搭建Hadoop2.5.2+Eclipse开发调试环境
一、简介
为了开发调试方便，本文介绍在Eclipse下搭建开发环境，连接和提交任务到Hadoop集群。
二、安装前准备：
1）Eclipse：Luna 4.4.1
2）eclipse插件：hadoop-eclipse-plugin-2.5.2.jar
3）hadoop版本：hadoop-2.5.2.tar.gz
三、环境搭建
1.安装eclipse
2.安装插件
将插件hadoop-eclipse-plugin-2.5.2.jar，下载后放到eclipse/plugins目录即可
3.配置hadoop主目录
解压缩hadoop-2.5.2.tar.gz到D:\Tools\hadoop\hadoop-2.6.0，在eclipse的Windows->Preferences的Hadoop Map/Reduce中设置安装目录。
4.配置插件
打开Windows->Open Perspective中的Map/Reduce，在此perspective下进行hadoop程序开发。
打开Windows->Show View中的Map/Reduce Locations，如下图右键选择New Hadoop location…新建hadoop连接。
确认完成以后如下，eclipse会连接hadoop集群。
如果连接成功，在project explorer的DFS Locations下会展现hdfs集群中的文件。
如果连接失败，先去将linux下的hadoop集群启动起来，再重新连接即可！
四、开发调试
1 程序开发
开发一个Sort示例，对输入整数进行排序。输入文件格式是每行一个整数。
1 package com.ccb;
2
3 /**
4 * Created by hp on 2015-7-20.
5 */
6
7 import java.io.IOException;
8
9 import org.apache.hadoop.conf.Configuration;
10 import org.apache.hadoop.fs.FileSystem;
11 import org.apache.hadoop.fs.Path;
12 import org.apache.hadoop.io.IntWritable;
13 import org.apache.hadoop.io.Text;
14 import org.apache.hadoop.mapreduce.Job;
15 import org.apache.hadoop.mapreduce.Mapper;
16 import org.apache.hadoop.mapreduce.Reducer;
17 import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
18 import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
19
20 public class Sort {
21
22 // 每行记录是一个整数。将Text文本转换为IntWritable类型，作为map的key
23 public static class Map extends Mapper<Object, Text, IntWritable, IntWritable> {
24 private static IntWritable data = new IntWritable();
25
26 // 实现map函数
27 public void map(Object key, Text value, Context context) throws IOException, InterruptedException {
28 String line = value.toString();
29 data.set(Integer.parseInt(line));
30 context.write(data, new IntWritable(1));
31 }
32 }
33
34 // reduce之前hadoop框架会进行shuffle和排序，因此直接输出key即可。
35 public static class Reduce extends Reducer<IntWritable, IntWritable, IntWritable, Text> {
36
37 //实现reduce函数
38 public void reduce(IntWritable key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
39 for (IntWritable v : values) {
40 context.write(key, new Text(""));
41 }
42 }
43 }
44
45 public static void main(String[] args) throws Exception {
46 Configuration conf = new Configuration();
47
48 // 指定JobTracker地址
49 conf.set("mapred.job.tracker", "192.168.62.129:9001");
50 if (args.length != 2) {
51 System.err.println("Usage: Data Sort <in> <out>");
52 System.exit(2);
53 }
54 System.out.println(args[0]);
55 System.out.println(args[1]);
56
57 Job job = Job.getInstance(conf, "Data Sort");
58 job.setJarByClass(Sort.class);
59
60 //设置Map和Reduce处理类
61 job.setMapperClass(Map.class);
62 job.setReducerClass(Reduce.class);
63
64 //设置输出类型
65 job.setOutputKeyClass(IntWritable.class);
66 job.setOutputValueClass(IntWritable.class);
67
68 //设置输入和输出目录
69 FileInputFormat.addInputPath(job, new Path(args[0]));
70 FileOutputFormat.setOutputPath(job, new Path(args[1]));
71 System.exit(job.waitForCompletion(true) ? 0 : 1);
72 }
73 }
2 配置文件
把log4j.properties和hadoop集群中的core-site.xml加入到classpath中。我的示例工程是maven组织，因此放到src/main/resources目录。
程序执行时会从core-site.xml中获取hdfs地址。
3 程序执行
右键选择Run As -> Run Configurations…，在参数中填好输入输出目录，执行Run即可。
执行日志：
1 hdfs://192.168.62.129:9000/user/vm/sort_in
2 hdfs://192.168.62.129:9000/user/vm/sort_out
3 15/07/27 16:21:36 INFO Configuration.deprecation: session.id is deprecated. Instead, use dfs.metrics.session-id
4 15/07/27 16:21:36 INFO jvm.JvmMetrics: Initializing JVM Metrics with processName=JobTracker, sessionId=
5 15/07/27 16:21:36 WARN mapreduce.JobSubmitter: Hadoop command-line option parsing not performed. Implement the Tool interface and execute your application with ToolRunner to remedy this.
