记录Presto数据查询引擎的配置过程 - 夜丶帝 - 博客园
配置准备：
1、centos6.4系统的虚拟机4个（master、secondary、node1、node2）
2、准备安装包
hadoop-cdh4.4.0、hive-cdh4.4.0、presto、discovery-server、hbase、JDK7.0+64bit、pythin2.4+、postgresql
注：Ssh 权限配置问题:
用户目录权限为 755 或者 700就是不能是77x
.ssh目录权限必须为755
rsa_id.pub 及authorized_keys权限必须为644
rsa_id权限必须为600
最后，在master中测试：ssh master date、ssh secondary date、ssh node1 date、ssh node2 date 不需要密码，则成功。
如果ssh secondary 、ssh node1、ssh node2 连接速度慢，需要更改/etc/ssh/ssh_config 为GSSAPIAuthentication no
修改root的ssh权限，/etc/ssh/sshd_config，将PermitRootLogin no 改为yes
重启sshd服务：/etc/init.d/sshd restrat
5、配置环境变量
[root@master~]# gedit .bash_profile
# .bash_profile
# Get the aliases and functions
if [ -f ~/.bashrc ]; then
. ~/.bashrc
fi
# User specific environment and startup programs
export JAVA_HOME=/usr/java/jdk1.7.0_45
export JRE_HOME=$JAVA_HOME/jre
export CLASS_PATH=./:$JAVA_HOME/lib:$JRE_HOME/lib:$JRE_HOME/lib/tools.jar:/usr/presto/server/lib:/usr/discovery-server/lib
export HADOOP_HOME=/usr/hadoop
export HIVE_HOME=/usr/hive
export HBASE_HOME=/usr/hbase
export HADOOP_MAPRED_HOME=${HADOOP_HOME}
export HADOOP_COMMON_HOME=${HADOOP_HOME}
export HADOOP_HDFS_HOME=${HADOOP_HOME}
export YARN_HOME=${HADOOP_HOME}
export HADOOP_YARN_HOME=${HADOOP_HOME}
export HADOOP_CONF_DIR=${HADOOP_HOME}/etc/hadoop
export HDFS_CONF_DIR=${HADOOP_HOME}/etc/hadoop
export YARN_CONF_DIR=${HADOOP_HOME}/etc/hadoop
export PATH=$PATH:$HOME/bin:$JAVA_HOME/bin:$HADOOP_HOME/sbin:$HIVE_HOME/bin:$HBASE_HOME/bin
master环境变量配置好后，secondary、node1和node2同样配置，可以使用scp命令同步到secondary、node1和node2中
6、配置hadoop
<?xml version="1.0" encoding="UTF-8"?> <?xml-stylesheet type="text/xsl" href="configuration.xsl"?> <configuration> <!--fs.default.name for MRV1 ,fs.defaultFS for MRV2(yarn) --> <property> <name>fs.defaultFS</name> <value>hdfs://master:8020</value> </property> <property> <name>fs.trash.interval</name> <value>10080</value> </property> <property> <name>fs.trash.checkpoint.interval</name> <value>10080</value> </property> </configuration>
c、hdfs-site.xml
<?xml version="1.0" encoding="UTF-8"?> <?xml-stylesheet type="text/xsl" href="configuration.xsl"?> <configuration> <property> <name>dfs.replication</name> <value>3</value> </property> <property> <name>hadoop.tmp.dir</name> <value>/opt/data/hadoop-${user.name}</value> </property> <property> <name>dfs.namenode.http-address</name> <value>master:50070</value> </property> <property> <name>dfs.namenode.secondary.http-address</name> <value>secondary:50090</value> </property> <property> <name>dfs.webhdfs.enabled</name> <value>true</value> </property> </configuration>
d、masters（没有则创建该文件）
<?xml version="1.0"?> <?xml-stylesheet type="text/xsl" href="configuration.xsl"?> <configuration> <property> <name>mapreduce.framework.name</name> <value>yarn</value> </property> <property> <name>mapreduce.jobhistory.address</name> <value>master:10020</value> </property> <property> <name>mapreduce.jobhistory.webapp.address</name> <value>master:19888</value> </property> </configuration>
g、yarn-site.xml
<?xml version="1.0"?> <configuration> <property> <name>yarn.resourcemanager.resource-tracker.address</name> <value>master:8031</value> </property> <property> <name>yarn.resourcemanager.address</name> <value>master:8032</value> </property> <property> <name>yarn.resourcemanager.scheduler.address</name> <value>master:8030</value> </property> <property> <name>yarn.resourcemanager.admin.address</name> <value>master:8033</value> </property> <property> <name>yarn.resourcemanager.webapp.address</name> <value>master:8088</value> </property> <property> <description>Classpath for typical applications.