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Hadoop高可用集群部署

作者：事業(yè)二部 2023-11-07 07:30:18

大數(shù)據(jù) Hadoop

在master節(jié)點中使用yarn rmadmin -getAllServiceState命令查看各個節(jié)點ResourceManager狀態(tài)，接下來停止active狀態(tài)節(jié)點的ResourceManage進程，ResourceManage active自動跳轉(zhuǎn)到其他節(jié)點，集群仍可用，隨后再啟動該節(jié)點ResourceManager進程，最后再次查看狀態(tài)，F(xiàn)ailed狀態(tài)恢復為standby。

背景

生產(chǎn)中Hadoop分布式集群中可能存在著單點故障問題，如果Namenode宕機或是軟硬件升級，集群將無法使用，所以進行搭建高可用的來消除單點故障。

Hadoop介紹

Hadoop集群一般為一個NameNode和ResourceManager，但在實際生產(chǎn)環(huán)境中，若恰好具有NameNode和ResourceManager的節(jié)點出現(xiàn)故障，那么整個Hadoop集群將會崩潰，這是因為在HDFS中NameNode是系統(tǒng)的核心節(jié)點，ResourceManager負責整個系統(tǒng)的資源管理和分配。

為了解決單點故障問題，在Hadoop2后中引入了高可用機制，支持NameNode和ResourceManager一個主節(jié)點和一個備用節(jié)點，而在Hadoop3中繼續(xù)對其進行了優(yōu)化和提升，它支持一個主節(jié)點和多個備用節(jié)點。所謂高可用（High Availability, HA）就是7*24 小時不中斷服務，消除單點故障。

Hadoop HA嚴格來說應該分成各個組件的HA機制：HDFS的HA和YARN的HA，可以通過配置多個NameNode和ResourceManager(Active/Standby)實現(xiàn)在集群中的熱備來解決上述問題。

環(huán)境準備：

圖片

節(jié)點相關進程如下：

圖片

操作系統(tǒng)：centos8
內(nèi)存：4G
Java 版本：jdk8

HDFS和YARN HA集群搭建

3.1 下載hadoop安裝包

官網(wǎng)https://hadoop.apache.org/下載hadoop 3.3.0安裝包解壓至/usr/local下3臺機器需修改的配置文件目錄為/usr/local/hadoop/etc/hadoop下。

3.2 hadoop.env

export JAVA_HOME=/usr/local/jdk #配置jdk路徑
#添加兩行
export HDFS_JOURNALNODE_USER=root
export HDFS_ZKFC_USER=root

3.3 core-site.xml

<?xml versinotallow="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<!-- Put site-specific property overrides in this file. -->
<configuration>
<!-- hdfs分布式文件系統(tǒng)名字/地址 -->
<property>
<name>fs.defaultFS</name>
<value>hdfs://ns</value>
</property>
<!--存放namenode、datanode數(shù)據(jù)的根路徑 -->
<property>
<name>hadoop.tmp.dir</name>
<value>/usr/local/hadoop/tmp</value>
</property>
<!-- 存放journalnode數(shù)據(jù)的地址 -->
<property>
<name>dfs.journalnode.edits.dir</name>
<value>/usr/local/hadoop/tmp/jn</value>
</property>
<!-- 列出運行 ZooKeeper 服務的主機端口對 -->
<property>
<name>ha.zookeeper.quorum</name>
<value>hadoop:2181,k8s-2:2181,k8s-3:2181</value>
</property>
</configuration>