6 15/07/27 16:21:36 WARN mapreduce.JobSubmitter: No job jar file set. User classes may not be found. See Job or Job#setJar(String).
7 15/07/27 16:21:36 INFO input.FileInputFormat: Total input paths to process : 3
8 15/07/27 16:21:36 INFO mapreduce.JobSubmitter: number of splits:3
9 15/07/27 16:21:36 INFO Configuration.deprecation: mapred.job.tracker is deprecated. Instead, use mapreduce.jobtracker.address
10 15/07/27 16:21:37 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_local1592166400_0001
11 15/07/27 16:21:37 INFO mapreduce.Job: The url to track the job: http://localhost:8080/
12 15/07/27 16:21:37 INFO mapreduce.Job: Running job: job_local1592166400_0001
13 15/07/27 16:21:37 INFO mapred.LocalJobRunner: OutputCommitter set in config null
14 15/07/27 16:21:37 INFO mapred.LocalJobRunner: OutputCommitter is org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter
15 15/07/27 16:21:37 INFO mapred.LocalJobRunner: Waiting for map tasks
16 15/07/27 16:21:37 INFO mapred.LocalJobRunner: Starting task: attempt_local1592166400_0001_m_000000_0
17 15/07/27 16:21:37 INFO util.ProcfsBasedProcessTree: ProcfsBasedProcessTree currently is supported only on Linux.
18 15/07/27 16:21:37 INFO mapred.Task: Using ResourceCalculatorProcessTree : org.apache.hadoop.yarn.util.WindowsBasedProcessTree@4c90dbc4
19 15/07/27 16:21:37 INFO mapred.MapTask: Processing split: hdfs://192.168.62.129:9000/user/vm/sort_in/file1:0+25
20 15/07/27 16:21:37 INFO mapred.MapTask: (EQUATOR) 0 kvi 26214396(104857584)
21 15/07/27 16:21:37 INFO mapred.MapTask: mapreduce.task.io.sort.mb: 100
22 15/07/27 16:21:37 INFO mapred.MapTask: soft limit at 83886080
23 15/07/27 16:21:37 INFO mapred.MapTask: bufstart = 0; bufvoid = 104857600
24 15/07/27 16:21:37 INFO mapred.MapTask: kvstart = 26214396; length = 6553600
25 15/07/27 16:21:37 INFO mapred.MapTask: Map output collector class = org.apache.hadoop.mapred.MapTask$MapOutputBuffer
26 15/07/27 16:21:38 INFO mapred.LocalJobRunner:
27 15/07/27 16:21:38 INFO mapred.MapTask: Starting flush of map output
28 15/07/27 16:21:38 INFO mapred.MapTask: Spilling map output
29 15/07/27 16:21:38 INFO mapred.MapTask: bufstart = 0; bufend = 56; bufvoid = 104857600
30 15/07/27 16:21:38 INFO mapred.MapTask: kvstart = 26214396(104857584); kvend = 26214372(104857488); length = 25/6553600
31 15/07/27 16:21:38 INFO mapred.MapTask: Finished spill 0
32 15/07/27 16:21:38 INFO mapred.Task: Task:attempt_local1592166400_0001_m_000000_0 is done. And is in the process of committing
33 15/07/27 16:21:38 INFO mapred.LocalJobRunner: map
34 15/07/27 16:21:38 INFO mapred.Task: Task 'attempt_local1592166400_0001_m_000000_0' done.
35 15/07/27 16:21:38 INFO mapred.LocalJobRunner: Finishing task: attempt_local1592166400_0001_m_000000_0
36 15/07/27 16:21:38 INFO mapred.LocalJobRunner: Starting task: attempt_local1592166400_0001_m_000001_0
37 15/07/27 16:21:38 INFO util.ProcfsBasedProcessTree: ProcfsBasedProcessTree currently is supported only on Linux.
