搭建hadoop2.6.0集群环境

mac2022-06-30 28

一、规划（一）硬件资源 10.171.29.191 master 10.171.94.155 slave1 10.251.0.197 slave3

（二）基本资料用户： jediael 目录：/mnt/jediael/ 二、环境配置（一）统一用户名密码，并为jediael赋予执行所有命令的权限 #passwd # useradd jediael # passwd jediael # vi /etc/sudoers 增加以下一行： jediael ALL=(ALL) ALL

（二）创建目录/mnt/jediael $sudo chown jediael:jediael /opt $ cd /opt $ sudo mkdir jediael 注意:/opt必须是jediael的，否则会在format namenode时出错。（三）修改用户名及/etc/hosts文件 1、修改/etc/sysconfig/network NETWORKING=yes HOSTNAME=*******

2、修改/etc/hosts 10.171.29.191 master 10.171.94.155 slave1 10.251.0.197 slave3 注意hosts文件不能有127.0.0.1 *****配置，否则会导致出现异常。org.apache.hadoop.ipc.Client: Retrying connect to server: master/10.171.29.191:9000. Already trie

3、hostname命令 hostname **** （四）配置免密码登录以上命令在master上使用jediael用户执行： $ ssh-keygen -t dsa -P '' -f ~/.ssh/id_dsa $ cat ~/.ssh/id_dsa.pub >> ~/.ssh/authorized_keys 然后，将authorized_keys复制到slave1,slave2 scp ~/.ssh/authorized_keys slave1:~/.ssh/ scp ~/.ssh/authorized_keys slave2:~/.ssh/ 注意（1）若提示.ssh目录不存在，则表示此机器从未运行过ssh，因此运行一次即可创建.ssh目录。（2）.ssh/的权限为600,authorized_keys的权限为700，权限大了小了都不行。（五）在3台机器上分别安装java，并设置相关环境变量参考http://blog.csdn.net/jediael_lu/article/details/38925871 （六）下载hadoop-2.6.0.tar.gz，并将其解压到/mnt/jediael wget http://mirror.bit.edu.cn/apache/hadoop/common/hadoop-2.6.0/hadoop-2.6.0.tar.gz tar -zxvf hadoop-2.6.0.tar.gz三、修改配置文件【3台机器上均要执行，一般先在一台机器上配置完成，再用scp复制到其它机器】（一）hadoop_env.sh export JAVA_HOME=/usr/java/jdk1.7.0_51 （二）修改core-site.xml

<property> <name>hadoop.tmp.dir</name> <value>/mnt/tmp</value> <description>Abase for other temporary directories.</description> </property> <property> <name>fs.defaultFS</name> <value>hdfs://master:9000</value> </property> <property> <name>io.file.buffer.size</name> <value>4096</value> </property> （三）修改hdfs-site.xml <property> <name>dfs.replication</name> <value>2</value> </property> （四）修改mapred-site.xml <property> <name>mapreduce.framework.name</name> <value>yarn</value> <final>true</final> </property> <property> <name>mapreduce.jobtracker.http.address</name> <value>master:50030</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> <property> <name>mapred.job.tracker</name> <value>http://master:9001</value> </property> （五）修改yarn.xml <property> <name>yarn.resourcemanager.hostname</name> <value>master</value> </property> <property> <name>yarn.nodemanager.aux-services</name> <value>mapreduce_shuffle</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.resource-tracker.address</name> <value>master:8031</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> （六）修改slaves 【不用修改masters文件？？】 slaves: slave1 slave3 四、启动并验证 1、格式化namenode [jediael@master hadoop-1.2.1]$ bin/hadoop namenode -format 2、启动hadoop【此步骤只需要在master上执行】 [jediael@master hadoop-1.2.1]$ bin/start-all.sh 3、验证1：向hdfs中写入内容 [jediael@master hadoop-2.6.0]$ bin/hadoop fs -ls / [jediael@master hadoop-2.6.0]$ bin/hadoop fs -mkdir /test [jediael@master hadoop-2.6.0]$ bin/hadoop fs -ls / Found 1 items drwxr-xr-x - jediael supergroup 0 2015-04-19 23:41 /test 4、验证：登录页面 NameNode http://ip:50070 5、查看各个主机的java进程（1）master: $ jps 3694 NameNode 3882 SecondaryNameNode 7216 Jps 4024 ResourceManager

（2）slave1: $ jps 1913 NodeManager 2673 Jps 1801 DataNode

（3）slave3: $ jps 1942 NodeManager 2252 Jps 1840 DataNode 五、运行一个完整的mapreduce程序:运行自带的wordcount程序 $ bin/hadoop fs -mkdir /input

