CentOS7 安装kylin2.6.0集群

1. 环境准备

zookeeper3.4.12

mysql5.7

hive2.3.4

hadoop2.7.3

JDK1.8

hbase1.3.3

2. 集群规划

ip地址	机器名	角色
192.168.1.101	palo101	hadoop namenode, hadoop datanode, yarn nodeManager, zookeeper, hive, hbase master,hbase region server，
192.168.1.102	palo102	hadoop secondary namenode, hadoop datanode, yarn nodeManager,  yarn resource manager, zookeeper, hive, hbase master,hbase region server
192.168.1.103	palo103	hadoop datanode, yarn nodeManager, zookeeper, hive,hbase region server,mysql

3. 下载kylin2.6

wget http://mirrors.tuna.tsinghua.edu.cn/apache/kylin/apache-kylin-2.6.0/apache-kylin-2.6.0-bin-hbase1x.tar.gz   #下载kylin2.6.0二进制文件
tar -xzvf apache-kylin-2.6.-bin-hbase1x.tar.gz          #解压kylin2..0二进制压缩包
mv apache-kylin-2.6.-bin apache-kylin-2.6.             #将kylin解压过的文件重命名（去掉最后的bin)
mkdir /usr/local/kylin/                                  #创建目标存放路径
mv apache-kylin-2.6.    /usr/local/kylin/               #将kylin2..0文件夹移动到/usr/local/kylin目录下

4. 添加系统环境变量

vim /etc/profile

在文件末尾添加

#kylin
export KYLIN_HOME=/usr/local/kylin/apache-kylin-2.6.
export KYLIN_CONF_HOME=$KYLIN_HOME/conf
export PATH=:$PATH:$KYLIN_HOME/bin:$CATALINE_HOME/bin
export tomcat_root=$KYLIN_HOME/tomcat   #变量名小写
export hive_dependency=$HIVE_HOME/conf:$HIVE_HOME/lib/*:$HCAT_HOME/share/hcatalog/hive-hcatalog-core-2.3.4.jar   #变量名小写

:wq保存退出，并输入source /etc/profile使环境变量生效

5. 配置kylin

5.1 配置$KYLIN_HOME/bin/kylin.sh

vim $KYLIN_HOME/bin/kylin.sh

在文件开头添加

export HBASE_CLASSPATH_PREFIX=${tomcat_root}/bin/bootstrap.jar:${tomcat_root}/bin/tomcat-juli.jar:${tomcat_root}/lib/*:$hive_dependency:$HBASE_CLASSPATH_PREFIX

这么做的目的是为了加入$hive_dependency环境，解决后续的两个问题，都是没有hive依赖的原因:
a) kylinweb界面load hive表会失败
b) cube build的第二步会报org/apache/Hadoop/hive/conf/hiveConf的错误。

5.2 hadoop压缩配置

关于snappy压缩支持问题，如果支持需要事先重新编译Hadoop源码，使得native库支持snappy.使用snappy能够实现一个适合的压缩比，使得这个运算的中间结果和最终结果都能占用较小的存储空间
本例的hadoop不支持snappy压缩，这个会导致后续cube build报错。

vim  $KYLIN_HOME/conf/Kylin_job_conf.xml

修改配置文件，将配置项mapreduce.map.output.compress，mapreduce.output.fileoutputformat.compress修改为false

    <property>
        <name>mapreduce.map.output.compress</name>
        <value>false</value>
        <description>Compress map outputs</description>
    </property>
    <property>
        <name>mapreduce.output.fileoutputformat.compress</name>
        <value>false</value>
        <description>Compress the output of a MapReduce job</description>
    </property>