38 15/07/27 16:21:38 INFO mapred.Task: Using ResourceCalculatorProcessTree : org.apache.hadoop.yarn.util.WindowsBasedProcessTree@69e4d7d
39 15/07/27 16:21:38 INFO mapred.MapTask: Processing split: hdfs://192.168.62.129:9000/user/vm/sort_in/file2:0+15
40 15/07/27 16:21:38 INFO mapred.MapTask: (EQUATOR) 0 kvi 26214396(104857584)
41 15/07/27 16:21:38 INFO mapred.MapTask: mapreduce.task.io.sort.mb: 100
42 15/07/27 16:21:38 INFO mapred.MapTask: soft limit at 83886080
43 15/07/27 16:21:38 INFO mapred.MapTask: bufstart = 0; bufvoid = 104857600
44 15/07/27 16:21:38 INFO mapred.MapTask: kvstart = 26214396; length = 6553600
45 15/07/27 16:21:38 INFO mapred.MapTask: Map output collector class = org.apache.hadoop.mapred.MapTask$MapOutputBuffer
46 15/07/27 16:21:38 INFO mapred.LocalJobRunner:
47 15/07/27 16:21:38 INFO mapred.MapTask: Starting flush of map output
48 15/07/27 16:21:38 INFO mapred.MapTask: Spilling map output
49 15/07/27 16:21:38 INFO mapred.MapTask: bufstart = 0; bufend = 32; bufvoid = 104857600
50 15/07/27 16:21:38 INFO mapred.MapTask: kvstart = 26214396(104857584); kvend = 26214384(104857536); length = 13/6553600
51 15/07/27 16:21:38 INFO mapred.MapTask: Finished spill 0
52 15/07/27 16:21:38 INFO mapred.Task: Task:attempt_local1592166400_0001_m_000001_0 is done. And is in the process of committing
53 15/07/27 16:21:38 INFO mapred.LocalJobRunner: map
54 15/07/27 16:21:38 INFO mapred.Task: Task 'attempt_local1592166400_0001_m_000001_0' done.
55 15/07/27 16:21:38 INFO mapred.LocalJobRunner: Finishing task: attempt_local1592166400_0001_m_000001_0
56 15/07/27 16:21:38 INFO mapred.LocalJobRunner: Starting task: attempt_local1592166400_0001_m_000002_0
57 15/07/27 16:21:38 INFO mapreduce.Job: Job job_local1592166400_0001 running in uber mode : false
58 15/07/27 16:21:38 INFO util.ProcfsBasedProcessTree: ProcfsBasedProcessTree currently is supported only on Linux.
59 15/07/27 16:21:38 INFO mapreduce.Job: map 100% reduce 0%
60 15/07/27 16:21:38 INFO mapred.Task: Using ResourceCalculatorProcessTree : org.apache.hadoop.yarn.util.WindowsBasedProcessTree@4e931efa
61 15/07/27 16:21:38 INFO mapred.MapTask: Processing split: hdfs://192.168.62.129:9000/user/vm/sort_in/file3:0+8
62 15/07/27 16:21:39 INFO mapred.MapTask: (EQUATOR) 0 kvi 26214396(104857584)
63 15/07/27 16:21:39 INFO mapred.MapTask: mapreduce.task.io.sort.mb: 100
64 15/07/27 16:21:39 INFO mapred.MapTask: soft limit at 83886080
65 15/07/27 16:21:39 INFO mapred.MapTask: bufstart = 0; bufvoid = 104857600
66 15/07/27 16:21:39 INFO mapred.MapTask: kvstart = 26214396; length = 6553600
67 15/07/27 16:21:39 INFO mapred.MapTask: Map output collector class = org.apache.hadoop.mapred.MapTask$MapOutputBuffer
68 15/07/27 16:21:39 INFO mapred.LocalJobRunner:
69 15/07/27 16:21:39 INFO mapred.MapTask: Starting flush of map output
70 15/07/27 16:21:39 INFO mapred.MapTask: Spilling map output
71 15/07/27 16:21:39 INFO mapred.MapTask: bufstart = 0; bufend = 24; bufvoid = 104857600
72 15/07/27 16:21:39 INFO mapred.MapTask: kvstart = 26214396(104857584); kvend = 26214388(104857552); length = 9/6553600
73 15/07/27 16:21:39 INFO mapred.MapTask: Finished spill 0
74 15/07/27 16:21:39 INFO mapred.Task: Task:attempt_local1592166400_0001_m_000002_0 is done. And is in the process of committing
75 15/07/27 16:21:39 INFO mapred.LocalJobRunner: map
76 15/07/27 16:21:39 INFO mapred.Task: Task 'attempt_local1592166400_0001_m_000002_0' done.