$ bin/hadoop fs -ls / Found 2 items drwxr-xr-x - jediael supergroup 0 2015-04-20 18:04 /input drwxr-xr-x - jediael supergroup 0 2015-04-19 23:41 /test

$ bin/hadoop fs -copyFromLocal etc/hadoop/mapred-site.xml.template /input

$ pwd /mnt/jediael/hadoop-2.6.0/share/hadoop/mapreduce

$ /mnt/jediael/hadoop-2.6.0/bin/hadoop jar hadoop-mapreduce-examples-2.6.0.jar wordcount /input /output 15/04/20 18:15:47 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable 15/04/20 18:15:48 INFO Configuration.deprecation: session.id is deprecated. Instead, use dfs.metrics.session-id 15/04/20 18:15:48 INFO jvm.JvmMetrics: Initializing JVM Metrics with processName=JobTracker, sessionId= 15/04/20 18:15:49 INFO input.FileInputFormat: Total input paths to process : 1 15/04/20 18:15:49 INFO mapreduce.JobSubmitter: number of splits:1 15/04/20 18:15:49 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_local657082309_0001 15/04/20 18:15:50 INFO mapreduce.Job: The url to track the job: http://localhost:8080/ 15/04/20 18:15:50 INFO mapreduce.Job: Running job: job_local657082309_0001 15/04/20 18:15:50 INFO mapred.LocalJobRunner: OutputCommitter set in config null 15/04/20 18:15:50 INFO mapred.LocalJobRunner: OutputCommitter is org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter 15/04/20 18:15:50 INFO mapred.LocalJobRunner: Waiting for map tasks 15/04/20 18:15:50 INFO mapred.LocalJobRunner: Starting task: attempt_local657082309_0001_m_000000_0 15/04/20 18:15:50 INFO mapred.Task: Using ResourceCalculatorProcessTree : [ ] 15/04/20 18:15:50 INFO mapred.MapTask: Processing split: hdfs://master:9000/input/mapred-site.xml.template:0+2268 15/04/20 18:15:51 INFO mapred.MapTask: (EQUATOR) 0 kvi 26214396(104857584) 15/04/20 18:15:51 INFO mapred.MapTask: mapreduce.task.io.sort.mb: 100 15/04/20 18:15:51 INFO mapred.MapTask: soft limit at 83886080 15/04/20 18:15:51 INFO mapred.MapTask: bufstart = 0; bufvoid = 104857600 15/04/20 18:15:51 INFO mapred.MapTask: kvstart = 26214396; length = 6553600 15/04/20 18:15:51 INFO mapred.MapTask: Map output collector class = org.apache.hadoop.mapred.MapTask$MapOutputBuffer 15/04/20 18:15:51 INFO mapred.LocalJobRunner: 15/04/20 18:15:51 INFO mapred.MapTask: Starting flush of map output 15/04/20 18:15:51 INFO mapred.MapTask: Spilling map output 15/04/20 18:15:51 INFO mapred.MapTask: bufstart = 0; bufend = 1698; bufvoid = 104857600 15/04/20 18:15:51 INFO mapred.MapTask: kvstart = 26214396(104857584); kvend = 26213916(104855664); length = 481/6553600 15/04/20 18:15:51 INFO mapred.MapTask: Finished spill 0 15/04/20 18:15:51 INFO mapred.Task: Task:attempt_local657082309_0001_m_000000_0 is done. And is in the process of committing 15/04/20 18:15:51 INFO mapred.LocalJobRunner: map 15/04/20 18:15:51 INFO mapred.Task: Task 'attempt_local657082309_0001_m_000000_0' done. 15/04/20 18:15:51 INFO mapred.LocalJobRunner: Finishing task: attempt_local657082309_0001_m_000000_0 15/04/20 18:15:51 INFO mapred.LocalJobRunner: map task executor complete. 15/04/20 18:15:51 INFO mapred.LocalJobRunner: Waiting for reduce tasks 15/04/20 18:15:51 INFO mapred.LocalJobRunner: Starting task: attempt_local657082309_0001_r_000000_0 15/04/20 18:15:51 INFO mapred.Task: Using ResourceCalculatorProcessTree : [ ] 15/04/20 18:15:51 INFO mapred.ReduceTask: Using ShuffleConsumerPlugin: org.apache.hadoop.mapreduce.task.reduce.Shuffle@39be5e01 15/04/20 18:15:51 INFO reduce.MergeManagerImpl: MergerManager: memoryLimit=363285696, maxSingleShuffleLimit=90821424, mergeThreshold=239768576, ioSortFactor=10, memToMemMergeOutputsThreshold=10 15/04/20 18:15:51 INFO reduce.EventFetcher: attempt_local657082309_0001_r_000000_0 Thread started: EventFetcher for fetching Map Completion Events 15/04/20 18:15:51 INFO reduce.LocalFetcher: localfetcher#1 about to shuffle output of map attempt_local657082309_0001_m_000000_0 decomp: 1566 len: 1570 to MEMORY 15/04/20 18:15:51 INFO reduce.InMemoryMapOutput: Read 1566 bytes from map-output for attempt_local657082309_0001_m_000000_0 15/04/20 18:15:51 INFO reduce.MergeManagerImpl: closeInMemoryFile -> map-output of size: 1566, inMemoryMapOutputs.size() -> 1, commitMemory -> 0, usedMemory ->1566 15/04/20 18:15:51 INFO reduce.EventFetcher: EventFetcher is interrupted.. Returning 15/04/20 18:15:51 INFO mapred.LocalJobRunner: 1 / 1 copied. 