3.4 hdfs-site.xml

<?xml versinotallow="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<!--
  Licensed under the Apache License, Version 2.0 (the "License");
  you may not use this file except in compliance with the License.
  You may obtain a copy of the License at
    http://www.apache.org/licenses/LICENSE-2.0
  Unless required by applicable law or agreed to in writing, software
  distributed under the License is distributed on an "AS IS" BASIS,
  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  See the License for the specific language governing permissions and
  limitations under the License. See accompanying LICENSE file.
-->
<configuration>
    <property>
        <name>dfs.replication</name>
        <value>3</value>
    </property>
    <property>
        <name>dfs.namenode.name.dir</name>
        <value>/usr/local/hadoop/dfs/name</value>
    </property>
    <property>
        <name>dfs.datanode.data.dir</name>
        <value>/usr/local/hadoop/dfs/data</value>
    </property>
    <property>
        <name>dfs.journalnode.edits.dir</name>
        <value>/usr/local/hadoop/dfs/journalnode</value>
        <description>The path where the JournalNode daemon will store its local state.</description>
    </property>
    <property>
        <name>dfs.nameservices</name>
        <value>ns</value>
        <description>The logical name for this new nameservice.</description>
    </property>
    <property>
        <name>dfs.ha.namenodes.ns</name>
        <value>nn1,nn2,nn3</value>
        <description>Unique identifiers for each NameNode in the nameservice.</description>
    </property>
    <property>
        <name>dfs.namenode.rpc-address.ns.nn1</name>
        <value>hadoop:8020</value>
        <description>The fully-qualified RPC address for nn1 to listen on.</description>
    </property>
    <property>
        <name>dfs.namenode.rpc-address.ns.nn2</name>
        <value>k8s-2:8020</value>
        <description>The fully-qualified RPC address for nn2 to listen on.</description>
    </property>
    <property>
        <name>dfs.namenode.rpc-address.ns.nn3</name>
        <value>k8s-3:8020</value>
        <description>The fully-qualified RPC address for nn3 to listen on.</description>
    </property>
    <property>
        <name>dfs.namenode.http-address.ns.nn1</name>
        <value>hadoop:9870</value>
        <description>The fully-qualified HTTP address for nn1 to listen on.</description>
    </property>
    <property>
        <name>dfs.namenode.http-address.ns.nn2</name>
        <value>k8s-2:9870</value>
        <description>The fully-qualified HTTP address for nn2 to listen on.</description>
    </property>
    <property>
        <name>dfs.namenode.http-address.ns.nn3</name>
        <value>k8s-3:9870</value>
        <description>The fully-qualified HTTP address for nn3 to listen on.</description>
    </property>
    <property>
        <name>dfs.namenode.shared.edits.dir</name>
        <value>qjournal://hadoop:8485;k8s-3:8485;k8s-2:8485/ns</value>
        <description>The URI which identifies the group of JNs where the NameNodes will write/read edits.</description>
    </property>
    <property>
        <name>dfs.client.failover.proxy.provider.ns</name>
<value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
        <description>The Java class that HDFS clients use to contact the Active NameNode.</description>
    </property>
    <property>
        <name>dfs.ha.fencing.methods</name>
        <value>
            sshfence
            shell(/bin/true)
        </value>
        <description>
            A list of scripts or Java classes which will be used to fence the Active NameNode during a failover.
            sshfence - SSH to the Active NameNode and kill the process
            shell - run an arbitrary shell command to fence the Active NameNode
        </description>
    </property>
    <property>
        <name>dfs.ha.fencing.ssh.private-key-files</name>
        <value>/root/.ssh/id_rsa</value>
        <description>Set SSH private key file.</description>
    </property>
    <property>
        <name>dfs.ha.automatic-failover.enabled</name>
        <value>true</value>
        <description>Automatic failover.</description>
    </property>
</configuration>

3.5 mapred-site.xml

<?xml versinotallow="1.0"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<!--
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. See accompanying LICENSE file.
-->
<!-- Put site-specific property overrides in this file. -->
<configuration>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
<property>
<name>yarn.app.mapreduce.am.env</name>
<value>HADOOP_MAPRED_HOME=/usr/local/hadoop</value>
</property>
<property>
<name>mapreduce.map.env</name>
<value>HADOOP_MAPRED_HOME=/usr/local/hadoop</value>
</property>
<property>
<name>mapreduce.reduce.env</name>
<value>HADOOP_MAPRED_HOME=/usr/local/hadoop</value>
</property>
</configuration>

