前一段时间，在上一篇博文中描述了自己抽时间在构建的完全分布式Hadoop环境过程中遇到的一些问题以及构建成功后，通过Eclipse操作HDFS的时候遇到的一些问题，最近又想进一步学习学习Hadoop操作Mysql数据库的一些知识，在这里网上存在很多分歧，很多人可能会笑话，用那么“笨重”的Hadoop来操作数据库，脑子有问题吧，Hadoop的HDFS优势在于处理分布式文件系统，这种说法没有任何错误，数据库的操作讲究“安全、轻便、快捷”，用Hadoop操作完全是不符合常理啊，那为啥还要学习这个东西呢？其实退一步讲，在之前access数据库的应用占一定份额的时候，很多人选择使用文件作为数据的仓储，增删查改全部是操作文件，一个文件可能就是一个数据库或者一个数据表，那么对于一些实时性要求不是很高且数据量比较小的操作，选择用hadoop操作数据库，其实说来也不是不可以考录，不说了，每个人有自己的观点，当然这个也与每个人所在的公司的要求有关系，下面就说说自己遇到的比较恼人的一个问题：还是classNotFound的问题：
首先要说明的是：你的运行环境，先的明白你的代码到底是在服务器端还是在本地,其次再参考不同的代码进行模拟。
参考文章：http://www.cnblogs.com/xia520pi/archive/2012/06/12/2546261.html项目的简单结构:
下面说说本地运行的时候3种classNotFount的问题
（1）MySql的驱动找不到，这个很容易解决，在自己的项目中引入MySql的官方驱动jar包就可以解决了，如上图红色框
（2)对JDBC的Jar包处理
因为程序虽然用Eclipse编译运行但最终要提交到Hadoop集群上，所以JDBC的jar必须放到Hadoop集群中。有两种方式：
<1>在每个节点下的${HADOOP_HOME}/lib下添加该包，重启集群，一般是比较原始的方法。
我们的Hadoop安装包在"/usr/hadoop"，所以把Jar放到"/usr/hadoop/lib"下面，然后重启，记得是Hadoop集群中所有的节点都要放，因为执行分布式是程序是在每个节点本地机器上进行。
<2>在Hadoop集群的分布式文件系统中创建"/lib"文件夹，并把我们的的JDBC的jar包上传上去，然后在主程序添加如下语句，就能保证 Hadoop集群中所有的节点都能使用这个jar包。因为这个jar包放在了HDFS上，而不是本地系统，这个要理解清楚。
(3)关联数据库表的实体类找不到（本篇文章解决的重点），StudentRecord.class not found。。。。
出现此问题的源代码如下：
1 package cn.hadoop.db;
2
3 import java.io.DataInput;
4 import java.io.DataOutput;
5 import java.io.IOException;
6 import java.net.URI;
7 import java.sql.PreparedStatement;
8 import java.sql.ResultSet;
9 import java.sql.SQLException;
10
11 import org.apache.hadoop.filecache.DistributedCache;
12 import org.apache.hadoop.fs.FileSystem;
13 import org.apache.hadoop.fs.Path;
14 import org.apache.hadoop.io.LongWritable;
15 import org.apache.hadoop.io.Text;
16 import org.apache.hadoop.io.Writable;
17 import org.apache.hadoop.mapred.FileOutputFormat;
18 import org.apache.hadoop.mapred.JobClient;
19 import org.apache.hadoop.mapred.JobConf;
20 import org.apache.hadoop.mapred.MapReduceBase;
21 import org.apache.hadoop.mapred.Mapper;
22 import org.apache.hadoop.mapred.OutputCollector;
23 import org.apache.hadoop.mapred.Reporter;
24 import org.apache.hadoop.mapred.lib.IdentityReducer;
25 import org.apache.hadoop.mapred.lib.db.DBConfiguration;
26 import org.apache.hadoop.mapred.lib.db.DBInputFormat;
27 import org.apache.hadoop.mapred.lib.db.DBWritable;
28
29 import cn.hadoop.db.DBAccessReader.Student.DBInputMapper;
30
31 public class DBAccessReader {
32
33 public static class Student implements Writable, DBWritable{
34 public int id;
35 public String name;
36 public String sex;
37 public int age;
38
39 public Student() {
40
41 }
42 @Override
43 public void write(PreparedStatement statement) throws SQLException {
44 statement.setInt(1, this.id);
45 statement.setString(2, this.name);
46 statement.setString(3, this.sex);
47 statement.setInt(4, this.age);
48 }
49
50 @Override
51 public void readFields(ResultSet resultSet) throws SQLException {
52 this.id = resultSet.getInt(1);
53 this.name = resultSet.getString(2);
54 this.sex = resultSet.getString(3);
55 this.age = resultSet.getInt(4);
56 }
57
58 @Override
59 public void write(DataOutput out) throws IOException {
60 out.writeInt(this.id);
61 Text.writeString(out, this.name);
62 Text.writeString(out, this.sex);
63 out.writeInt(this.age);
64 }
65
66 @Override
67 public void readFields(DataInput in) throws IOException {
68 this.id = in.readInt();
69 this.name = Text.readString(in);
70 this.sex = Text.readString(in);
71 this.age = in.readInt();
72 }
73
74 @Override
75 public String toString() {
76 return new String("Student [id=" + id + ", name=" + name + ", sex=" + sex
77 + ", age=" + age + "]");