</description> <name>yarn.application.classpath</name> <value>$HADOOP_CONF_DIR,$HADOOP_COMMON_HOME/share/hadoop/common/*, $HADOOP_COMMON_HOME/share/hadoop/common/lib/*, $HADOOP_HDFS_HOME/share/hadoop/hdfs/*,$HADOOP_HDFS_HOME/share/hadoop/hdfs/lib/*, $YARN_HOME/share/hadoop/yarn/*,$YARN_HOME/share/hadoop/yarn/lib/*, $YARN_HOME/share/hadoop/mapreduce/*,$YARN_HOME/share/hadoop/mapreduce/lib/*</value> </property> <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.nodemanager.local-dirs</name> <value>/opt/data/yarn/local</value> </property> <property> <name>yarn.nodemanager.log-dirs</name> <value>/opt/data/yarn/logs</value> </property> <property> <description>Where to aggregate logs</description> <name>yarn.nodemanager.remote-app-log-dir</name> <value>/opt/data/yarn/logs</value> </property> <property> <name>yarn.app.mapreduce.am.staging-dir</name> <value>/user</value> </property> </configuration>
h、复制hadoop到secondary、node1和node2
i、hadoop第一次运行需要先格式化，命令如下：[root@tamaster hadoop]hadoop namenode -format
j、关闭hadoop安全模式，命令如下：hdfs dfsadmin -safemode leave
k、运行hadoop，命令： [root@tamaster:~]start-all.sh
master
secondary
node1
<?xml version="1.0"?> <?xml-stylesheet type="text/xsl" href="configuration.xsl"?> <configuration> <property> <name>hbase.rootdir</name> <value>hdfs://master/hbase-${user.name}</value> </property> <property> <name>hbase.cluster.distributed</name> <value>true</value> </property> <property> <name>hbase.tmp.dir</name> <value>/opt/data/hbase-${user.name}</value> </property> <property> <name>hbase.zookeeper.quorum</name> <value>master,secondary,node1,node2</value> </property> </configuration>
d、将hbase同步到secondary、node1、node2中
e、启动hbase，命令如下：
[root@master:~]# start-hbase.sh
8、安装hive
a、下载hive压缩包，并将其解压到/usr，即：/usr/hive
b、hive-site.xml
<?xml version="1.0"?> <?xml-stylesheet type="text/xsl" href="configuration.xsl"?> <configuration> <property> <name>javax.jdo.option.ConnectionURL</name> <value>jdbc:postgresql://master/testdb</value> <description>JDBC connect string for a JDBC metastore</description> </property> <property> <name>javax.jdo.option.ConnectionDriverName</name> <value>org.postgresql.Driver</value> <description>Driver class name for a JDBC metastore</description> </property> <property> <name>javax.jdo.option.ConnectionUserName</name> <value>hiveuser</value> <description>username to use against metastore database</description> </property> <property> <name>javax.jdo.option.ConnectionPassword</name> <value>redhat</value> <description>password to use against metastore database</description> </property> <property> <name>mapred.job.tracker</name> <value>master:8031</value> </property> <property> <name>mapreduce.framework.name</name> <value>yarn</value> </property> <property> <name>hive.aux.jars.path</name> <value>file:///usr/hive/lib/zookeeper-3.4.5-cdh4.4.0.jar, file:///usr/hive/lib/hive-hbase-handler-0.10.0-cdh4.4.0.jar, file:///usr/hive/lib/hbase-0.94.2-cdh4.4.0.jar, file:///usr/hive/lib/guava-11.0.2.jar</value> </property> <property> <name>hive.metastore.warehouse.dir</name> <value>/opt/data/warehouse-${user.name}</value> <description>location of default database for the warehouse</description> </property> <property> <name>hive.exec.scratchdir</name> <value>/opt/data/hive-${user.name}</value> <description>Scratch space for Hive jobs</description> </property> <property> <name>hive.querylog.location</name> <value>/opt/data/querylog-${user.name}</value> <description> Location of Hive run time structured log file </description> </property> <property> <name>hive.support.concurrency</name> <description>Enable Hive's Table Lock Manager Service</description> <value>true</value> </property> <property> <name>hive.zookeeper.quorum</name> <description>Zookeeper quorum used by Hive's Table Lock Manager</description> <value>node1</value> </property> <property> <name>hive.hwi.listen.host</name> <value>desktop1</value> <description>This is the host address the Hive Web Interface will listen on</description> </property> <property> <name>hive.hwi.listen.port</name> <value>9999</value> <description>This is the port the Hive Web Interface will listen on</description> </property> <property> <name>hive.hwi.war.file</name> <value>lib/hive-hwi-0.10.0-cdh4.2.0.war</value> <description>This is the WAR file with the jsp content for Hive Web Interface</description> </property> </configuration>
9、安装postgresql（用postgresql作为元数据库）
a、下载postgresql，并安装
b、使用pgadmin创建用户sa
c、使用pgadmin创建数据库testdb，并指定所属角色为sa
d、配置pg_hba.conf的访问地址，允许主机访问
e、配置postgresql.conf
standard_conforming_strings = off
f、复制postgres 的jdbc驱动 到 /usr/hive-cdh4.4.0/lib
1)node.properties
node.environment=production
node.id=F25B16CB-5D5B-50FD-A30D-B2221D71C882
node.data-dir=/var/presto/data
注意每台服务器node.id必须是唯一的
2)jvm.config
-server
-Xmx16G
-XX:+UseConcMarkSweepGC
-XX:+ExplicitGCInvokesConcurrent
-XX:+CMSClassUnloadingEnabled
-XX:+AggressiveOpts
-XX:+HeapDumpOnOutOfMemoryError
-XX:OnOutOfMemoryError=kill -9 %p
-XX:PermSize=150M
-XX:MaxPermSize=150M
-XX:ReservedCodeCacheSize=150M
-Xbootclasspath/p:/var/presto/installation/lib/floatingdecimal-0.1.jar
下载floatingdecimal-0.1.jar包放在/var/presto/installation/lib/目录下
3)config.properties
coordinator=true
datasources=jmx
http-server.http.port=8080
presto-metastore.db.type=h2
presto-metastore.db.filename=var/db/MetaStore
task.max-memory=1GB
discovery-server.enabled=true
discovery.uri=http://master:8411
以上为master的配置，secondary、node1和node2中需将coordinator=true值改为false,将discovery-server.enabled=true删除掉
4)log.properties
com.facebook.presto=DEBUG
5)在/usr/presto/etc中创建catalog文件夹，并创建以下配置文件
jmx.properties
connector.name=jmx
hive.propertes
connector.name=hive-cdh4
hive.metastore.uri=thrift://master:9083
1）node.properties
node.environment=production
node.id=D28C24CF-78A1-CD09-C693-7BDE66A51EFD
node.data-dir=/var/discovery/data
2）jvm.config
-server
-Xmx1G
-XX:+UseConcMarkSweepGC
-XX:+ExplicitGCInvokesConcurrent
-XX:+AggressiveOpts
-XX:+HeapDumpOnOutOfMemoryError
-XX:OnOutOfMemoryError=kill -9 %p
3）config.properties
http-server.http.port=8411
运行：
master机器上运行命令如下：
start-all.sh（启动每台机器上的hadoop）
start-hbase.sh（启动每台机器上的hbase）
转入usr/disdiscovery-server/bin中启动disdiscovery-server，命令如下
1、启动hadoop命令:
hadoop namenode -format
hadoop datanode -format
start-all.sh
hadoop dfsadmin -safemode leave
hdfs dfsadmin -safemode leave
2、hive启动命令：
./hive
./hive --service hiveserver -p 9083 //thrift模式
3、hbase 命令
./start-hbase.sh
4、discovery-server命令：
laucher start //启动
laucher run //运行
lancher stop //停止
5、presto命令
laucher start //启动
laucher run //运行
lancher stop //停止
6、presto 客户端启动
./presto --server localhost:8080 --catalog hive --schema default
4 nodes select Count(*) from mytable; 10s
4 nodes select Count(*),num from mytable group by num; 10s
4 nodes select num from mytable group by num having count(*)>1000; 10s
4 nodes select min(num) from mytable group by num; 9s
4 nodes select min(num) from mytable; 9s
4 nodes select max(num) from mytable; 9s
4 nodes select min(num) from mytable group by num; 9s
4 nodes select row_number() over(partition by name order by num) as row_index from mytable; 16s