hadoop 2.7.3本地环境运行官方wordcount

hadoop 2.7.3本地环境运行官方wordcount

基本环境：

系统：win7

虚机环境：virtualBox

虚机：centos 7

hadoop版本：2.7.3

本次先以独立模式（本地模式）来运行。

参考：

• hadoop docs

  ​

1 hadoop 安装

java环境

yum install java-1.8.0-openjdk

hadoop下载压缩包并安装

mkdir ~/hadoop/
cd ~/hadoop/

# http://apache.fayea.com/hadoop/common/hadoop-2.7.3/
curl http://apache.fayea.com/apache/hadoop/common/hadoop-2.7.3/hadoop-2.7.3.tar.gz -O
# 如果下载出现中断，则可以使用-C参数继续下载

ls -l
#-rw-rw-r--. 1 jungle jungle 165297920 Jan  6 13:10 hadoop-2.7.3.tar.gz

curl http://apache.fayea.com/apache/hadoop/common/hadoop-2.7.3/hadoop-2.7.3.tar.gz -C 165297920 -O
# ** Resuming transfer from byte position 165297920 ……

# download checksum
curl http://apache.fayea.com/hadoop/core/hadoop-2.7.3/hadoop-2.7.3.tar.gz.mds -O

# check
cat hadoop-2.7.3.tar.gz.mds

md5sum hadoop-2.7.3.tar.gz
sha256sum hadoop-2.7.3.tar.gz

tar -zxf hadoop-2.7.3.tar.gz
mv hadoop-2.7.3 hadoop-local

2 配置环境

因为是使用本地模式，需要配置的项非常少，只需要涉及环境变量。

# java path
whereis java
java: /usr/bin/java /usr/lib/java /etc/java /usr/share/java 

ls -l /usr/bin/java
lrwxrwxrwx. 1 root root 22 Dec 30 12:26 /usr/bin/java -> /etc/alternatives/java

ls -l /etc/alternatives/java
lrwxrwxrwx. 1 root root 73 Dec 30 12:26 /etc/alternatives/java -> /usr/lib/jvm/java-1.8.0-openjdk-1.8.0.111-2.b15.el7_3.x86_64/jre/bin/java

在~/.bashrc中增加如下三行

export JAVA_HOME=/usr/lib/jvm/java-1.8.0-openjdk-1.8.0.111-2.b15.el7_3.x86_64/jre
export HADOOP_INSTALL=/home/jungle/hadoop/hadoop-local
export PATH=$PATH:$HADOOP_INSTALL/bin:$HADOOP_INSTALL/sbin

确认hadoop可用：

hadoop version
Hadoop 2.7.3
Subversion https://git-wip-us.apache.org/repos/asf/hadoop.git -r baa91f7c6bc9cb92be5982de4719c1c8af91ccff
Compiled by root on 2016-08-18T01:41Z
Compiled with protoc 2.5.0
From source with checksum 2e4ce5f957ea4db193bce3734ff29ff4
This command was run using /home/jungle/hadoop/hadoop-local/share/hadoop/common/hadoop-common-2.7.3.jar

2 使用linux文件系统做测试

直接使用linux的文件系统做测试，即不使用hadoop fs相关命令。

2.1 wordcount

bin/hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.7.3.jar
An example program must be given as the first argument.
Valid program names are:
  aggregatewordcount: An Aggregate based map/reduce program that counts the words in the input files.
  aggregatewordhist: An Aggregate based map/reduce program that computes the histogram of the words in the input files.
  bbp: A map/reduce program that uses Bailey-Borwein-Plouffe to compute exact digits of Pi.
  dbcount: An example job that count the pageview counts from a database.
# ...
  wordcount: A map/reduce program that counts the words in the input files.
# ...

bin/hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.7.3.jar  wordcount
# Usage: wordcount <in> [<in>...] <out>

2.2 准备数据

mkdir -p dataLocal/input/
cd dataLocal/input/

echo "hello world, I am jungle. bye world" > file1.txt
echo "hello hadoop. hello jungle. bye hadoop." > file2.txt
echo "the great software is hadoop." >> file2.txt

2.3 运行

cd /home/jungle/hadoop/hadoop-local/

hadoop jar /home/jungle/hadoop/hadoop-local/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.7.3.jar wordcount  dataLocal/input/ dataLocal/outout
# dataLocal/outout 当前不存在，由程序生成
echo $?

