• 部署hadoop2.7.2 集群 基于zookeeper配置HDFS HA+Federation


    转自:http://www.2cto.com/os/201605/510489.html

    hadoop1的核心组成是两部分,即HDFS和MapReduce。在hadoop2中变为HDFS和Yarn。新的HDFS中的NameNode不再是只有一个了,可以有多个(目前只支持2个)。每一个都有相同的职能。

    两个NameNode

    当集群运行时,只有active状态的NameNode是正常工作的,standby状态的NameNode是处于待命状态的,时刻同步active状态NameNode的数据。一旦active状态的NameNode不能工作,通过手工或者自动切换,standby状态的NameNode就可以转变为active状态的,就可以继续工作了。这就是高可靠。

    NameNode发生故障时

    2个NameNode的数据其实是实时共享的。新HDFS采用了一种共享机制,JournalNode集群或者NFS进行共享。NFS是操作系统层面的,JournalNode是hadoop层面的,我们这里使用JournalNode集群进行数据共享。

    实现NameNode的自动切换

    需要使用ZooKeeper集群进行选择了。HDFS集群中的两个NameNode都在ZooKeeper中注册,当active状态的NameNode出故障时,ZooKeeper能检测到这种情况,它就会自动把standby状态的NameNode切换为active状态。

    HDFS Federation

    NameNode是核心节点,维护着整个HDFS中的元数据信息,那么其容量是有限的,受制于服务器的内存空间。当NameNode服务器的内存装不下数据后,那么HDFS集群就装不下数据了,寿命也就到头了。因此其扩展性是受限的。HDFS联盟指的是有多个HDFS集群同时工作,那么其容量理论上就不受限了,夸张点说就是无限扩展。

    节点分布

    配置过程详述

    配置文件一共包括6个,分别是hadoop-env.sh、core-site.xml、hdfs-site.xml、mapred-site.xml、yarn-site.xml和slaves。除了hdfs-site.xml文件在不同集群配置不同外,其余文件在四个节点的配置是完全一样的,可以复制。

    hadoop-env.sh

    默认的HDFS路径。当有多个HDFS集群同时工作时,用户如果不写集群名称,那么默认使用哪个哪就在这里指定!该值来自于hdfs-site.xml中的配置

    默认是NameNode、DataNode、JournalNode等存放数据的公共目录

    ZooKeeper集群的地址和端口。注意,数量一定是奇数

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    <configuration>
        <property>
            <name>fs.defaultFS</name>
            <value>hdfs://cluster1</value>
        </property>
        <property>
            <name>hadoop.tmp.dir</name>
            <value>/opt/ha/hadoop-2.7.2/data/tmp</value>
        </property>
        <property>
            <name>io.file.buffer.size</name>
            <value>131072</value>
        </property>
        <property>
            <name>ha.zookeeper.quorum</name>
            <value>hadoop:2181,hadoop1:2181,hadoop2:2181;slave1:2181;slave2:2181</value>
        </property>
    </configuration>

    hdfs-site.xml

    这里dfs.namenode.shared.edits.dir的只在hadoop1,hadoop2中最后路径为cluster1,在slave1,slave2中最后路径为cluster2,区分开就行,可以是别的名称,还有一个core-site.xml中的fs.defaultFS在slave1和slave2中可以更改为cluster2

    yarn-site.xml

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    <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.resourcemanager.hostname</name>
        <value>hadoop</value>
    </property>
    <property>
        <name>yarn.log-aggregation-enable</name>
        <value>true</value>
    </property>
    <property>
        <name>yarn.log-aggregation.retain-seconds</name>
        <value>604800</value>
    </property>

    mapred-site.xml

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    <property>
        <name>mapreduce.framework.name</name>
        <value>yarn</value>
    </property>
    <property>
        <name>mapreduce.job.tracker</name>
        <value>hdfs://hadoop:9001</value>
        <final>true</final>
    </property>
    <property>
        <name>mapreduce.jobhistory.address</name>
        <value>hadoop:10020</value>
    </property>
    <property>
        <name>mapreduce.jobhistory.webapp.address</name>
        <value>hadoop:19888</value>
    </property>

    slaves

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    hadoop
    hadoop1
    hadoop2
    slave1
    slave2