78 }
79
80 public static class DBInputMapper extends MapReduceBase implements Mapper<LongWritable, cn.hadoop.db.DBAccessReader.Student, LongWritable, Text>{
81
82 @Override
83 public void map(LongWritable key, cn.hadoop.db.DBAccessReader.Student value,
84 OutputCollector<LongWritable, Text> collector,
85 Reporter reporter) throws IOException {
86 collector.collect(new LongWritable(value.id), new Text(value.toString()));
87
88 }
89
90 }
91
92
93
94 }
95 public static void main(String[] args) throws IOException{
96
97 JobConf conf = new JobConf(DBAccessReader.class);
98 conf.set("mapred.job.tracker", "192.168.56.10:9001");
99
100 FileSystem fileSystem = FileSystem.get(
101 URI.create("hdfs://192.168.56.10:9000/"), conf);
102
103 DistributedCache
104 .addFileToClassPath(
105 new Path(
106 "hdfs://192.168.56.10:9000/lib/mysql-connector-java-5.1.18-bin.jar"),
107 conf, fileSystem);
108 conf.setOutputKeyClass(LongWritable.class);
109 conf.setOutputValueClass(Text.class);
110
111 conf.setInputFormat(DBInputFormat.class);
112
113
114
115 FileOutputFormat.setOutputPath(conf, new Path(
116 "hdfs://192.168.56.10:9000/user/studentInfo"));
117
118 DBConfiguration.configureDB(conf, "com.mysql.jdbc.Driver",
119 "jdbc:mysql://192.168.56.109:3306/school", "root", "1qaz2wsx");
120
121 String[] fields = { "id", "name", "sex", "age" };
122
123 DBInputFormat.setInput(conf, cn.hadoop.db.DBAccessReader.Student.class, "student", null,
124 "id", fields);
125
126 conf.setMapperClass(DBInputMapper.class);
127 conf.setReducerClass(IdentityReducer.class);
128
129 JobClient.runJob(conf);
130 }
131 }
运行的时候，报的错误如下：
错误很明显，就是找不到实体类Student,可是看代码好多遍，这个类明明在啊，为啥会报错找不到呢？？？我也迷糊了很长时间，各种尝试都是不行，最后还是将目标锁定在日志信息里面，很明显，这是在服务器端去找DBAccessReader这个Job的jar，明显我们没有上传，肯定是找不到到，所以报错，错误很明显，就在main方法下面的这里：
1 JobConf conf = new JobConf(DBAccessReader.class);
2 conf.set("mapred.job.tracker", "192.168.56.10:9001");
所以，修改代码如下以后，问题得到解决：
1 package cn.hadoop.db;
2
3 import java.io.DataInput;
4 import java.io.DataOutput;
5 import java.io.IOException;
6 import java.net.URI;
7 import java.sql.PreparedStatement;
8 import java.sql.ResultSet;
9 import java.sql.SQLException;
10
11 import org.apache.hadoop.filecache.DistributedCache;
12 import org.apache.hadoop.fs.FileSystem;
13 import org.apache.hadoop.fs.Path;
14 import org.apache.hadoop.io.LongWritable;
15 import org.apache.hadoop.io.Text;
16 import org.apache.hadoop.io.Writable;
17 import org.apache.hadoop.mapred.FileOutputFormat;
18 import org.apache.hadoop.mapred.JobClient;
19 import org.apache.hadoop.mapred.JobConf;
20 import org.apache.hadoop.mapred.MapReduceBase;
21 import org.apache.hadoop.mapred.Mapper;
22 import org.apache.hadoop.mapred.OutputCollector;
23 import org.apache.hadoop.mapred.Reporter;
24 import org.apache.hadoop.mapred.lib.IdentityReducer;
25 import org.apache.hadoop.mapred.lib.db.DBConfiguration;
26 import org.apache.hadoop.mapred.lib.db.DBInputFormat;
27 import org.apache.hadoop.mapred.lib.db.DBWritable;
28
29 import cn.hadoop.db.DBAccessReader.Student.DBInputMapper;
30
31 public class DBAccessReader {
32
33 public static class Student implements Writable, DBWritable {
34 public int id;
35 public String name;
36 public String sex;
37 public int age;
38
39 public Student() {
40
41 }
42
43 @Override
44 public void write(PreparedStatement statement) throws SQLException {
45 statement.setInt(1, this.id);
46 statement.setString(2, this.name);
47 statement.setString(3, this.sex);
48 statement.setInt(4, this.age);
49 }
50