15/04/20 18:15:51 INFO reduce.MergeManagerImpl: finalMerge called with 1 in-memory map-outputs and 0 on-disk map-outputs 15/04/20 18:15:51 INFO mapred.Merger: Merging 1 sorted segments 15/04/20 18:15:51 INFO mapred.Merger: Down to the last merge-pass, with 1 segments left of total size: 1560 bytes 15/04/20 18:15:51 INFO reduce.MergeManagerImpl: Merged 1 segments, 1566 bytes to disk to satisfy reduce memory limit 15/04/20 18:15:51 INFO reduce.MergeManagerImpl: Merging 1 files, 1570 bytes from disk 15/04/20 18:15:51 INFO reduce.MergeManagerImpl: Merging 0 segments, 0 bytes from memory into reduce 15/04/20 18:15:51 INFO mapred.Merger: Merging 1 sorted segments 15/04/20 18:15:51 INFO mapred.Merger: Down to the last merge-pass, with 1 segments left of total size: 1560 bytes 15/04/20 18:15:51 INFO mapred.LocalJobRunner: 1 / 1 copied. 15/04/20 18:15:51 INFO Configuration.deprecation: mapred.skip.on is deprecated. Instead, use mapreduce.job.skiprecords 15/04/20 18:15:51 INFO mapreduce.Job: Job job_local657082309_0001 running in uber mode : false 15/04/20 18:15:51 INFO mapreduce.Job: map 100% reduce 0% 15/04/20 18:15:51 INFO mapred.Task: Task:attempt_local657082309_0001_r_000000_0 is done. And is in the process of committing 15/04/20 18:15:51 INFO mapred.LocalJobRunner: 1 / 1 copied. 15/04/20 18:15:51 INFO mapred.Task: Task attempt_local657082309_0001_r_000000_0 is allowed to commit now 15/04/20 18:15:51 INFO output.FileOutputCommitter: Saved output of task 'attempt_local657082309_0001_r_000000_0' to hdfs://master:9000/output/_temporary/0/task_local657082309_0001_r_000000 15/04/20 18:15:51 INFO mapred.LocalJobRunner: reduce > reduce 15/04/20 18:15:51 INFO mapred.Task: Task 'attempt_local657082309_0001_r_000000_0' done. 15/04/20 18:15:51 INFO mapred.LocalJobRunner: Finishing task: attempt_local657082309_0001_r_000000_0 15/04/20 18:15:51 INFO mapred.LocalJobRunner: reduce task executor complete. 15/04/20 18:15:52 INFO mapreduce.Job: map 100% reduce 100% 15/04/20 18:15:52 INFO mapreduce.Job: Job job_local657082309_0001 completed successfully 15/04/20 18:15:52 INFO mapreduce.Job: Counters: 38 File System Counters FILE: Number of bytes read=544164 FILE: Number of bytes written=1040966 FILE: Number of read operations=0 FILE: Number of large read operations=0 FILE: Number of write operations=0 HDFS: Number of bytes read=4536 HDFS: Number of bytes written=1196 HDFS: Number of read operations=15 HDFS: Number of large read operations=0 HDFS: Number of write operations=4 Map-Reduce Framework Map input records=43 Map output records=121 Map output bytes=1698 Map output materialized bytes=1570 Input split bytes=114 Combine input records=121 Combine output records=92 Reduce input groups=92 Reduce shuffle bytes=1570 Reduce input records=92 Reduce output records=92 Spilled Records=184 Shuffled Maps =1 Failed Shuffles=0 Merged Map outputs=1 GC time elapsed (ms)=123 CPU time spent (ms)=0 Physical memory (bytes) snapshot=0 Virtual memory (bytes) snapshot=0 Total committed heap usage (bytes)=269361152 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=2268 File Output Format Counters

$ /mnt/jediael/hadoop-2.6.0/bin/hadoop fs -cat /output/*

转载于:https://www.cnblogs.com/jinhong-lu/p/4559329.html

相关资源：JAVA上百实例源码以及开源项目

最新回复(0)