77 15/07/27 16:21:39 INFO mapred.LocalJobRunner: Finishing task: attempt_local1592166400_0001_m_000002_0
78 15/07/27 16:21:39 INFO mapred.LocalJobRunner: map task executor complete.
79 15/07/27 16:21:39 INFO mapred.LocalJobRunner: Waiting for reduce tasks
80 15/07/27 16:21:39 INFO mapred.LocalJobRunner: Starting task: attempt_local1592166400_0001_r_000000_0
81 15/07/27 16:21:39 INFO util.ProcfsBasedProcessTree: ProcfsBasedProcessTree currently is supported only on Linux.
82 15/07/27 16:21:39 INFO mapred.Task: Using ResourceCalculatorProcessTree : org.apache.hadoop.yarn.util.WindowsBasedProcessTree@49250068
83 15/07/27 16:21:39 INFO mapred.ReduceTask: Using ShuffleConsumerPlugin: org.apache.hadoop.mapreduce.task.reduce.Shuffle@2129404b
84 15/07/27 16:21:39 INFO reduce.MergeManagerImpl: MergerManager: memoryLimit=652528832, maxSingleShuffleLimit=163132208, mergeThreshold=430669056, ioSortFactor=10, memToMemMergeOutputsThreshold=10
85 15/07/27 16:21:39 INFO reduce.EventFetcher: attempt_local1592166400_0001_r_000000_0 Thread started: EventFetcher for fetching Map Completion Events
86 15/07/27 16:21:40 INFO reduce.LocalFetcher: localfetcher#1 about to shuffle output of map attempt_local1592166400_0001_m_000002_0 decomp: 32 len: 36 to MEMORY
87 15/07/27 16:21:40 INFO reduce.InMemoryMapOutput: Read 32 bytes from map-output for attempt_local1592166400_0001_m_000002_0
88 15/07/27 16:21:40 INFO reduce.MergeManagerImpl: closeInMemoryFile -> map-output of size: 32, inMemoryMapOutputs.size() -> 1, commitMemory -> 0, usedMemory ->32
89 15/07/27 16:21:40 INFO reduce.LocalFetcher: localfetcher#1 about to shuffle output of map attempt_local1592166400_0001_m_000000_0 decomp: 72 len: 76 to MEMORY
90 15/07/27 16:21:40 INFO reduce.InMemoryMapOutput: Read 72 bytes from map-output for attempt_local1592166400_0001_m_000000_0
91 15/07/27 16:21:40 INFO reduce.MergeManagerImpl: closeInMemoryFile -> map-output of size: 72, inMemoryMapOutputs.size() -> 2, commitMemory -> 32, usedMemory ->104
92 15/07/27 16:21:40 INFO reduce.LocalFetcher: localfetcher#1 about to shuffle output of map attempt_local1592166400_0001_m_000001_0 decomp: 42 len: 46 to MEMORY
93 15/07/27 16:21:40 INFO reduce.InMemoryMapOutput: Read 42 bytes from map-output for attempt_local1592166400_0001_m_000001_0
94 15/07/27 16:21:40 INFO reduce.MergeManagerImpl: closeInMemoryFile -> map-output of size: 42, inMemoryMapOutputs.size() -> 3, commitMemory -> 104, usedMemory ->146
95 15/07/27 16:21:40 INFO reduce.EventFetcher: EventFetcher is interrupted.. Returning
96 15/07/27 16:21:40 INFO mapred.LocalJobRunner: 3 / 3 copied.