51 @Override
52 public void readFields(ResultSet resultSet) throws SQLException {
53 this.id = resultSet.getInt(1);
54 this.name = resultSet.getString(2);
55 this.sex = resultSet.getString(3);
56 this.age = resultSet.getInt(4);
57 }
58
59 @Override
60 public void write(DataOutput out) throws IOException {
61 out.writeInt(this.id);
62 Text.writeString(out, this.name);
63 Text.writeString(out, this.sex);
64 out.writeInt(this.age);
65 }
66
67 @Override
68 public void readFields(DataInput in) throws IOException {
69 this.id = in.readInt();
70 this.name = Text.readString(in);
71 this.sex = Text.readString(in);
72 this.age = in.readInt();
73 }
74
75 @Override
76 public String toString() {
77 return new String("Student [id=" + id + ", name=" + name + ", sex="
78 + sex + ", age=" + age + "]");
79 }
80
81 public static class DBInputMapper extends MapReduceBase
82 implements
83 Mapper<LongWritable, cn.hadoop.db.DBAccessReader.Student, LongWritable, Text> {
84
85 @Override
86 public void map(LongWritable key,
87 cn.hadoop.db.DBAccessReader.Student value,
88 OutputCollector<LongWritable, Text> collector,
89 Reporter reporter) throws IOException {
90 collector.collect(new LongWritable(value.id),
91 new Text(value.toString()));
92
93 }
94
95 }
96
97 }
98
99 public static void main(String[] args) throws IOException {
100
101 JobConf conf = new JobConf();
102 FileSystem fileSystem = FileSystem.get(
103 URI.create("hdfs://192.168.56.10:9000/"), conf);
104
105 DistributedCache
106 .addFileToClassPath(
107 new Path(
108 "hdfs://192.168.56.10:9000/lib/mysql-connector-java-5.1.18-bin.jar"),
109 conf, fileSystem);
110 conf.setOutputKeyClass(LongWritable.class);
111 conf.setOutputValueClass(Text.class);
112
113 conf.setInputFormat(DBInputFormat.class);
114
115 FileOutputFormat.setOutputPath(conf, new Path(
116 "hdfs://192.168.56.10:9000/user/studentInfo"));
117
118 DBConfiguration.configureDB(conf, "com.mysql.jdbc.Driver",
119 "jdbc:mysql://192.168.56.109:3306/school", "root", "1qaz2wsx");
120
121 String[] fields = { "id", "name", "sex", "age" };
122
123 DBInputFormat.setInput(conf, cn.hadoop.db.DBAccessReader.Student.class,
124 "student", null, "id", fields);
125
126 conf.setMapperClass(DBInputMapper.class);
127 conf.setReducerClass(IdentityReducer.class);
128
129 JobClient.runJob(conf);
130 }
131 }
以下是运行时打印出的日志信息：
三月 13, 2016 5:39:57 下午 org.apache.hadoop.util.NativeCodeLoader <clinit> 警告: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable 三月 13, 2016 5:39:57 下午 org.apache.hadoop.mapred.JobClient copyAndConfigureFiles 警告: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same. 三月 13, 2016 5:39:57 下午 org.apache.hadoop.mapred.JobClient copyAndConfigureFiles 警告: No job jar file set. User classes may not be found. See JobConf(Class) or JobConf#setJar(String). 三月 13, 2016 5:39:57 下午 org.apache.hadoop.filecache.TrackerDistributedCacheManager downloadCacheObject 信息: Creating mysql-connector-java-5.1.18-bin.jar in /tmp/hadoop-hadoop/mapred/local/archive/2605709384407216388_-2048973133_91096108/192.168.56.10/lib-work-2076365714246383853 with rwxr-xr-x 三月 13, 2016 5:39:58 下午 org.apache.hadoop.filecache.TrackerDistributedCacheManager downloadCacheObject 信息: Cached hdfs://192.168.56.10:9000/lib/mysql-connector-java-5.1.18-bin.jar as /tmp/hadoop-hadoop/mapred/local/archive/2605709384407216388_-2048973133_91096108/192.168.56.10/lib/mysql-connector-java-5.1.18-bin.jar 三月 13, 2016 5:39:58 下午 org.apache.hadoop.filecache.TrackerDistributedCacheManager