还有一个关于压缩的地方需要修改

vim   $KYLIN_HOME/conf/kylin.properties

将kylin.hbase.default.compression.codec设置为none或者注释掉

#kylin.storage.hbase.compression-codec=none

5.3 主配置$KYLIN_HOME/conf/kylin.properties

vim   $KYLIN_HOME/conf/kylin.properties

修改为：

## The metadata store in hbase
##hbase上存储kylin元数据
kylin.metadata.url=kylin_metadata@hbase

## metadata cache sync retry times
##元数据同步重试次数
kylin.metadata.sync-retries=

## Working folder in HDFS, better be qualified absolute path, make sure user has the right permission to this directory
##hdfs上kylin工作目录
kylin.env.hdfs-working-dir=/kylin

## kylin zk base path
kylin.env.zookeeper-base-path=/kylin

## DEV|QA|PROD. DEV will turn on some dev features, QA and PROD has no difference in terms of functions.
#kylin.env=DEV

## Kylin server mode, valid value [all, query, job]
##kylin主节点模式，从节点的模式为query，只有这一点不一样
kylin.server.mode=all

## List of web servers in use, this enables one web server instance to sync up with other servers.
##集群的信息同步
kylin.server.cluster-servers=192.168.1.131:,192.168.1.193:,192.168.1.194:

## Display timezone on UI,format like[GMT+N or GMT-N]
##改为中国时间
kylin.web.timezone=GMT+    

## Timeout value for the queries submitted through the Web UI, in milliseconds
##web查询超时时间（毫秒）
kylin.web.query-timeout=

## Max count of concurrent jobs running
##可并发执行的job数量
kylin.job.max-concurrent-jobs=

#### ENGINE ###
## Time interval to check hadoop job status
##检查hdfs job的时间间隔(秒)
kylin.engine.mr.yarn-check-interval-seconds=

## Hive database name for putting the intermediate flat tables
##build cube 产生的Hive中间表存放的数据库
kylin.source.hive.database-for-flat-table=kylin_flat_db

## The percentage of the sampling, default %
kylin.job.cubing.inmem.sampling.percent=

## Max job retry on error, default : no retry
kylin.job.retry=

## Compression codec for htable, valid value [none, snappy, lzo, gzip, lz4]
##不采用压缩
kylin.storage.hbase.compression-codec=none  

## The cut size for hbase region, in GB.
kylin.storage.hbase.region-cut-gb=

## The hfile size of GB, smaller hfile leading to the converting hfile MR has more reducers and be faster.
## Set  to disable this optimization.
kylin.storage.hbase.hfile-size-gb=

## The storage for final cube file in hbase
kylin.storage.url=hbase

## The prefix of hbase table
kylin.storage.hbase.table-name-prefix=KYLIN_

## The namespace for hbase storage
kylin.storage.hbase.namespace=default

###定义kylin用于MR jobs的job.jar包和hbase的协处理jar包，用于提升性能(添加项)
kylin.job.jar=/usr/local/kylin/apache-kylin-2.6./lib/kylin-job-2.6..jar
kylin.coprocessor.local.jar=/usr/local/kylin/apache-kylin-2.6./lib/kylin-coprocessor-2.6..jar

5.4 将配置好的kylin复制到其他两台机器上去

scp -r /usr/local/kylin/  192.168.1.102:/usr/local
scp -r /usr/local/kylin/  192.168.1.103:/usr/local

5.5 将192.168.1.102，192.168.1.103上的kylin.server.mode改为query

vim   $KYLIN_HOME/conf/kylin.properties

修改项为

kylin.server.mode=query      ###kylin主节点模式，从节点的模式为query，只有这一点不一样

6. 启动kylin

6.1 前提条件：依赖服务先启动

a) 启动zookeeper，所有节点运行

$ZOO_KEEPER_HOME/bin/zkServer.sh start

b) 启动hadoop，主节点运行

$HADOOP_HOME/bin/start-all.sh

c) 启动JobHistoryserver服务，master主节点启动.

