Naive Bayes在mapreduce上的实现
package hadoop.MachineLearning.Bayes.Pro; import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; public class PriorProbability {//用于求各个类别下的单词数,为后面求先验概率 public static void main(String[] args) throws Exception {
Configuration conf = new Configuration();
String input="hdfs://10.107.8.110:9000/Bayes/Bayes_input/";
String output="hdfs://10.107.8.110:9000/Bayes/Bayes_output/Pro/";
Job job = Job.getInstance(conf, "ProirProbability");
job.setJarByClass(hadoop.MachineLearning.Bayes.Pro.PriorProbability.class);
// TODO: specify a mapper
job.setMapperClass(MyMapper.class);
//job.setMapInputKeyClass(LongWritable.class);
// TODO: specify a reducer
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(Text.class);
job.setReducerClass(MyReducer.class); // TODO: specify output types
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class); // TODO: specify input and output DIRECTORIES (not files)
FileInputFormat.setInputPaths(job, new Path(input));
FileOutputFormat.setOutputPath(job, new Path(output)); if (!job.waitForCompletion(true))
return;
} } package hadoop.MachineLearning.Bayes.Pro; import java.io.IOException; import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Mapper.Context; public class MyMapper extends Mapper<LongWritable, Text, Text, Text> { public void map(LongWritable ikey, Text ivalue, Context context)
throws IOException, InterruptedException {
String[] line=ivalue.toString().split(":| ");
int size=line.length-1;
context.write(new Text(line[0]),new Text(String.valueOf(size)));
} } package hadoop.MachineLearning.Bayes.Pro; import java.io.IOException; import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.Reducer.Context; public class MyReducer extends Reducer<Text, Text, Text, IntWritable> { public void reduce(Text _key, Iterable<Text> values, Context context)
throws IOException, InterruptedException {
// process values
int sum=0;
for (Text val : values) {
sum+=Integer.parseInt(val.toString());
}
context.write(_key,new IntWritable(sum));
} }
package hadoop.MachineLearning.Bayes.Count; import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; public class Count {//计算文档中的单词种类数目 public static void main(String[] args) throws Exception {
Configuration conf = new Configuration();
Job job = Job.getInstance(conf, "Count");
String input="hdfs://10.107.8.110:9000/Bayes/Bayes_input";
String output="hdfs://10.107.8.110:9000/Bayes/Bayes_output/Count";
job.setJarByClass(hadoop.MachineLearning.Bayes.Count.Count.class);
// TODO: specify a mapper
job.setMapperClass(MyMapper.class);
// TODO: specify a reducer
job.setCombinerClass(MyCombiner.class);
job.setReducerClass(MyReducer.class); // TODO: specify output types
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(Text.class); // TODO: specify input and output DIRECTORIES (not files)
FileInputFormat.setInputPaths(job, new Path(input));
FileOutputFormat.setOutputPath(job, new Path(output)); if (!job.waitForCompletion(true))
return;
} } package hadoop.MachineLearning.Bayes.Count; import java.io.IOException; import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper; public class MyMapper extends Mapper<LongWritable, Text, Text, Text> { public void map(LongWritable ikey, Text ivalue, Context context)
throws IOException, InterruptedException {
String[] line=ivalue.toString().split(":| ");
String key="1";
System.out.println(" ");
System.out.println(" ");
System.out.println(" ");
for(int i=1;i<line.length;i++){ System.out.println(line[i]);
context.write(new Text(key),new Text(line[i]));//以相同的key进行输出,使得能最后输出到一个reduce中
}
} } package hadoop.MachineLearning.Bayes.Count; import java.io.IOException;
import java.util.HashSet;
import java.util.Iterator;
import java.util.Set; import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer; public class MyCombiner extends Reducer<Text, Text, Text, Text> {//先在本地的节点上利用set删去重复的单词 public void reduce(Text _key, Iterable<Text> values, Context context)