localizePublicCacheObject 信息: Cached hdfs://192.168.56.10:9000/lib/mysql-connector-java-5.1.18-bin.jar as /tmp/hadoop-hadoop/mapred/local/archive/2605709384407216388_-2048973133_91096108/192.168.56.10/lib/mysql-connector-java-5.1.18-bin.jar 三月 13, 2016 5:39:58 下午 org.apache.hadoop.mapred.JobClient monitorAndPrintJob 信息: Running job: job_local_0001 三月 13, 2016 5:39:59 下午 org.apache.hadoop.mapred.Task initialize 信息: Using ResourceCalculatorPlugin : null 三月 13, 2016 5:39:59 下午 org.apache.hadoop.mapred.MapTask runOldMapper 信息: numReduceTasks: 1 三月 13, 2016 5:39:59 下午 org.apache.hadoop.mapred.MapTask$MapOutputBuffer <init> 信息: io.sort.mb = 100 三月 13, 2016 5:39:59 下午 org.apache.hadoop.mapred.MapTask$MapOutputBuffer <init> 信息: data buffer = 79691776/99614720 三月 13, 2016 5:39:59 下午 org.apache.hadoop.mapred.MapTask$MapOutputBuffer <init> 信息: record buffer = 262144/327680 三月 13, 2016 5:39:59 下午 org.apache.hadoop.mapred.JobClient monitorAndPrintJob 信息: map 0% reduce 0% 三月 13, 2016 5:40:04 下午 org.apache.hadoop.mapred.MapTask$MapOutputBuffer flush 信息: Starting flush of map output 三月 13, 2016 5:40:04 下午 org.apache.hadoop.mapred.MapTask$MapOutputBuffer sortAndSpill 信息: Finished spill 0 三月 13, 2016 5:40:04 下午 org.apache.hadoop.mapred.Task done 信息: Task:attempt_local_0001_m_000000_0 is done. And is in the process of commiting 三月 13, 2016 5:40:04 下午 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate 信息: 三月 13, 2016 5:40:04 下午 org.apache.hadoop.mapred.Task sendDone 信息: Task ‘attempt_local_0001_m_000000_0‘ done. 三月 13, 2016 5:40:05 下午 org.apache.hadoop.mapred.JobClient monitorAndPrintJob 信息: map 100% reduce 0% 三月 13, 2016 5:40:05 下午 org.apache.hadoop.mapred.Task initialize 信息: Using ResourceCalculatorPlugin : null 三月 13, 2016 5:40:05 下午 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate 信息: 三月 13, 2016 5:40:05 下午 org.apache.hadoop.mapred.Merger$MergeQueue merge 信息: Merging 1 sorted segments 三月 13, 2016 5:40:05 下午 org.apache.hadoop.mapred.Merger$MergeQueue merge 信息: Down to the last merge-pass, with 1 segments left of total size: 542 bytes 三月 13, 2016 5:40:05 下午 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate 信息: 三月 13, 2016 5:40:06 下午 org.apache.hadoop.mapred.Task done 信息: Task:attempt_local_0001_r_000000_0 is done. And is in the process of commiting 三月 13, 2016 5:40:06 下午 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate 信息: 三月 13, 2016 5:40:06 下午 org.apache.hadoop.mapred.Task commit 信息: Task attempt_local_0001_r_000000_0 is allowed to commit now 三月 13, 2016 5:40:06 下午 org.apache.hadoop.mapred.FileOutputCommitter commitTask 信息: Saved output of task ‘attempt_local_0001_r_000000_0‘ to hdfs://192.168.56.10:9000/user/studentInfo 三月 13, 2016 5:40:08 下午 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate 信息: reduce > reduce 三月 13, 2016 5:40:08 下午 org.apache.hadoop.mapred.Task sendDone 信息: Task ‘attempt_local_0001_r_000000_0‘ done. 三月 13, 2016 5:40:09 下午 org.apache.hadoop.mapred.JobClient monitorAndPrintJob 信息: map 100% reduce 100% 三月 13, 2016 5:40:09 下午 org.apache.hadoop.mapred.JobClient monitorAndPrintJob 信息: Job complete: job_local_0001 三月 13, 2016 5:40:09 下午 org.apache.hadoop.mapred.Counters log 信息: Counters: 20 三月 13, 2016 5:40:09 下午 org.apache.hadoop.mapred.Counters log 信息: File Input Format Counters 三月 13, 2016 5:40:09 下午 org.apache.hadoop.mapred.Counters log 信息: Bytes Read=0 三月 13, 2016 5:40:09 下午 org.apache.hadoop.mapred.Counters log 信息: File Output Format Counters 三月 13, 2016 5:40:09 下午 org.apache.hadoop.mapred.Counters