    启动过程

    在所有zk节点启动zookeeper

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    hadoop@hadoop:hadoop-2.7.2$ zkServer.sh start

    格式化zookeeper集群

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    [hadoop@hadoop1 hadoop-2.7.2]$ bin/hdfs zkfc -formatZK
    [hadoop@slave1 hadoop-2.7.2]$ bin/hdfs zkfc -formatZK
    [hadoop@slave1 hadoop-2.7.2]$ zkCli.sh
    [zk: localhost:2181(CONNECTED) 5] ls /hadoop-ha/cluster
     
    cluster2   cluster1

    在所有节点启动journalnode

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    hadoop@hadoop:hadoop-2.7.2$ sbin/hadoop-daemon.sh start journalnode
    starting journalnode, logging to /opt/ha/hadoop-2.7.2/logs/hadoop-hadoop-journalnode-hadoop.out
    hadoop@hadoop:hadoop-2.7.2$


    在cluster1中的nn1格式化namenode,验证并启动

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    [hadoop@hadoop1 hadoop-2.7.2]$ bin/hdfs namenode -format -clusterId hadoop1
    16/05/19 15:43:01 INFO common.Storage: Storage directory /opt/ha/hadoop-2.7.2/data/dfs/name has been successfully formatted.
    16/05/19 15:43:01 INFO namenode.NNStorageRetentionManager: Going to retain 1 images with txid >= 0
    16/05/19 15:43:01 INFO util.ExitUtil: Exiting with status 0
    16/05/19 15:43:01 INFO namenode.NameNode: SHUTDOWN_MSG:
    /************************************************************
    SHUTDOWN_MSG: Shutting down NameNode at hadoop1/192.168.2.10
    ************************************************************/
    [hadoop@hadoop1 hadoop-2.7.2]$ ls data/dfs/name/current/
    fsimage_0000000000000000000      seen_txid
    fsimage_0000000000000000000.md5  VERSION
    [hadoop@hadoop1 hadoop-2.7.2]$ sbin/hadoop-daemon.sh start namenode
    starting namenode, logging to /opt/ha/hadoop-2.7.2/logs/hadoop-hadoop-namenode-hadoop1.out
    [hadoop@hadoop1 hadoop-2.7.2]$ jps
    9551 NameNode
    9423 JournalNode
    9627 Jps
    9039 QuorumPeerMain

    http://hadoop1:50070查看

    cluster1中另一个节点同步数据格式化,并启动

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    [hadoop@hadoop2 hadoop-2.7.2]$ bin/hdfs namenode -bootstrapStandby
    ......
    16/05/19 15:48:27 INFO common.Storage: Storage directory /opt/ha/hadoop-2.7.2/data/dfs/name has been successfully formatted.
    16/05/19 15:48:27 INFO namenode.TransferFsImage: Opening connection to http://hadoop1:50070/imagetransfer?getimage=1&txid=0&storageInfo=-63:1280767544:0:hadoop1
    16/05/19 15:48:28 INFO namenode.TransferFsImage: Image Transfer timeout configured to 60000 milliseconds
    16/05/19 15:48:28 INFO namenode.TransferFsImage: Transfer took 0.00s at 0.00 KB/s
    16/05/19 15:48:28 INFO namenode.TransferFsImage: Downloaded file fsimage.ckpt_0000000000000000000 size 353 bytes.
    16/05/19 15:48:28 INFO util.ExitUtil: Exiting with status 0
    16/05/19 15:48:28 INFO namenode.NameNode: SHUTDOWN_MSG:
    /************************************************************
    SHUTDOWN_MSG: Shutting down NameNode at hadoop2/192.168.2.11
    ************************************************************/
    [hadoop@hadoop2 hadoop-2.7.2]$ ls data/dfs/name/current/
    fsimage_0000000000000000000      seen_txid
    fsimage_0000000000000000000.md5  VERSION
    [hadoop@hadoop2 hadoop-2.7.2]$
    [hadoop@hadoop2 hadoop-2.7.2]$ sbin/hadoop-daemon.sh start namenode
    starting namenode, logging to /opt/ha/hadoop-2.7.2/logs/hadoop-hadoop-namenode-hadoop2.out
    [hadoop@hadoop2 hadoop-2.7.2]$ jps
    7196 Jps
    6980 JournalNode
    7120 NameNode
    6854 QuorumPeerMain