3.6 yarn-site.xml

<?xml versinotallow="1.0"?>
<!--
  Licensed under the Apache License, Version 2.0 (the "License");
  you may not use this file except in compliance with the License.
  You may obtain a copy of the License at
    http://www.apache.org/licenses/LICENSE-2.0
  Unless required by applicable law or agreed to in writing, software
  distributed under the License is distributed on an "AS IS" BASIS,
  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  See the License for the specific language governing permissions and
  limitations under the License. See accompanying LICENSE file.
-->
<configuration>
<property>
    <name>yarn.resourcemanager.ha.enabled</name>
    <value>true</value>
    <description>Enable RM HA.</description>
</property>
<property>
    <name>yarn.resourcemanager.cluster-id</name>
    <value>yrc</value>
    <description>Identifies the cluster.</description>
</property>
<property>
    <name>yarn.resourcemanager.ha.rm-ids</name>
    <value>rm1,rm2,rm3</value>
    <description>List of logical IDs for the RMs. e.g., "rm1,rm2".</description>
</property>
<property>
    <name>yarn.resourcemanager.hostname.rm1</name>
    <value>hadoop</value>
    <description>Set rm1 service addresses.</description>
</property>
<property>
    <name>yarn.resourcemanager.hostname.rm2</name>
    <value>k8s-2</value>
    <description>Set rm2 service addresses.</description>
</property>
<property>
    <name>yarn.resourcemanager.hostname.rm3</name>
    <value>k8s-3</value>
    <description>Set rm3 service addresses.</description>
</property>
<property>
    <name>yarn.resourcemanager.webapp.address.rm1</name>
    <value>hadoop:8088</value>
    <description>Set rm1 web application addresses.</description>
</property>
<property>
    <name>yarn.resourcemanager.webapp.address.rm2</name>
    <value>k8s-2:8088</value>
    <description>Set rm2 web application addresses.</description>
</property>
<property>
    <name>yarn.resourcemanager.webapp.address.rm3</name>
    <value>k8s-3:8088</value>
    <description>Set rm3 web application addresses.</description>
</property>
<property>
    <name>hadoop.zk.address</name>
    <value>hadoop:2181,k8s-2:2181,k8s-3:2181</value>
    <description>Address of the ZK-quorum.</description>
</property>
</configuration>

3.7 workers

hadoop
k8s-2
k8s-3

安裝zookeeper

版本：zookeeper-3.6.4

通過https://www.apache.org/dyn/closer.lua/zookeeper/zookeeper-3.6.4/apache-zookeeper-3.6.4-bin.tar.gz 下載安裝包，3臺機器進行解壓配置安裝。

echo "1" > /data/zookeeperdata/myid #不同機器id不同

zoo.cfg配置如下：

tickTime=2000
initLimit=10
syncLimit=5
dataDir=/data/zookeeperdata #數(shù)據(jù)目錄
dataLogDir=/data/zookeeperdata/logs #日志目錄
clientPort=2181 #端口
server.1=192.xxx.xxx.128:2888:3888
server.2=192.xxx.xxx.132:2888:3888
server.3=192.xxx.xxx.131:2888:3888

環(huán)境變量配置

vi /etc/profile

export JAVA_HOME=/usr/local/jdk
export HAD00P_HOME=/usr/local/hadoop
export PATH=$PATH:$HADOOP_HOME/bin
export HADOOP_CLASSPATH=`hadoop classpath`

source /etc/profile

啟動集群

在所有節(jié)點上使用rm -rf /usr/local/hadoop/dfs命令，刪除之前創(chuàng)建的存儲路徑，同時在master節(jié)點上執(zhí)行mkdir -p /usr/local/hadoop/dfs/name /usr/local/hadoop/dfs/data /usr/local/hadoop/dfs/journalnode，再次創(chuàng)建存儲路徑。