log 信息: Bytes Written=513 三月 13, 2016 5:40:09 下午 org.apache.hadoop.mapred.Counters log 信息: FileSystemCounters 三月 13, 2016 5:40:09 下午 org.apache.hadoop.mapred.Counters log 信息: FILE_BYTES_READ=1592914 三月 13, 2016 5:40:09 下午 org.apache.hadoop.mapred.Counters log 信息: HDFS_BYTES_READ=1579770 三月 13, 2016 5:40:09 下午 org.apache.hadoop.mapred.Counters log 信息: FILE_BYTES_WRITTEN=3270914 三月 13, 2016 5:40:09 下午 org.apache.hadoop.mapred.Counters log 信息: HDFS_BYTES_WRITTEN=513 三月 13, 2016 5:40:09 下午 org.apache.hadoop.mapred.Counters log 信息: Map-Reduce Framework 三月 13, 2016 5:40:09 下午 org.apache.hadoop.mapred.Counters log 信息: Reduce input groups=9 三月 13, 2016 5:40:09 下午 org.apache.hadoop.mapred.Counters log 信息: Map output materialized bytes=546 三月 13, 2016 5:40:09 下午 org.apache.hadoop.mapred.Counters log 信息: Combine output records=0 三月 13, 2016 5:40:09 下午 org.apache.hadoop.mapred.Counters log 信息: Map input records=9 三月 13, 2016 5:40:09 下午 org.apache.hadoop.mapred.Counters log 信息: Reduce shuffle bytes=0 三月 13, 2016 5:40:09 下午 org.apache.hadoop.mapred.Counters log 信息: Reduce output records=9 三月 13, 2016 5:40:09 下午 org.apache.hadoop.mapred.Counters log 信息: Spilled Records=18 三月 13, 2016 5:40:09 下午 org.apache.hadoop.mapred.Counters log 信息: Map output bytes=522 三月 13, 2016 5:40:09 下午 org.apache.hadoop.mapred.Counters log 信息: Total committed heap usage (bytes)=231874560 三月 13, 2016 5:40:09 下午 org.apache.hadoop.mapred.Counters log 信息: Map input bytes=9 三月 13, 2016 5:40:09 下午 org.apache.hadoop.mapred.Counters log 信息: Combine input records=0 三月 13, 2016 5:40:09 下午 org.apache.hadoop.mapred.Counters log 信息: Map output records=9 三月 13, 2016 5:40:09 下午 org.apache.hadoop.mapred.Counters log 信息: SPLIT_RAW_BYTES=75 三月 13, 2016 5:40:09 下午 org.apache.hadoop.mapred.Counters log 信息: Reduce input records=9
这是运行的结果：
到此，Hadoop连接数据库读取数据表输出的操作完成了，当然这就是一个简单的演示，实际项目中不会用到，只是可以帮我们熟悉熟悉Hadoop操作数据库的流程，下面给出
Hadoop处理文件以后，将结果写入数据库的示例代码，和上面的差不多：
1 package cn.hadoop.db;
2
3 import java.io.DataInput;
4 import java.io.DataOutput;
5 import java.io.IOException;
6 import java.net.URI;
7 import java.sql.PreparedStatement;
8 import java.sql.ResultSet;
9 import java.sql.SQLException;
10 import java.util.Iterator;
11 import java.util.StringTokenizer;
12
13 import org.apache.hadoop.filecache.DistributedCache;
14 import org.apache.hadoop.fs.FileSystem;
15 import org.apache.hadoop.fs.Path;
16 import org.apache.hadoop.io.IntWritable;
17 import org.apache.hadoop.io.Text;
18 import org.apache.hadoop.io.Writable;
19 import org.apache.hadoop.mapred.FileInputFormat;
20 import org.apache.hadoop.mapred.JobClient;
21 import org.apache.hadoop.mapred.JobConf;
22 import org.apache.hadoop.mapred.MapReduceBase;
23 import org.apache.hadoop.mapred.Mapper;
24 import org.apache.hadoop.mapred.OutputCollector;
25 import org.apache.hadoop.mapred.Reducer;
26 import org.apache.hadoop.mapred.Reporter;
27 import org.apache.hadoop.mapred.TextInputFormat;
28 import org.apache.hadoop.mapred.lib.db.DBConfiguration;
29 import org.apache.hadoop.mapred.lib.db.DBOutputFormat;
30 import org.apache.hadoop.mapred.lib.db.DBWritable;
31
32 public class WriteDB {
33
34 public static void main(String[] args) throws IOException {
35 JobConf conf = new JobConf();
36
37 FileSystem fileSystem = FileSystem.get(
38 URI.create("hdfs://192.168.56.10:9000/"), conf);
39 DistributedCache
40 .addFileToClassPath(
41 new Path(
42 "hdfs://192.168.56.10:9000/lib/mysql-connector-java-5.1.18-bin.jar"),
43 conf, fileSystem);