    http://hadoop2:50070查看如下

    使用以上步骤同是启动cluster2的两个namenode;这里省略

    然后启动所有的datanode和(必须也在hadoop节点上启动)yarn

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    [hadoop@hadoop1 hadoop-2.7.2]$ sbin/hadoop-daemons.sh start datanode
    hadoop1: starting datanode, logging to /opt/ha/hadoop-2.7.2/logs/hadoop-hadoop-datanode-hadoop1.out
    slave2: starting datanode, logging to /opt/ha/hadoop-2.7.2/logs/hadoop-hadoop-datanode-slave2.out
    hadoop2: starting datanode, logging to /opt/ha/hadoop-2.7.2/logs/hadoop-hadoop-datanode-hadoop2.out
    slave1: starting datanode, logging to /opt/ha/hadoop-2.7.2/logs/hadoop-hadoop-datanode-slave1.out
    hadoop: starting datanode, logging to /opt/ha/hadoop-2.7.2/logs/hadoop-hadoop-datanode-hadoop.out
    hadoop@hadoop:hadoop-2.7.2$ sbin/start-yarn.sh
    starting yarn daemons
    starting resourcemanager, logging to /opt/ha/hadoop-2.7.2/logs/yarn-hadoop-resourcemanager-hadoop.out
    hadoop2: starting nodemanager, logging to /opt/ha/hadoop-2.7.2/logs/yarn-hadoop-nodemanager-hadoop2.out
    hadoop1: starting nodemanager, logging to /opt/ha/hadoop-2.7.2/logs/yarn-hadoop-nodemanager-hadoop1.out
    slave2: starting nodemanager, logging to /opt/ha/hadoop-2.7.2/logs/yarn-hadoop-nodemanager-slave2.out
    hadoop: starting nodemanager, logging to /opt/ha/hadoop-2.7.2/logs/yarn-hadoop-nodemanager-hadoop.out
    slave1: starting nodemanager, logging to /opt/ha/hadoop-2.7.2/logs/yarn-hadoop-nodemanager-slave1.out
    hadoop@hadoop:hadoop-2.7.2$ jps
    19384 JournalNode
    19013 QuorumPeerMain
    20649 Jps
    20241 ResourceManager
    20396 NodeManager
    19815 DataNode
     
     
    [hadoop@hadoop1 hadoop-2.7.2]$ jps
    10091 NodeManager
    9551 NameNode
    9822 DataNode
    9423 JournalNode
    10232 Jps
    9039 QuorumPeerMain
    [hadoop@hadoop2 hadoop-2.7.2]$ jps
    7450 NodeManager
    7295 DataNode
    6980 JournalNode
    7120 NameNode
    6854 QuorumPeerMain
    7580 Jps
    [hadoop@slave1 hadoop-2.7.2]$ jps
    3706 DataNode
    3988 Jps
    3374 JournalNode
    3591 NameNode
    3860 NodeManager
    3184 QuorumPeerMain
    [hadoop@slave2 hadoop-2.7.2]$ jps
    3023 QuorumPeerMain
    3643 NodeManager
    3782 Jps
    3177 JournalNode
    3497 DataNode
    3383 NameNod
      

    http://hadoop:8088/cluster/nodes/


     