$HADOOP_HOME/sbin/mr-jobhistory-daemon.sh start historyserver

d) 启动hivemetastore服务

nohup $HIVE_HOME/bin/hive --service metastore /dev/null >& &

e) 启动hbase集群，主节点启动

$HBASE_HOME/bin/start-hbase.sh

启动后的进程为：

192.168.1.101

[root@palo101 apache-kylin-2.6.]# jps
 NameNode          #hdfs NameNode
 NodeManager       #yarn NodeManager
 Kafka
 QuorumPeerMain    #zookeeper
 Jps
 DataNode          #hadoop datanode
 HRegionServer     #hbase region server
 HMaster            #hbase master

192.168.1.102

[root@palo102 ~]# jps
 QuorumPeerMain    #zookeeper
 NodeManager       #yarn NodeManager
 ResourceManager   #yarn ResourceManager
 Jps
 HRegionServer      #hbase region server
 Kafka
 SecondaryNameNode #hdfs SecondaryNameNode
 DataNode          #hadoop datanode

192.168.1.103

[root@palo103 ~]# jps
 RunJar             #hive metastore
 NodeManager       #yarn NodeManager
 HRegionServer     #hbase region server
 QuorumPeerMain    #zookeeper
 ManagerBootStrap
 Kafka
 RunJar            #hive thrift server
 DataNode          #hadoop datanode
 Jps

6.2 检查配置是否正确

 $KYLIN_HOME/bin/check-env.sh

[root@palo101 bin]#  $KYLIN_HOME/bin/check-env.sh
Retrieving hadoop conf dir...
KYLIN_HOME is set to /usr/local/kylin/apache-kylin-2.6.
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/usr/local/hadoop-2.7./share/hadoop/common/lib/slf4j-log4j12-1.7..jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/local/apache-hive-2.3.-bin/lib/log4j-slf4j-impl-2.6..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]
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/usr/local/hadoop-2.7./share/hadoop/common/lib/slf4j-log4j12-1.7..jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/local/apache-hive-2.3.-bin/lib/log4j-slf4j-impl-2.6..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]
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/usr/local/hadoop-2.7./share/hadoop/common/lib/slf4j-log4j12-1.7..jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/local/apache-hive-2.3.-bin/lib/log4j-slf4j-impl-2.6..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]

hive依赖检查find-hive-dependency.sh
hbase依赖检查find-hbase-dependency.sh
所有的依赖检查可吃用check-env.sh

6.3 所有节点运行下面命令来启动kylin

 $KYLIN_HOME/bin/kylin.sh start

启动时如果出现下面的错误

Failed to find metadata store by url: kylin_metadata@hbase

解决办法 为：

1）将$HBASE_HOME/conf/hbase-site.html的属性hbase.rootdir改成与$HADOOP_HOME/etc/hadoop/core-site.xml中的属性fs.defaultFS一致

2）进入zk的bin的zkCli，将/hbase删除，然后重启hbase可以解决

6.4 登录kylin

http：//192.168.1.101:7070/kylin， 其他几台也可以登录，只要切换相应的ip即可

默认登录名密码为:admin/KYLIN

登录后的主页面为:

7 FAQ

7.1 如果遇到类似下面的错误

WARNING: Failed to process JAR
[jar:file:/home/hadoop-2.7.3/contrib/capacity-scheduler/.jar!/] for

这个问题只是一些小bug问题把这个脚本的内容改动一下就好了${HADOOP_HOME}/etc/hadoop/hadoop-env.sh，把下面的这一段循环语句给注释掉

 vim ${HADOOP_HOME}/etc/hadoop/hadoop-env.sh

#for f in $HADOOP_HOME/contrib/capacity-scheduler/*.jar; do
#  if [ "$HADOOP_CLASSPATH" ]; then
#    export HADOOP_CLASSPATH=$HADOOP_CLASSPATH:$f
#  else
#    export HADOOP_CLASSPATH=$f
#  fi
#done

 7.2 如果遇到Caused by: java.lang.ClassCastException: com.fasterxml.jackson.datatype.joda.JodaModule cannot be cast to com.fasterxml.jackson.databind.Module的错误