44 conf.setInputFormat(TextInputFormat.class);
45 conf.setOutputFormat(DBOutputFormat.class);
46
47 conf.setOutputKeyClass(Text.class);
48 conf.setOutputValueClass(IntWritable.class);
49
50 conf.setMapperClass(Map.class);
51 conf.setCombinerClass(Combine.class);
52 conf.setReducerClass(Reduce.class);
53
54 FileInputFormat.setInputPaths(conf, new Path(
55 "hdfs://192.168.56.10:9000/user/db_in"));
56
57 DBConfiguration
58 .configureDB(
59 conf,
60 "com.mysql.jdbc.Driver",
61 "jdbc:mysql://192.168.56.109:3306/school?characterEncoding=UTF-8",
62 "root", "1qaz2wsx");
63
64 String[] fields = { "word", "number" };
65
66 DBOutputFormat.setOutput(conf, "wordcount", fields);
67 JobClient.runJob(conf);
68
69 }
70 }
71
72 class Map extends MapReduceBase implements
73 Mapper<Object, Text, Text, IntWritable> {
74
75 private final static IntWritable one = new IntWritable(1);
76
77 private Text word = new Text();
78
79 @Override
80 public void map(Object key, Text value,
81 OutputCollector<Text, IntWritable> output, Reporter reporter)
82 throws IOException {
83 String line = value.toString();
84 StringTokenizer tokenizer = new StringTokenizer(line);
85 while (tokenizer.hasMoreTokens()) {
86 word.set(tokenizer.nextToken());
87 output.collect(word, one);
88 }
89 }
90
91 }
92
93 class Combine extends MapReduceBase implements
94 Reducer<Text, IntWritable, Text, IntWritable> {
95
96 @Override
97 public void reduce(Text key, Iterator<IntWritable> values,
98 OutputCollector<Text, IntWritable> output, Reporter reporter)
99 throws IOException {
100 int sum = 0;
101 while (values.hasNext()) {
102 sum += values.next().get();
103 }
104 output.collect(key, new IntWritable(sum));
105 }
106
107 }
108
109 class Reduce extends MapReduceBase implements
110 Reducer<Text, IntWritable, WordRecord, Text> {
111
112 @Override
113 public void reduce(Text key, Iterator<IntWritable> values,
114 OutputCollector<WordRecord, Text> output, Reporter reporter)
115 throws IOException {
116 int sum = 0;
117 while (values.hasNext()) {
118 sum += values.next().get();
119 }
120 WordRecord wordcount = new WordRecord();
121 wordcount.word = key.toString();
122 wordcount.number = sum;
123 output.collect(wordcount, new Text());
124 }
125
126 }
127
128 class WordRecord implements Writable, DBWritable {
129
130 public String word;
131 public int number;
132
133 @Override
134 public void write(PreparedStatement statement) throws SQLException {
135 statement.setString(1, this.word);
136 statement.setInt(2, this.number);
137 }
138
139 @Override
140 public void readFields(ResultSet resultSet) throws SQLException {
141 this.word = resultSet.getString(1);
142 this.number = resultSet.getInt(2);
143 }
144
145 @Override
146 public void write(DataOutput out) throws IOException {
147 Text.writeString(out, this.word);
148 out.writeInt(this.number);
149 }
150
151 @Override
152 public void readFields(DataInput in) throws IOException {
153 this.word = Text.readString(in);
154 this.number = in.readInt();
155 }
156
157 }
运行打印的日志信息如下：