ls -la dataLocal/outout/
total 12
drwxrwxr-x. 2 jungle jungle 84 Jan  6 16:53 .
drwxrwxr-x. 4 jungle jungle 31 Jan  6 16:53 ..
-rw-r--r--. 1 jungle jungle 82 Jan  6 16:53 part-r-00000
-rw-r--r--. 1 jungle jungle 12 Jan  6 16:53 .part-r-00000.crc
-rw-r--r--. 1 jungle jungle  0 Jan  6 16:53 _SUCCESS
-rw-r--r--. 1 jungle jungle  8 Jan  6 16:53 ._SUCCESS.crc

# 结果
cat dataLocal/outout//part-r-00000
I	1
am	1
bye	2
great	1
hadoop.	3
hello	3
is	1
jungle.	2
software	1
the	1
world.	2

2.4 最后是运行日志

通过日志，可以了解运行时的一些常用参数和配置。

17/01/06 16:53:26 INFO Configuration.deprecation: session.id is deprecated. Instead, use dfs.metrics.session-id
17/01/06 16:53:26 INFO jvm.JvmMetrics: Initializing JVM Metrics with processName=JobTracker, sessionId=
17/01/06 16:53:26 INFO input.FileInputFormat: Total input paths to process : 2
17/01/06 16:53:26 INFO mapreduce.JobSubmitter: number of splits:2
17/01/06 16:53:27 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_local1147390429_0001
17/01/06 16:53:27 INFO mapreduce.Job: The url to track the job: http://localhost:8080/
17/01/06 16:53:27 INFO mapreduce.Job: Running job: job_local1147390429_0001
17/01/06 16:53:27 INFO mapred.LocalJobRunner: OutputCommitter set in config null
17/01/06 16:53:27 INFO output.FileOutputCommitter: File Output Committer Algorithm version is 1
17/01/06 16:53:27 INFO mapred.LocalJobRunner: OutputCommitter is org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter
17/01/06 16:53:27 INFO mapred.LocalJobRunner: Waiting for map tasks
17/01/06 16:53:27 INFO mapred.LocalJobRunner: Starting task: attempt_local1147390429_0001_m_000000_0
17/01/06 16:53:27 INFO output.FileOutputCommitter: File Output Committer Algorithm version is 1
17/01/06 16:53:27 INFO mapred.Task:  Using ResourceCalculatorProcessTree : [ ]
17/01/06 16:53:27 INFO mapred.MapTask: Processing split: file:/home/jungle/hadoop/hadoop-local/dataLocal/input/file2.txt:0+70
17/01/06 16:53:27 INFO mapred.MapTask: (EQUATOR) 0 kvi 26214396(104857584)
17/01/06 16:53:27 INFO mapred.MapTask: mapreduce.task.io.sort.mb: 100
17/01/06 16:53:27 INFO mapred.MapTask: soft limit at 83886080
17/01/06 16:53:27 INFO mapred.MapTask: bufstart = 0; bufvoid = 104857600
17/01/06 16:53:27 INFO mapred.MapTask: kvstart = 26214396; length = 6553600
17/01/06 16:53:27 INFO mapred.MapTask: Map output collector class = org.apache.hadoop.mapred.MapTask$MapOutputBuffer
17/01/06 16:53:27 INFO mapred.LocalJobRunner:
17/01/06 16:53:27 INFO mapred.MapTask: Starting flush of map output
17/01/06 16:53:27 INFO mapred.MapTask: Spilling map output
17/01/06 16:53:27 INFO mapred.MapTask: bufstart = 0; bufend = 114; bufvoid = 104857600
17/01/06 16:53:27 INFO mapred.MapTask: kvstart = 26214396(104857584); kvend = 26214356(104857424); length = 41/6553600
17/01/06 16:53:27 INFO mapred.MapTask: Finished spill 0
17/01/06 16:53:27 INFO mapred.Task: Task:attempt_local1147390429_0001_m_000000_0 is done. And is in the process of committing
17/01/06 16:53:27 INFO mapred.LocalJobRunner: map
17/01/06 16:53:27 INFO mapred.Task: Task 'attempt_local1147390429_0001_m_000000_0' done.
17/01/06 16:53:27 INFO mapred.LocalJobRunner: Finishing task: attempt_local1147390429_0001_m_000000_0