    所有namenode节点启动zkfc

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    [hadoop@hadoop1 hadoop-2.7.2]$ sbin/hadoop-daemon.sh start zkfc
    starting zkfc, logging to /opt/ha/hadoop-2.7.2/logs/hadoop-hadoop-zkfc-hadoop1.out
    [hadoop@hadoop1 hadoop-2.7.2]$ jps
    10665 DFSZKFailoverController
    9551 NameNode
    9822 DataNode
    9423 JournalNode
    10739 Jps
    9039 QuorumPeerMain
    10483 NodeManager


    上传文件测试

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    [hadoop@hadoop1 hadoop-2.7.2]$ bin/hdfs dfs -mkdir /test
    16/05/19 16:09:19 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
    [hadoop@hadoop1 hadoop-2.7.2]$ bin/hdfs dfs -put etc/hadoop/*.xml /test
    16/05/19 16:09:36 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
    #在slave1中查看
    [hadoop@slave1 hadoop-2.7.2]$ bin/hdfs dfs -ls -R /
    16/05/19 16:11:32 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
    drwxr-xr-x   - hadoop supergroup          0 2016-05-19 16:09 /test
    -rw-r--r--   2 hadoop supergroup       4436 2016-05-19 16:09 /test/capacity-scheduler.xml
    -rw-r--r--   2 hadoop supergroup       1185 2016-05-19 16:09 /test/core-site.xml
    -rw-r--r--   2 hadoop supergroup       9683 2016-05-19 16:09 /test/hadoop-policy.xml
    -rw-r--r--   2 hadoop supergroup       3814 2016-05-19 16:09 /test/hdfs-site.xml
    -rw-r--r--   2 hadoop supergroup        620 2016-05-19 16:09 /test/httpfs-site.xml
    -rw-r--r--   2 hadoop supergroup       3518 2016-05-19 16:09 /test/kms-acls.xml
    -rw-r--r--   2 hadoop supergroup       5511 2016-05-19 16:09 /test/kms-site.xml
    -rw-r--r--   2 hadoop supergroup       1170 2016-05-19 16:09 /test/mapred-site.xml
    -rw-r--r--   2 hadoop supergroup       1777 2016-05-19 16:09 /test/yarn-site.xml
    [hadoop@slave1 hadoop-2.7.2]$
      

    验证yarn

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    [hadoop@hadoop1 hadoop-2.7.2]$ bin/hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.7.2.jar wordcount /test /out
    16/05/19 16:15:25 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
    16/05/19 16:15:26 INFO client.RMProxy: Connecting to ResourceManager at hadoop/192.168.2.3:8032
    16/05/19 16:15:27 INFO input.FileInputFormat: Total input paths to process : 9
    16/05/19 16:15:27 INFO mapreduce.JobSubmitter: number of splits:9
    16/05/19 16:15:27 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1463644924165_0001
    16/05/19 16:15:27 INFO impl.YarnClientImpl: Submitted application application_1463644924165_0001
    16/05/19 16:15:27 INFO mapreduce.Job: The url to track the job: http://hadoop:8088/proxy/application_1463644924165_0001/
    16/05/19 16:15:27 INFO mapreduce.Job: Running job: job_1463644924165_0001
    16/05/19 16:15:35 INFO mapreduce.Job: Job job_1463644924165_0001 running in uber mode : false
    16/05/19 16:15:35 INFO mapreduce.Job:  map 0% reduce 0%
    16/05/19 16:15:44 INFO mapreduce.Job:  map 11% reduce 0%
    16/05/19 16:15:59 INFO mapreduce.Job:  map 11% reduce 4%
    16/05/19 16:16:08 INFO mapreduce.Job:  map 22% reduce 4%
    16/05/19 16:16:10 INFO mapreduce.Job:  map 22% reduce 7%
    16/05/19 16:16:22 INFO mapreduce.Job:  map 56% reduce 7%
    16/05/19 16:16:26 INFO mapreduce.Job:  map 100% reduce 67%
    16/05/19 16:16:29 INFO mapreduce.Job:  map 100% reduce 100%
    16/05/19 16:16:29 INFO mapreduce.Job: Job job_1463644924165_0001 completed successfully
    16/05/19 16:16:31 INFO mapreduce.Job: Counters: 51
        File System Counters
            FILE: Number of bytes read=25164
            FILE: Number of bytes written=1258111
            FILE: Number of read operations=0
            FILE: Number of large read operations=0
            FILE: Number of write operations=0
            HDFS: Number of bytes read=32620
            HDFS: Number of bytes written=13523
            HDFS: Number of read operations=30
            HDFS: Number of large read operations=0
            HDFS: Number of write operations=2
        Job Counters
            Killed map tasks=2
            Launched map tasks=10
            Launched reduce tasks=1
            Data-local map tasks=8
            Rack-local map tasks=2
            Total time spent by all maps in occupied slots (ms)=381816
            Total time spent by all reduces in occupied slots (ms)=42021
            Total time spent by all map tasks (ms)=381816
            Total time spent by all reduce tasks (ms)=42021
            Total vcore-milliseconds taken by all map tasks=381816
            Total vcore-milliseconds taken by all reduce tasks=42021
            Total megabyte-milliseconds taken by all map tasks=390979584
            Total megabyte-milliseconds taken by all reduce tasks=43029504
        Map-Reduce Framework
            Map input records=963
            Map output records=3041
            Map output bytes=41311
            Map output materialized bytes=25212
            Input split bytes=906
            Combine input records=3041
            Combine output records=1335
            Reduce input groups=673
            Reduce shuffle bytes=25212
            Reduce input records=1335
            Reduce output records=673
            Spilled Records=2670
            Shuffled Maps =9
            Failed Shuffles=0
            Merged Map outputs=9
            GC time elapsed (ms)=43432
            CPU time spent (ms)=30760
            Physical memory (bytes) snapshot=1813704704
            Virtual memory (bytes) snapshot=8836780032
            Total committed heap usage (bytes)=1722810368
        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=31714
        File Output Format Counters
            Bytes Written=13523