三月 13, 2016 6:09:31 下午 org.apache.hadoop.util.NativeCodeLoader <clinit> 警告: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable 三月 13, 2016 6:09:31 下午 org.apache.hadoop.mapred.JobClient copyAndConfigureFiles 警告: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same. 三月 13, 2016 6:09:31 下午 org.apache.hadoop.mapred.JobClient copyAndConfigureFiles 警告: No job jar file set. User classes may not be found. See JobConf(Class) or JobConf#setJar(String). 三月 13, 2016 6:09:31 下午 org.apache.hadoop.mapred.FileInputFormat listStatus 信息: Total input paths to process : 2 三月 13, 2016 6:09:32 下午 org.apache.hadoop.filecache.TrackerDistributedCacheManager downloadCacheObject 信息: Creating mysql-connector-java-5.1.18-bin.jar in /tmp/hadoop-hadoop/mapred/local/archive/-8205516116475251282_-2048973133_91096108/192.168.56.10/lib-work-1371358416408211818 with rwxr-xr-x 三月 13, 2016 6:09:33 下午 org.apache.hadoop.filecache.TrackerDistributedCacheManager downloadCacheObject 信息: Cached hdfs://192.168.56.10:9000/lib/mysql-connector-java-5.1.18-bin.jar as /tmp/hadoop-hadoop/mapred/local/archive/-8205516116475251282_-2048973133_91096108/192.168.56.10/lib/mysql-connector-java-5.1.18-bin.jar 三月 13, 2016 6:09:33 下午 org.apache.hadoop.filecache.TrackerDistributedCacheManager localizePublicCacheObject 信息: Cached hdfs://192.168.56.10:9000/lib/mysql-connector-java-5.1.18-bin.jar as /tmp/hadoop-hadoop/mapred/local/archive/-8205516116475251282_-2048973133_91096108/192.168.56.10/lib/mysql-connector-java-5.1.18-bin.jar 三月 13, 2016 6:09:33 下午 org.apache.hadoop.mapred.JobClient monitorAndPrintJob 信息: Running job: job_local_0001 三月 13, 2016 6:09:33 下午 org.apache.hadoop.mapred.Task initialize 信息: Using ResourceCalculatorPlugin : null 三月 13, 2016 6:09:33 下午 org.apache.hadoop.mapred.MapTask runOldMapper 信息: numReduceTasks: 1 三月 13, 2016 6:09:33 下午 org.apache.hadoop.mapred.MapTask$MapOutputBuffer <init> 信息: io.sort.mb = 100 三月 13, 2016 6:09:34 下午 org.apache.hadoop.mapred.MapTask$MapOutputBuffer <init> 信息: data buffer = 79691776/99614720 三月 13, 2016 6:09:34 下午 org.apache.hadoop.mapred.MapTask$MapOutputBuffer <init> 信息: record buffer = 262144/327680 三月 13, 2016 6:09:34 下午 org.apache.hadoop.mapred.MapTask$MapOutputBuffer flush 信息: Starting flush of map output 三月 13, 2016 6:09:34 下午 org.apache.hadoop.mapred.MapTask$MapOutputBuffer sortAndSpill 信息: Finished spill 0 三月 13, 2016 6:09:34 下午 org.apache.hadoop.mapred.Task done 信息: Task:attempt_local_0001_m_000000_0 is done. And is in the process of commiting 三月 13, 2016 6:09:34 下午 org.apache.hadoop.mapred.JobClient monitorAndPrintJob 信息: map 0% reduce 0% 三月 13, 2016 6:09:36 下午 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate 信息: hdfs://192.168.56.10:9000/user/db_in/file2.txt:0+41 三月 13, 2016 6:09:36 下午 org.apache.hadoop.mapred.Task sendDone 信息: Task ‘attempt_local_0001_m_000000_0‘ done. 三月 13, 2016 6:09:36 下午 org.apache.hadoop.mapred.Task initialize 信息: Using ResourceCalculatorPlugin : null 三月 13, 2016 6:09:36 下午 org.apache.hadoop.mapred.MapTask runOldMapper 信息: numReduceTasks: 1 三月 13, 2016 6:09:36 下午 org.apache.hadoop.mapred.MapTask$MapOutputBuffer <init> 信息: io.sort.mb = 100 三月 13, 2016 6:09:36 下午 org.apache.hadoop.mapred.MapTask$MapOutputBuffer <init> 信息: data buffer = 79691776/99614720 三月 13, 2016 6:09:36 下午 org.apache.hadoop.mapred.MapTask$MapOutputBuffer <init> 信息: record buffer = 262144/327680 三月 13, 2016 6:09:36 下午 org.apache.hadoop.mapred.MapTask$MapOutputBuffer flush 信息: Starting flush of map output 三月 13, 2016 6:09:36 下午 org.apache.hadoop.mapred.MapTask$MapOutputBuffer sortAndSpill 信息: Finished spill 0 三月 13, 2016 6:09:36 下午 org.apache.hadoop.mapred.Task done 信息: Task:attempt_local_0001_m_000001_0 is done. And is in the process of commiting 三月 13, 2016 6:09:37 下午 org.apache.hadoop.mapred.JobClient monitorAndPrintJob 信息: map 100% reduce 0% 三月 13, 2016 6:09:39 下午 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate 信息: hdfs://192.168.56.10:9000/user/db_in/file1.txt:0+24 三月 13, 2016 6:09:39 下午 org.apache.hadoop.mapred.Task sendDone 信息: Task ‘attempt_local_0001_m_000001_0‘ done. 