throws IOException, InterruptedException {
// process values
Set set=new HashSet();
for (Text val : values) {
set.add(val.toString());
}
for(Iterator it=set.iterator();it.hasNext();){
context.write(new Text("1"),new Text(it.next().toString()));
}
} } package hadoop.MachineLearning.Bayes.Count; import java.io.IOException;
import java.util.HashSet;
import java.util.Set; import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer; public class MyReducer extends Reducer<Text, Text, Text, Text> {//通过combiner后,再利用set对单词进行去重,最后得到种类数 public void reduce(Text _key, Iterable<Text> values, Context context)
throws IOException, InterruptedException {
// process values
Set set=new HashSet();
for (Text val : values) {
set.add(val.toString());
}
context.write(new Text("num is "),new Text(String.valueOf(set.size())));
} }
package hadoop.MachineLearning.Bayes.Cond; import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; public class CondiPro {//用于求条件概率 public static void main(String[] args) throws Exception {
Configuration conf = new Configuration();
String input="hdfs://10.107.8.110:9000/Bayes/Bayes_input";
String output="hdfs://10.107.8.110:9000/Bayes/Bayes_output/Con";
String proPath="hdfs://10.107.8.110:9000/Bayes/Bayes_output/Pro";//这是之前求各个类别下单词数目的输出
String countPath="hdfs://10.107.8.110:9000/Bayes/Bayes_output/Count";//这是之前求的单词种类数
conf.set("propath",proPath);
conf.set("countPath",countPath);
Job job = Job.getInstance(conf, "ConditionPro"); job.setJarByClass(hadoop.MachineLearning.Bayes.Cond.CondiPro.class);
// TODO: specify a mapper
job.setMapperClass(MyMapper.class);
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(IntWritable.class);
// TODO: specify a reducer
job.setReducerClass(MyReducer.class); // TODO: specify output types
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class); // TODO: specify input and output DIRECTORIES (not files)
FileInputFormat.setInputPaths(job, new Path(input));
FileOutputFormat.setOutputPath(job, new Path(output)); if (!job.waitForCompletion(true))
return;
} } package hadoop.MachineLearning.Bayes.Cond; import java.io.IOException;
import java.util.Map; import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper; public class MyMapper extends Mapper<LongWritable, Text, Text, IntWritable> { public void map(LongWritable ikey, Text ivalue, Context context)
throws IOException, InterruptedException {
String[] line=ivalue.toString().split(":| ");
for(int i=1;i<line.length;i++){
String key=line[0]+":"+line[i];
context.write(new Text(key),new IntWritable(1));
}
} } package hadoop.MachineLearning.Bayes.Cond; import java.io.IOException;
import java.util.Map; import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.io.DoubleWritable;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer; public class MyReducer extends Reducer<Text, IntWritable, Text, DoubleWritable> {
public Map<String,Integer> map;
public int count=0;
public void setup(Context context) throws IOException{
Configuration conf=context.getConfiguration(); String proPath=conf.get("propath");
String countPath=conf.get("countPath");//
map=Utils.getMapFormHDFS(proPath);//获得各个类别下的单词数
count=Utils.getCountFromHDFS(countPath);//获得单词种类数
}
public void reduce(Text _key, Iterable<IntWritable> values, Context context)
throws IOException, InterruptedException {
// process values
int sum=0;
for (IntWritable val : values) {
sum+=val.get();
}
int type=Integer.parseInt(_key.toString().split(":")[0]);
double probability=0.0;
for(Map.Entry<String,Integer> entry:map.entrySet()){
if(type==Integer.parseInt(entry.getKey())){
probability=(sum+1)*1.0/(entry.getValue()+count);//条件概率的计算
}
}
context.write(_key,new DoubleWritable(probability));
} } package hadoop.MachineLearning.Bayes.Cond; import java.io.IOException;
import java.util.HashMap;
import java.util.Map; import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FSDataInputStream;
