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1.4.3 配置HDFS-HA自动故障转移
1)具体配置 (1)在hdfs-site.xml中增加
<!-- 启用nn故障自动转移 -->
<property>
<name>dfs.ha.automatic-failover.enabled</name>
<value>true</value>
</property>
(2)在core-site.xml文件中增加
<!-- 指定zkfc要连接的zkServer地址 -->
<property>
<name>ha.zookeeper.quorum</name>
<value>hadoop102:2181,hadoop103:2181,hadoop104:2181</value>
</property>
(3)修改后分发配置文件
[summer@hadoop102 etc]$ pwd
/opt/ha/hadoop-3.1.3/etc
[summer@hadoop102 etc]$ xsync hadoop/
2)启动 (1)关闭所有HDFS服务:
[summer@hadoop102 ~]$ stop-dfs.sh
(2)启动Zookeeper集群:
[summer@hadoop102 ~]$ zkServer.sh start
[summer@hadoop103 ~]$ zkServer.sh start
[summer@hadoop104 ~]$ zkServer.sh start
(3)启动Zookeeper以后,然后再初始化HA在Zookeeper中状态: [summer@hadoop102 ~] start-dfs.sh (5)可以去zkCli.sh客户端查看Namenode选举锁节点内容: [zk: localhost:2181(CONNECTED) 7] get -s /hadoop-ha/mycluster/ActiveStandbyElectorLock
myclusternn2 hadoop103 �>(�>
cZxid = 0x10000000b ctime = Tue Jul 14 17:00:13 CST 2020 mZxid = 0x10000000b mtime = Tue Jul 14 17:00:13 CST 2020 pZxid = 0x10000000b cversion = 0 dataVersion = 0 aclVersion = 0 ephemeralOwner = 0x40000da2eb70000 dataLength = 33 numChildren = 0 3)验证 (1)将Active NameNode进程kill,查看网页端三台Namenode的状态变化 [summer@hadoop102 ~]$ kill -9 namenode的进程id
1.4.4 常见问题1--解决NN连接不上JN的问题
自动故障转移配置好以后,然后使用start-dfs.sh群起脚本启动hdfs集群,有可能会遇到NameNode起来一会后,进程自动关闭的问题。查看NameNode日志,报错信息如下:
2020-08-17 10:11:40,658 INFO org.apache.hadoop.ipc.Client: Retrying connect to server: hadoop104/192.168.6.104:8485. Already tried 0 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS) 2020-08-17 10:11:40,659 INFO org.apache.hadoop.ipc.Client: Retrying connect to server: hadoop102/192.168.6.102:8485. Already tried 0 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS) 2020-08-17 10:11:40,659 INFO org.apache.hadoop.ipc.Client: Retrying connect to server: hadoop103/192.168.6.103:8485. Already tried 0 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)
… …
2020-08-17 10:11:49,669 INFO org.apache.hadoop.ipc.Client: Retrying connect to server: hadoop102/192.168.6.102:8485. Already tried 9 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS) 2020-08-17 10:11:49,673 INFO org.apache.hadoop.ipc.Client: Retrying connect to server: hadoop104/192.168.6.104:8485. Already tried 9 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS) 2020-08-17 10:11:49,676 INFO org.apache.hadoop.ipc.Client: Retrying connect to server: hadoop103/192.168.6.103:8485. Already tried 9 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS) 2020-08-17 10:11:49,678 WARN org.apache.hadoop.hdfs.server.namenode.FSEditLog: Unable to determine input streams from QJM to [192.168.6.102:8485, 192.168.6.103:8485, 192.168.6.104:8485]. Skipping. org.apache.hadoop.hdfs.qjournal.client.QuorumException: Got too many exceptions to achieve quorum size 2/3. 3 exceptions thrown: 192.168.6.103:8485: Call From hadoop102/192.168.6.102 to hadoop103:8485 failed on connection exception: java.net.ConnectException: 拒绝连接; For more details see: wiki.apache.org/hadoop/Conn… 192.168.6.102:8485: Call From hadoop102/192.168.6.102 to hadoop102:8485 failed on connection exception: java.net.ConnectException: 拒绝连接; For more details see: wiki.apache.org/hadoop/Conn… 192.168.6.104:8485: Call From hadoop102/192.168.6.102 to hadoop104:8485 failed on connection exception: java.net.ConnectException: 拒绝连接; For more details see: wiki.apache.org/hadoop/Conn…