    http://hadoop:8088/查看

    结果

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    [hadoop@slave1 hadoop-2.7.2]$ bin/hdfs dfs -lsr /out
    lsr: DEPRECATED: Please use 'ls -R' instead.
    16/05/19 16:22:14 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
    -rw-r--r--   2 hadoop supergroup          0 2016-05-19 16:16 /out/_SUCCESS
    -rw-r--r--   2 hadoop supergroup      13523 2016-05-19 16:16 /out/part-r-00000
    [hadoop@slave1 hadoop-2.7.2]$


    测试故障自动转移

    当前情况在网页查看hadoop1和slave1为Active状态,

    那把这两个namenode关闭,再查看

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    [hadoop@hadoop1 hadoop-2.7.2]$ jps
    10665 DFSZKFailoverController
    9551 NameNode
    12166 Jps
    9822 DataNode
    9423 JournalNode
    9039 QuorumPeerMain
    10483 NodeManager
    [hadoop@hadoop1 hadoop-2.7.2]$ sbin/hadoop-daemon.sh stop namenode
    stopping namenode
    [hadoop@hadoop1 hadoop-2.7.2]$ jps
    10665 DFSZKFailoverController
    9822 DataNode
    9423 JournalNode
    12221 Jps
    9039 QuorumPeerMain
    10483 NodeManager


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    [hadoop@slave1 hadoop-2.7.2]$ sbin/hadoop-daemon.sh stop namenode
    stopping namenode
    [hadoop@slave1 hadoop-2.7.2]$ jps
    3706 DataNode
    3374 JournalNode
    4121 NodeManager
    5460 Jps
    4324 DFSZKFailoverController
    3184 QuorumPeerMain

    此时Active NN已经分别转移到hadoop2和slave2上了

    以上是hadoop2.2.0的HDFS集群HA配置和自动切换、HDFS federation配置、Yarn配置的基本过程,其中大家可以添加其他配置,zookeeper和journalnode也不一定所有节点都启动,只要是奇数个就ok,如果集群数量多,这些及节点均可以单独配置在一个host上

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  • 原文地址:https://www.cnblogs.com/seaspring/p/6000210.html
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