mysql-connector-java_8.0.21-1debian10_all.deb

dpkg -i mysql-connector-java_8.0.21-1debian10_all.deb cp /usr/share/java/mysql-connector-java-8.0.21.jar /opt/hive/lib/

2.3.1.25.元数据存储初始化

初始化hive的元数据库（使用mysql数据库） schematool -initSchema -dbType mysql 输出以下内容： SLF4J: Class path contains multiple SLF4J bindings. SLF4J: Found binding in [jar:file:/opt/apache-hive-2.3.4-bin/lib/log4j-slf4j-impl-2.6.2.jar!/org/slf4j/impl/StaticLoggerBinder.class] SLF4J: Found binding in [jar:file:/opt/hadoop-2.8.5/share/hadoop/common/lib/slf4j-log4j12-1.7.10.jar!/org/slf4j/impl/StaticLoggerBinder.class] SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation. SLF4J: Actual binding is of type [org.apache.logging.slf4j.Log4jLoggerFactory] Metastore connection URL: jdbc:mysql://127.0.0.1:3306/hive?useSSL=false Metastore Connection Driver : com.mysql.cj.jdbc.Driver Metastore connection User: root Starting metastore schema initialization to 2.3.0 Initialization script hive-schema-2.3.0.mysql.sql Initialization script completed schemaTool completed

2.3.1.26.进入hive命令行

hive 输出以下内容： SLF4J: Class path contains multiple SLF4J bindings. SLF4J: Found binding in [jar:file:/opt/apache-hive-2.3.4-bin/lib/log4j-slf4j-impl-2.6.2.jar!/org/slf4j/impl/StaticLoggerBinder.class] SLF4J: Found binding in [jar:file:/opt/hadoop-2.8.5/share/hadoop/common/lib/slf4j-log4j12-1.7.10.jar!/org/slf4j/impl/StaticLoggerBinder.class] SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation. SLF4J: Actual binding is of type [org.apache.logging.slf4j.Log4jLoggerFactory]

Logging initialized using configuration in jar:file:/opt/apache-hive-2.3.4-bin/lib/hive-common-2.3.4.jar!/hive-log4j2.properties Async: true Hive-on-MR is deprecated in Hive 2 and may not be available in the future versions. Consider using a different execution engine (i.e. spark, tez) or using Hive 1.X releases. hive>

2.3.5 Spark 安装部署

Spark下载地址http://spark.apache.org/releases/spark-release-2-4-0.html scala下载地址：https://downloads.lightbend.com/scala/2.13.0/scala-2.13.0.tgz

2.3.1.27.解压Scala

解压scala软件至/usr/local，配置环境变量 ~/.bashrc export SCALA_HOME=/usr/local/scala-2.13.0 export SCALA_CLASSPATH=$SCALA_HOME export PATH=$PATH:$SCALA_HOME/bin

2.3.1.28.解压Spark

解压spark包至/opt，配置环境变量 vim ~/.bashrc export SPARK_HOME=/opt/spark-2.3.3-bin-hadoop2.7 export SPARK_CLASSPATH=$SPARK_HOME export PATH=$PATH:$SPARK_HOME/bin source ~/.bashrc

2.3.1.29.修改Spark配置文件

修改spark配置文件（在安装目录下的conf文件夹中） cp spark-env.sh.template spark-env.sh 修改spark-env.sh SPARK_LOCAL_IP=master #本机ip或hostname SPARK_MASTER_IP=master #master节点ip或hostname export HADOOP_CONF_DIR=/opt/hadoop-2.8.5 #hadoop的配置路径 export YARN_CONF_DIR=/opt/hadoop-2.8.5 #yarn路径配置 修改slaves cp slaves.template slaves slave1 slave2 分发安装包和配置到其他节点 scp -r /usr/local/scala-2.13.0/ root@slave1:/usr/local scp -r /opt/spark-2.3.3-bin-hadoop2.7/ root@slave1:/opt/ scp -r /root/.bashrc root@slave1:/root/ scp -r /root/.bashrc root@slave2:/root/

2.3.1.30.修改各个节点

修改各节点中的在spark-env.sh中SPARK_LOCAL_IP选项 vim /opt/spark-2.3.3-bin-hadoop2.7/conf/spark-env.sh SPARK_LOCAL_IP=slave1 #本机ip或hostname SPARK_MASTER_IP=master #master节点ip或hostname export HADOOP_CONF_DIR=/opt/hadoop-2.8.5 #hadoop的配置路径 export YARN_CONF_DIR=/opt/hadoop-2.8.5 #yarn路径配置 #修改下Spark Web UI默认的8080端口，SPARK_HOME/sbin目录下start-master.sh，查找8080定位并修改为你想要的端口即可

2.3.1.31.启动服务

./start-all.sh 输出以下内容： starting org.apache.spark.deploy.master.Master, logging to /opt/spark-2.3.3-bin-hadoop2.7/logs/spark-root-org.apache.spark.deploy.master.Master-1-master.out slave1: starting org.apache.spark.deploy.worker.Worker, logging to /opt/spark-2.3.3-bin-hadoop2.7/logs/spark-root-org.apache.spark.deploy.worker.Worker-1-slave1.out slave2: starting org.apache.spark.deploy.worker.Worker, logging to /opt/spark-2.3.3-bin-hadoop2.7/logs/spark-root-org.apache.spark.deploy.worker.Worker-1-slave2.out

2.3.1.32.查看服务状态

#利用jps命令看下状态输出以下内容： 34176 Master #master的（master）,slave的（worker） 10755 NameNode 10917 SecondaryNameNode 34264 Jps 11049 ResourceManager 19673 HMaster 19785 HRegionServer 20717 QuorumPeerMain

Spark默认8080端口被其他服务占用，自定义修改后可以打开spark-web http://172.16.96.51:8081/

开源大数据部署手册

第一章 方案概述

第二章 方案规划