查看报错日志,可分析出报错原因是因为NameNode连接不上JournalNode,而利用jps命令查看到三台JN都已经正常启动,为什么NN还是无法正常连接到JN呢?这是因为start-dfs.sh群起脚本默认的启动顺序是先启动NN,再启动DN,然后再启动JN,并且默认的rpc连接参数是重试次数为10,每次重试的间隔是1s,也就是说启动完NN以后的10s中内,JN还启动不起来,NN就会报错了。 core-default.xml里面有两个参数如下:
<!-- NN连接JN重试次数,默认是10次 -->
<property>
<name>ipc.client.connect.max.retries</name>
<value>10</value>
</property>
<!-- 重试时间间隔,默认1s -->
<property>
<name>ipc.client.connect.retry.interval</name>
<value>1000</value>
</property>
解决方案:遇到上述问题后,可以稍等片刻,等JN成功启动后,手动启动下三台NN:
[summer@hadoop102 ~]$ hdfs --daemon start namenode
[summer@hadoop103 ~]$ hdfs --daemon start namenode
[summer@hadoop104 ~]$ hdfs --daemon start namenode
也可以在core-site.xml里面适当调大上面的两个参数:
<!-- NN连接JN重试次数,默认是10次 -->
<property>
<name>ipc.client.connect.max.retries</name>
<value>20</value>
</property>
<!-- 重试时间间隔,默认1s -->
<property>
<name>ipc.client.connect.retry.interval</name>
<value>5000</value>
</property>
1.5 YARN-HA配置
1.5.1 YARN-HA工作机制
1)官方文档:
hadoop.apache.org/docs/r3.1.3…
2)YARN-HA工作机制
1.5.2 配置YARN-HA集群
1)环境准备 (1)修改IP (2)修改主机名及主机名和IP地址的映射 (3)关闭防火墙 (4)ssh免密登录 (5)安装JDK,配置环境变量等 (6)配置Zookeeper集群 2)规划集群
hadoop102 | hadoop103 | hadoop104 |
---|---|---|
ResourceManager | ResourceManager | ResourceManager |
NodeManager | NodeManager | NodeManager |
Zookeeper | Zookeeper | Zookeeper |
3)核心问题 (1)如果当前active rm挂了,其他rm怎么将其他standby rm上位 核心原理跟HDFS一样,利用了zk的临时节点。 (2)当前rm上有很多的计算程序在等待运行,其他的rm怎么将这些程序接手过来接着跑 rm会将当前的所有计算程序的状态存储在zk中,其他rm上位后会去读取,然后接着跑。 4)具体配置 (1)yarn-site.xml
<configuration>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
<!-- 启用resourcemanager ha -->
<property>
<name>yarn.resourcemanager.ha.enabled</name>
<value>true</value>
</property>
<!-- 声明两台resourcemanager的地址 -->
<property>
<name>yarn.resourcemanager.cluster-id</name>
<value>cluster-yarn1</value>
</property>
<!--指定resourcemanager的逻辑列表-->
<property>
<name>yarn.resourcemanager.ha.rm-ids</name>
<value>rm1,rm2,rm3</value>
</property>
<!-- ========== rm1的配置 ========== -->
<!-- 指定rm1的主机名 -->
<property>
<name>yarn.resourcemanager.hostname.rm1</name>
<value>hadoop102</value>
</property>
<!-- 指定rm1的web端地址 -->
<property>
<name>yarn.resourcemanager.webapp.address.rm1</name>
<value>hadoop102:8088</value>
</property>
<!-- 指定rm1的内部通信地址 -->
<property>
<name>yarn.resourcemanager.address.rm1</name>
<value>hadoop102:8032</value>
</property>
<!-- 指定AM向rm1申请资源的地址 -->
<property>
<name>yarn.resourcemanager.scheduler.address.rm1</name>
<value>hadoop102:8030</value>
</property>
<!-- 指定供NM连接的地址 -->
<property>
<name>yarn.resourcemanager.resource-tracker.address.rm1</name>