三月 13, 2016 6:09:39 下午 org.apache.hadoop.mapred.Task initialize 信息: Using ResourceCalculatorPlugin : null 三月 13, 2016 6:09:39 下午 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate 信息: 三月 13, 2016 6:09:39 下午 org.apache.hadoop.mapred.Merger$MergeQueue merge 信息: Merging 2 sorted segments 三月 13, 2016 6:09:39 下午 org.apache.hadoop.mapred.Merger$MergeQueue merge 信息: Down to the last merge-pass, with 2 segments left of total size: 116 bytes 三月 13, 2016 6:09:39 下午 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate 信息: 三月 13, 2016 6:09:41 下午 org.apache.hadoop.mapred.Task done 信息: Task:attempt_local_0001_r_000000_0 is done. And is in the process of commiting 三月 13, 2016 6:09:42 下午 org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate 信息: reduce > reduce 三月 13, 2016 6:09:42 下午 org.apache.hadoop.mapred.Task sendDone 信息: Task ‘attempt_local_0001_r_000000_0‘ done. 三月 13, 2016 6:09:42 下午 org.apache.hadoop.mapred.FileOutputCommitter cleanupJob 警告: Output path is null in cleanup 三月 13, 2016 6:09:43 下午 org.apache.hadoop.mapred.JobClient monitorAndPrintJob 信息: map 100% reduce 100% 三月 13, 2016 6:09:43 下午 org.apache.hadoop.mapred.JobClient monitorAndPrintJob 信息: Job complete: job_local_0001 三月 13, 2016 6:09:43 下午 org.apache.hadoop.mapred.Counters log 信息: Counters: 19 三月 13, 2016 6:09:43 下午 org.apache.hadoop.mapred.Counters log 信息: File Input Format Counters 三月 13, 2016 6:09:43 下午 org.apache.hadoop.mapred.Counters log 信息: Bytes Read=65 三月 13, 2016 6:09:43 下午 org.apache.hadoop.mapred.Counters log 信息: File Output Format Counters 三月 13, 2016 6:09:43 下午 org.apache.hadoop.mapred.Counters log 信息: Bytes Written=0 三月 13, 2016 6:09:43 下午 org.apache.hadoop.mapred.Counters log 信息: FileSystemCounters 三月 13, 2016 6:09:43 下午 org.apache.hadoop.mapred.Counters log 信息: FILE_BYTES_READ=2389740 三月 13, 2016 6:09:43 下午 org.apache.hadoop.mapred.Counters log 信息: HDFS_BYTES_READ=2369826 三月 13, 2016 6:09:43 下午 org.apache.hadoop.mapred.Counters log 信息: FILE_BYTES_WRITTEN=4905883 三月 13, 2016 6:09:43 下午 org.apache.hadoop.mapred.Counters log 信息: Map-Reduce Framework 三月 13, 2016 6:09:43 下午 org.apache.hadoop.mapred.Counters log 信息: Reduce input groups=7 三月 13, 2016 6:09:43 下午 org.apache.hadoop.mapred.Counters log 信息: Map output materialized bytes=124 三月 13, 2016 6:09:43 下午 org.apache.hadoop.mapred.Counters log 信息: Combine output records=9 三月 13, 2016 6:09:43 下午 org.apache.hadoop.mapred.Counters log 信息: Map input records=5 三月 13, 2016 6:09:43 下午 org.apache.hadoop.mapred.Counters log 信息: Reduce shuffle bytes=0 三月 13, 2016 6:09:43 下午 org.apache.hadoop.mapred.Counters log 信息: Reduce output records=7 三月 13, 2016 6:09:43 下午 org.apache.hadoop.mapred.Counters log 信息: Spilled Records=18 三月 13, 2016 6:09:43 下午 org.apache.hadoop.mapred.Counters log 信息: Map output bytes=104 三月 13, 2016 6:09:43 下午 org.apache.hadoop.mapred.Counters log 信息: Total committed heap usage (bytes)=482291712 三月 13, 2016 6:09:43 下午 org.apache.hadoop.mapred.Counters log 信息: Map input bytes=65 三月 13, 2016 6:09:43 下午 org.apache.hadoop.mapred.Counters log 信息: Combine input records=10 三月 13, 2016 6:09:43 下午 org.apache.hadoop.mapred.Counters log 信息: Map output records=10 三月 13, 2016 6:09:43 下午 org.apache.hadoop.mapred.Counters log 信息: SPLIT_RAW_BYTES=198 三月 13, 2016 6:09:43 下午 org.apache.hadoop.mapred.Counters log 信息: Reduce input records=9
数据库中的结果如下：
以下代码都是本人亲自测试和运行过的，hadoop的版本和服务器环境信息请参看上一篇博文。
时间： 2024-12-12 11:58:15