产生这个问题的原因是hive使用的jackson-datatype-joda-2.4.6.jar，而kylin使用的是jackson-databind-2.9.5.jar，jar包版本不一致造成的。

hive：

kylin:

解决办法为：

mv $HIVE_HOME/lib/jackson-datatype-joda-2.4..jar $HIVE_HOME/lib/jackson-datatype-joda-2.4..jarback

即不使用hive的这个jar包，详情请参见https://issues.apache.org/jira/browse/KYLIN-3129

7.3 如果遇到Failed to load keystore type JKS with path conf/.keystore due to (No such file or directory)

解决办法为:

打开apache-kylin-2.6.0/tomcat/conf/server.xml文件，把其中的https的配置删除掉（或者注释掉)

        <!--
        <Connector port="7443" protocol="org.apache.coyote.http11.Http11Protocol"
                   maxThreads="150" SSLEnabled="true" scheme="https" secure="true"
                   keystoreFile="conf/.keystore" keystorePass="changeit"
                   clientAuth="false" sslProtocol="TLS" />
         -->

8. 简单使用入门

8.1 执行官方发布的样例数据

 $KYLIN_HOME/bin/sample.sh

如果出现Restart Kylin Server or click Web UI => System Tab => Reload Metadata to take effect，就说明示例cube创建成功了，如图：

8.2 重启kylin或者重新加载元数据让数据生效

本例中选择重新加载元数据，操作如图所示

8.3 进入hive，查看kylin cube表结构

$HIVE_HOME/bin/hive        #进入hive shell客户端
hive>show databases;       #查询hive中数据库列表
hive>use kylin_flat_db;    #切换到kylin的hive数据库
hive>show tables;          #查询kylin hive数据库中的所有表

输入如下：

[druid@palo101 kafka_2.-2.1.]$ $HIVE_HOME/bin/hive
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/home/workspace/apache-hive-2.3.-bin/lib/log4j-slf4j-impl-2.6..jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/home/workspace/hadoop-2.7./share/hadoop/common/lib/slf4j-log4j12-1.7..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 file:/home/workspace/apache-hive-2.3.-bin/conf/hive-log4j2.properties Async: true
Hive-on-MR is deprecated in Hive  and may not be available in the future versions. Consider using a different execution engine (i.e. spark, tez) or using Hive .X releases.
hive> show databases;
OK
default
dw_sales
kylin_flat_db
ods_sales
Time taken: 1.609 seconds, Fetched:  row(s)
hive> use kylin_flat_db;
OK
Time taken: 0.036 seconds
hive> show tables;
OK
kylin_account
kylin_cal_dt
kylin_category_groupings
kylin_country
kylin_sales
Time taken: 0.321 seconds, Fetched:  row(s)
hive> 

再来看hbase

[druid@palo101 kafka_2.-2.1.]$ hbase shell
SLF4J: Class path contains multiple SLF4J bindings.
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; enter 'help<RETURN>' for list of supported commands.
Type "exit<RETURN>" to leave the HBase Shell
Version 1.3., rfd0d55b1e5ef54eb9bf60cce1f0a8e4c1da073ef, Sat Nov  :: CST 

hbase(main)::> list
TABLE
dev
kylin_metadata
test
 row(s) in 0.3180 seconds

=> ["dev", "kylin_metadata", "test"]

hbase中多了个叫kylin_metadata的表，说明使用官方示例数据的cube已经创建成功了！

8.4 构建cube

刷新http://192.168.1.101:7070/kylin,我们发现多了个项目learn_kylin

 选择kylin_sales_model,进行构建

可以在monitor里查看构建的进度

Build成功之后model里面会出现storage信息，之前是没有的，可以到hbase里面去找对应的表，同时cube状态变为ready,表示可查询。

8.5 kylin中进行查询

至此，kylin集群部署结束。