<value>hadoop102:8031</value>
</property>
<!-- ========== rm2的配置 ========== -->
<!-- 指定rm2的主机名 -->
<property>
<name>yarn.resourcemanager.hostname.rm2</name>
<value>hadoop103</value>
</property>
<property>
<name>yarn.resourcemanager.webapp.address.rm2</name>
<value>hadoop103:8088</value>
</property>
<property>
<name>yarn.resourcemanager.address.rm2</name>
<value>hadoop103:8032</value>
</property>
<property>
<name>yarn.resourcemanager.scheduler.address.rm2</name>
<value>hadoop103:8030</value>
</property>
<property>
<name>yarn.resourcemanager.resource-tracker.address.rm2</name>
<value>hadoop103:8031</value>
</property>
<!-- ========== rm3的配置 ========== -->
<!-- 指定rm1的主机名 -->
<property>
<name>yarn.resourcemanager.hostname.rm3</name>
<value>hadoop104</value>
</property>
<!-- 指定rm1的web端地址 -->
<property>
<name>yarn.resourcemanager.webapp.address.rm3</name>
<value>hadoop104:8088</value>
</property>
<!-- 指定rm1的内部通信地址 -->
<property>
<name>yarn.resourcemanager.address.rm3</name>
<value>hadoop104:8032</value>
</property>
<!-- 指定AM向rm1申请资源的地址 -->
<property>
<name>yarn.resourcemanager.scheduler.address.rm3</name>
<value>hadoop104:8030</value>
</property>
<!-- 指定供NM连接的地址 -->
<property>
<name>yarn.resourcemanager.resource-tracker.address.rm3</name>
<value>hadoop104:8031</value>
</property>
<!-- 指定zookeeper集群的地址 -->
<property>
<name>yarn.resourcemanager.zk-address</name>
<value>hadoop102:2181,hadoop103:2181,hadoop104:2181</value>
</property>
<!-- 启用自动恢复 -->
<property>
<name>yarn.resourcemanager.recovery.enabled</name>
<value>true</value>
</property>
<!-- 指定resourcemanager的状态信息存储在zookeeper集群 -->
<property>
<name>yarn.resourcemanager.store.class</name> <value>org.apache.hadoop.yarn.server.resourcemanager.recovery.ZKRMStateStore</value>
</property>
<!-- 环境变量的继承 -->
<property>
<name>yarn.nodemanager.env-whitelist</name>
<value>JAVA_HOME,HADOOP_COMMON_HOME,HADOOP_HDFS_HOME,HADOOP_CONF_DIR,CLASSPATH_PREPEND_DISTCACHE,HADOOP_YARN_HOME,HADOOP_MAPRED_HOME</value>
</property>
</configuration>
(2)同步更新其他节点的配置信息,分发配置文件
[summer@hadoop102 etc]$ xsync hadoop/
4)启动YARN (1)在有ResourceManager的节点启动。 [summer@hadoop102 ~] yarn rmadmin -getServiceState rm1 (3)可以去zkCli.sh客户端查看ResourceManager选举锁节点内容。 [summer@hadoop102 ~]$ zkCli.sh [zk: localhost:2181(CONNECTED) 16] get -s /yarn-leader-election/cluster-yarn1/ActiveStandbyElectorLock
cluster-yarn1rm1
cZxid = 0x100000022
ctime = Tue Jul 14 17:06:44 CST 2020
mZxid = 0x100000022
mtime = Tue Jul 14 17:06:44 CST 2020
pZxid = 0x100000022
cversion = 0
dataVersion = 0
aclVersion = 0
ephemeralOwner = 0x30000da33080005
dataLength = 20
numChildren = 0
(4)web端查看hadoop102:8088和hadoop103:8088的YARN的状态
将整个ha搭建完成后,集群将形成以下模样
hadoop102 | hadoop103 | hadoop104 |
---|---|---|
NameNode | NameNode | NameNode |
JournalNode | JournalNode | JournalNode |
DataNode | DataNode | DataNode |
Zookeeper | Zookeeper | Zookeeper |
ZKFC | ZKFC | ZKFC |
ResourceManager | ResourceManager | ResourceManager |
NodeManager | NodeManager | NodeManager |