97 15/07/27 16:21:40 INFO reduce.MergeManagerImpl: finalMerge called with 3 in-memory map-outputs and 0 on-disk map-outputs
98 15/07/27 16:21:40 INFO mapred.Merger: Merging 3 sorted segments
99 15/07/27 16:21:40 INFO mapred.Merger: Down to the last merge-pass, with 3 segments left of total size: 128 bytes
100 15/07/27 16:21:40 INFO reduce.MergeManagerImpl: Merged 3 segments, 146 bytes to disk to satisfy reduce memory limit
101 15/07/27 16:21:40 INFO reduce.MergeManagerImpl: Merging 1 files, 146 bytes from disk
102 15/07/27 16:21:40 INFO reduce.MergeManagerImpl: Merging 0 segments, 0 bytes from memory into reduce
103 15/07/27 16:21:40 INFO mapred.Merger: Merging 1 sorted segments
104 15/07/27 16:21:40 INFO mapred.Merger: Down to the last merge-pass, with 1 segments left of total size: 136 bytes
105 15/07/27 16:21:40 INFO mapred.LocalJobRunner: 3 / 3 copied.
106 15/07/27 16:21:40 INFO Configuration.deprecation: mapred.skip.on is deprecated. Instead, use mapreduce.job.skiprecords
107 15/07/27 16:21:40 INFO mapred.Task: Task:attempt_local1592166400_0001_r_000000_0 is done. And is in the process of committing
108 15/07/27 16:21:40 INFO mapred.LocalJobRunner: 3 / 3 copied.
109 15/07/27 16:21:40 INFO mapred.Task: Task attempt_local1592166400_0001_r_000000_0 is allowed to commit now
110 15/07/27 16:21:40 INFO output.FileOutputCommitter: Saved output of task 'attempt_local1592166400_0001_r_000000_0' to hdfs://192.168.62.129:9000/user/vm/sort_out/_temporary/0/task_local1592166400_0001_r_000000
111 15/07/27 16:21:40 INFO mapred.LocalJobRunner: reduce > reduce
112 15/07/27 16:21:40 INFO mapred.Task: Task 'attempt_local1592166400_0001_r_000000_0' done.
113 15/07/27 16:21:40 INFO mapred.LocalJobRunner: Finishing task: attempt_local1592166400_0001_r_000000_0
114 15/07/27 16:21:40 INFO mapred.LocalJobRunner: reduce task executor complete.
115 15/07/27 16:21:40 INFO mapreduce.Job: map 100% reduce 100%
116 15/07/27 16:21:41 INFO mapreduce.Job: Job job_local1592166400_0001 completed successfully
117 15/07/27 16:21:41 INFO mapreduce.Job: Counters: 38
118 File System Counters
119 FILE: Number of bytes read=3834
120 FILE: Number of bytes written=1017600
121 FILE: Number of read operations=0
122 FILE: Number of large read operations=0
123 FILE: Number of write operations=0
124 HDFS: Number of bytes read=161
125 HDFS: Number of bytes written=62
126 HDFS: Number of read operations=41
127 HDFS: Number of large read operations=0
128 HDFS: Number of write operations=10
129 Map-Reduce Framework
130 Map input records=14
131 Map output records=14
132 Map output bytes=112
133 Map output materialized bytes=158
134 Input split bytes=339
135 Combine input records=0
136 Combine output records=0
137 Reduce input groups=13
138 Reduce shuffle bytes=158
139 Reduce input records=14
140 Reduce output records=14
141 Spilled Records=28
142 Shuffled Maps =3
143 Failed Shuffles=0
144 Merged Map outputs=3
145 GC time elapsed (ms)=10
146 CPU time spent (ms)=0
147 Physical memory (bytes) snapshot=0
148 Virtual memory (bytes) snapshot=0
149 Total committed heap usage (bytes)=1420296192
150 Shuffle Errors
151 BAD_ID=0
152 CONNECTION=0
153 IO_ERROR=0
154 WRONG_LENGTH=0
155 WRONG_MAP=0
156 WRONG_REDUCE=0
157 File Input Format Counters
158 Bytes Read=48
159 File Output Format Counters
160 Bytes Written=62
4. 可能出现的问题
4.1 权限问题，无法访问HDFS
修改集群hdfs-site.xml配置，关闭hadoop集群的权限校验。
|
<property> <name>dfs.permissions</name> <value>false</value> </property> |
4.2 出现NullPointerException异常
在环境变量中配置%HADOOP_HOME%为C:\Download\hadoop-2.6.0\
下载winutils.exe和hadoop.dll到C:\Download\hadoop-2.6.0\bin
注意：网上很多资料说的是下载hadoop-common-2.2.0-bin-master.zip，但很多不支持hadoop2.6.0版本。需要下载支持hadoop2.6.0版本的程序。
4.3 程序执行失败
需要执行Run on Hadoop，而不是Java Application。
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