在所有節(jié)點上使用rm -rf /usr/local/hadoop/tmp /usr/local/hadoop/logs && mkdir -p /usr/local/hadoop/tmp /usr/local/hadoop/logs命令，重置臨時路徑和日志信息。

通過以上步驟，Hadoop HA集群就配置完成了，當?shù)谝淮螁親A集群時需要依次執(zhí)行以下命令：

$ZOOKEEPER_HOME/bin/zkServer.sh start # 開啟Zookeeper進程(所有節(jié)點上執(zhí)行)
$HADOOP_HOME/bin/hdfs --daemon start journalnode # 開啟監(jiān)控NameNode的管理日志的JournalNode進程(所有節(jié)點上執(zhí)行)
$HADOOP_HOME/bin/hdfs namenode -format # 命令格式化NameNode(在master節(jié)點上執(zhí)行)
scp -r /usr/local/hadoop/dfs k8s-2:/usr/local/hadoop  # 將格式化后的目錄復制到slave1中(在master節(jié)點上執(zhí)行)
scp -r /usr/local/hadoop/dfs k8s-3:/usr/local/hadoop   # 將格式化后的目錄復制到slave2中(在master節(jié)點上執(zhí)行)
$HADOOP_HOME/bin/hdfs zkfc -formatZK # 格式化Zookeeper Failover Controllers(在master節(jié)點上執(zhí)行)
start-dfs.sh&&start-yarn.sh # 啟動HDFS和Yarn集群(在master節(jié)點上執(zhí)行)

若不是第一次啟動HA集群（常規(guī)啟動HA集群），則只需要依次執(zhí)行以下命令：

$ZOOKEEPER_HOME/bin/zkServer.sh start    # 開啟Zookeeper進程(所有節(jié)點上執(zhí)行)
start-all.sh或者$HADOOP_HOME/sbin/start-dfs.sh && $HADOOP_HOME/sbin/start-yarn.sh # 啟動HDFS和Yarn集群(在master節(jié)點上執(zhí)行)

啟動完成后每個節(jié)點使用jps命令會出現(xiàn)NameNode、DataNode、ResourceManager、NodeManager、JournalNode、DFSZKFailoverController、QuorumPeerMain和Jps 8個進程。

圖片

圖片

通過頁面訪問查看：

http://192.xxx.xxx.128:9870/

圖片

http://192.xxx.xxx.128:8088/cluster/nodes

圖片

hdfs HA驗證

6.1 查看各個節(jié)點NameNode狀態(tài)

圖片

6.2 驗證hdfs的高可用

在開啟HA集群并成功啟動的情況下，在master節(jié)點中使用hdfs haadmin -getAllServiceState命令查看各個節(jié)點NameNode狀態(tài)，接下來停止active狀態(tài)節(jié)點的NameNode進程。

圖片

Namenode active自動跳轉(zhuǎn)其他節(jié)點，集群仍可用。

圖片

圖片

隨后再啟動該節(jié)點NameNode進程，最后再次查看狀態(tài)，可以發(fā)現(xiàn)HDFS HA是正常的，并且沒有發(fā)生搶占。

圖片

驗證yarn 高可用

在master節(jié)點中使用yarn rmadmin -getAllServiceState命令查看各個節(jié)點ResourceManager狀態(tài)，接下來停止active狀態(tài)節(jié)點的ResourceManage進程，ResourceManage active自動跳轉(zhuǎn)到其他節(jié)點，集群仍可用，隨后再啟動該節(jié)點ResourceManager進程，最后再次查看狀態(tài)，F(xiàn)ailed狀態(tài)恢復為standby。

圖片

若要關閉集群可以master使用$HADOOP_HOME/sbin/stop-yarn.sh && $HADOOP_HOME/sbin/stop-dfs.sh命令或者stop-all.sh 即可關閉hadoop集群，然后關閉zookeeper,三臺機器分別執(zhí)行/data/apache-zookeeper-3.6.4-bin/bin/zkServer.sh stop。

責任編輯：武曉燕來源： IT那活兒

Hadoop 高可用

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