17/01/06 16:53:27 INFO mapred.LocalJobRunner: Starting task: attempt_local1147390429_0001_m_000001_0
17/01/06 16:53:27 INFO output.FileOutputCommitter: File Output Committer Algorithm version is 1
17/01/06 16:53:27 INFO mapred.Task:  Using ResourceCalculatorProcessTree : [ ]
17/01/06 16:53:27 INFO mapred.MapTask: Processing split: file:/home/jungle/hadoop/hadoop-local/dataLocal/input/file1.txt:0+37
17/01/06 16:53:27 INFO mapred.MapTask: (EQUATOR) 0 kvi 26214396(104857584)
17/01/06 16:53:27 INFO mapred.MapTask: mapreduce.task.io.sort.mb: 100
17/01/06 16:53:27 INFO mapred.MapTask: soft limit at 83886080
17/01/06 16:53:27 INFO mapred.MapTask: bufstart = 0; bufvoid = 104857600
17/01/06 16:53:27 INFO mapred.MapTask: kvstart = 26214396; length = 6553600
17/01/06 16:53:27 INFO mapred.MapTask: Map output collector class = org.apache.hadoop.mapred.MapTask$MapOutputBuffer
17/01/06 16:53:27 INFO mapred.LocalJobRunner:
17/01/06 16:53:27 INFO mapred.MapTask: Starting flush of map output
17/01/06 16:53:27 INFO mapred.MapTask: Spilling map output
17/01/06 16:53:27 INFO mapred.MapTask: bufstart = 0; bufend = 65; bufvoid = 104857600
17/01/06 16:53:27 INFO mapred.MapTask: kvstart = 26214396(104857584); kvend = 26214372(104857488); length = 25/6553600
17/01/06 16:53:27 INFO mapred.MapTask: Finished spill 0
17/01/06 16:53:27 INFO mapred.Task: Task:attempt_local1147390429_0001_m_000001_0 is done. And is in the process of committing
17/01/06 16:53:27 INFO mapred.LocalJobRunner: map
17/01/06 16:53:27 INFO mapred.Task: Task 'attempt_local1147390429_0001_m_000001_0' done.
17/01/06 16:53:27 INFO mapred.LocalJobRunner: Finishing task: attempt_local1147390429_0001_m_000001_0
17/01/06 16:53:27 INFO mapred.LocalJobRunner: map task executor complete.
17/01/06 16:53:27 INFO mapred.LocalJobRunner: Waiting for reduce tasks
17/01/06 16:53:27 INFO mapred.LocalJobRunner: Starting task: attempt_local1147390429_0001_r_000000_0
17/01/06 16:53:27 INFO output.FileOutputCommitter: File Output Committer Algorithm version is 1
17/01/06 16:53:27 INFO mapred.Task:  Using ResourceCalculatorProcessTree : [ ]
17/01/06 16:53:27 INFO mapred.ReduceTask: Using ShuffleConsumerPlugin: org.apache.hadoop.mapreduce.task.reduce.Shuffle@2aa26fdb
17/01/06 16:53:27 INFO reduce.MergeManagerImpl: MergerManager: memoryLimit=363285696, maxSingleShuffleLimit=90821424, mergeThreshold=239768576, ioSortFactor=10, memToMemMergeOutputsThreshold=10
17/01/06 16:53:27 INFO reduce.EventFetcher: attempt_local1147390429_0001_r_000000_0 Thread started: EventFetcher for fetching Map Completion Events
17/01/06 16:53:27 INFO reduce.LocalFetcher: localfetcher#1 about to shuffle output of map attempt_local1147390429_0001_m_000000_0 decomp: 98 len: 102 to MEMORY
17/01/06 16:53:27 INFO reduce.InMemoryMapOutput: Read 98 bytes from map-output for attempt_local1147390429_0001_m_000000_0
17/01/06 16:53:27 INFO reduce.MergeManagerImpl: closeInMemoryFile -> map-output of size: 98, inMemoryMapOutputs.size() -> 1, commitMemory -> 0, usedMemory ->98
17/01/06 16:53:27 INFO reduce.LocalFetcher: localfetcher#1 about to shuffle output of map attempt_local1147390429_0001_m_000001_0 decomp: 68 len: 72 to MEMORY

17/01/06 16:53:27 WARN io.ReadaheadPool: Failed readahead on ifile
EBADF: Bad file descriptor
	at org.apache.hadoop.io.nativeio.NativeIO$POSIX.posix_fadvise(Native Method)
	at org.apache.hadoop.io.nativeio.NativeIO$POSIX.posixFadviseIfPossible(NativeIO.java:267)
	at org.apache.hadoop.io.nativeio.NativeIO$POSIX$CacheManipulator.posixFadviseIfPossible(NativeIO.java:146)
	at org.apache.hadoop.io.ReadaheadPool$ReadaheadRequestImpl.run(ReadaheadPool.java:206)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
	at java.lang.Thread.run(Thread.java:745)

17/01/06 16:53:27 INFO reduce.InMemoryMapOutput: Read 68 bytes from map-output for attempt_local1147390429_0001_m_000001_0
17/01/06 16:53:27 INFO reduce.MergeManagerImpl: closeInMemoryFile -> map-output of size: 68, inMemoryMapOutputs.size() -> 2, commitMemory -> 98, usedMemory ->166
17/01/06 16:53:27 INFO reduce.EventFetcher: EventFetcher is interrupted.. Returning

17/01/06 16:53:27 WARN io.ReadaheadPool: Failed readahead on ifile
EBADF: Bad file descriptor
	at org.apache.hadoop.io.nativeio.NativeIO$POSIX.posix_fadvise(Native Method)
	at org.apache.hadoop.io.nativeio.NativeIO$POSIX.posixFadviseIfPossible(NativeIO.java:267)
	at org.apache.hadoop.io.nativeio.NativeIO$POSIX$CacheManipulator.posixFadviseIfPossible(NativeIO.java:146)
	at org.apache.hadoop.io.ReadaheadPool$ReadaheadRequestImpl.run(ReadaheadPool.java:206)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
	at java.lang.Thread.run(Thread.java:745)

17/01/06 16:53:27 INFO mapred.LocalJobRunner: 2 / 2 copied.
17/01/06 16:53:27 INFO reduce.MergeManagerImpl: finalMerge called with 2 in-memory map-outputs and 0 on-disk map-outputs
17/01/06 16:53:27 INFO mapred.Merger: Merging 2 sorted segments
17/01/06 16:53:27 INFO mapred.Merger: Down to the last merge-pass, with 2 segments left of total size: 156 bytes
17/01/06 16:53:27 INFO reduce.MergeManagerImpl: Merged 2 segments, 166 bytes to disk to satisfy reduce memory limit
17/01/06 16:53:27 INFO reduce.MergeManagerImpl: Merging 1 files, 168 bytes from disk
17/01/06 16:53:27 INFO reduce.MergeManagerImpl: Merging 0 segments, 0 bytes from memory into reduce
17/01/06 16:53:27 INFO mapred.Merger: Merging 1 sorted segments
17/01/06 16:53:27 INFO mapred.Merger: Down to the last merge-pass, with 1 segments left of total size: 160 bytes
17/01/06 16:53:27 INFO mapred.LocalJobRunner: 2 / 2 copied.
17/01/06 16:53:27 INFO Configuration.deprecation: mapred.skip.on is deprecated. Instead, use mapreduce.job.skiprecords
17/01/06 16:53:27 INFO mapred.Task: Task:attempt_local1147390429_0001_r_000000_0 is done. And is in the process of committing
17/01/06 16:53:27 INFO mapred.LocalJobRunner: 2 / 2 copied.
17/01/06 16:53:27 INFO mapred.Task: Task attempt_local1147390429_0001_r_000000_0 is allowed to commit now
17/01/06 16:53:27 INFO output.FileOutputCommitter: Saved output of task 'attempt_local1147390429_0001_r_000000_0' to file:/home/jungle/hadoop/hadoop-local/dataLocal/outout/_temporary/0/task_local1147390429_0001_r_000000
17/01/06 16:53:27 INFO mapred.LocalJobRunner: reduce > reduce
17/01/06 16:53:27 INFO mapred.Task: Task 'attempt_local1147390429_0001_r_000000_0' done.
17/01/06 16:53:27 INFO mapred.LocalJobRunner: Finishing task: attempt_local1147390429_0001_r_000000_0
17/01/06 16:53:27 INFO mapred.LocalJobRunner: reduce task executor complete.
17/01/06 16:53:28 INFO mapreduce.Job: Job job_local1147390429_0001 running in uber mode : false
17/01/06 16:53:28 INFO mapreduce.Job:  map 100% reduce 100%
17/01/06 16:53:28 INFO mapreduce.Job: Job job_local1147390429_0001 completed successfully
17/01/06 16:53:28 INFO mapreduce.Job: Counters: 30
	File System Counters
		FILE: Number of bytes read=889648
		FILE: Number of bytes written=1748828
		FILE: Number of read operations=0
		FILE: Number of large read operations=0
		FILE: Number of write operations=0
	Map-Reduce Framework
		Map input records=3
		Map output records=18
		Map output bytes=179
		Map output materialized bytes=174
		Input split bytes=256
		Combine input records=18
		Combine output records=14
		Reduce input groups=11
		Reduce shuffle bytes=174
		Reduce input records=14
		Reduce output records=11
		Spilled Records=28
		Shuffled Maps =2
		Failed Shuffles=0
		Merged Map outputs=2
		GC time elapsed (ms)=43
		Total committed heap usage (bytes)=457912320
	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=107
	File Output Format Counters
		Bytes Written=94

EBADF: Bad file descriptor。这两个错误，从网上看可以忽略。