import org.apache.hadoop.fs.FileStatus;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.util.LineReader; public class Utils { /**
* @param args
* @throws IOException
*/ public static Map<String,Integer> getMapFormHDFS(String input) throws IOException{
Configuration conf=new Configuration();
Path path=new Path(input);
FileSystem fs=path.getFileSystem(conf); FileStatus[] stats=fs.listStatus(path);
Map<String,Integer> map=new HashMap();
for(int i=0;i<stats.length;i++){
if(stats[i].isFile()){
FSDataInputStream infs=fs.open(stats[i].getPath());
LineReader reader=new LineReader(infs,conf);
Text line=new Text();
while(reader.readLine(line)>0){
String[] temp=line.toString().split(" ");
//System.out.println(temp.length);
map.put(temp[0],Integer.parseInt(temp[1]));
}
reader.close();
}
} return map; } public static Map<String,Double> getMapFormHDFS(String input,boolean j) throws IOException{
Configuration conf=new Configuration();
Path path=new Path(input);
FileSystem fs=path.getFileSystem(conf); FileStatus[] stats=fs.listStatus(path);
Map<String,Double> map=new HashMap();
for(int i=0;i<stats.length;i++){
if(stats[i].isFile()){
FSDataInputStream infs=fs.open(stats[i].getPath());
LineReader reader=new LineReader(infs,conf);
Text line=new Text();
while(reader.readLine(line)>0){
String[] temp=line.toString().split(" ");
//System.out.println(temp.length);
map.put(temp[0],Double.parseDouble(temp[1]));
}
reader.close();
}
} return map; } public static int getCountFromHDFS(String input) throws IOException{
Configuration conf=new Configuration();
Path path=new Path(input);
FileSystem fs=path.getFileSystem(conf); FileStatus[] stats=fs.listStatus(path); int count=0;
for(int i=0;i<stats.length;i++){
if(stats[i].isFile()){
FSDataInputStream infs=fs.open(stats[i].getPath());
LineReader reader=new LineReader(infs,conf);
Text line=new Text();
while(reader.readLine(line)>0){
String[] temp=line.toString().split(" ");
//System.out.println(temp.length);
count=Integer.parseInt(temp[1]);
}
reader.close();
}
}
return count;
} public static void main(String[] args) throws IOException {
// TODO Auto-generated method stub
String proPath="hdfs://10.107.8.110:9000/Bayes/Bayes_output/Pro";
String countPath="hdfs://10.107.8.110:9000/Bayes/Bayes_output/Count/";
Map<String,Integer> map=Utils.getMapFormHDFS(proPath);
for(Map.Entry<String,Integer> entry:map.entrySet()){
System.out.println(entry.getKey()+"->"+entry.getValue());
} int count=Utils.getCountFromHDFS(countPath);
System.out.println("count is "+count);
} }
package hadoop.MachineLearning.Bayes.Predict; import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.DoubleWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; public class Predict { public static void main(String[] args) throws Exception {//预测
Configuration conf = new Configuration();
String input="hdfs://10.107.8.110:9000/Bayes/Predict_input";
String output="hdfs://10.107.8.110:9000/Bayes/Bayes_output/Predict";
String condiProPath="hdfs://10.107.8.110:9000/Bayes/Bayes_output/Con";
String proPath="hdfs://10.107.8.110:9000/Bayes/Bayes_output/Pro";
String countPath="hdfs://10.107.8.110:9000/Bayes/Bayes_output/Count";
conf.set("condiProPath",condiProPath);
conf.set("proPath",proPath);
conf.set("countPath",countPath);
Job job = Job.getInstance(conf, "Predict");
job.setJarByClass(hadoop.MachineLearning.Bayes.Predict.Predict.class);
// TODO: specify a mapper
job.setMapperClass(MyMapper.class);
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(Text.class);
// TODO: specify a reducer
job.setReducerClass(MyReducer.class); // TODO: specify output types
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(DoubleWritable.class); // TODO: specify input and output DIRECTORIES (not files)
FileInputFormat.setInputPaths(job, new Path(input));
FileOutputFormat.setOutputPath(job, new Path(output)); if (!job.waitForCompletion(true))
return;
} } package hadoop.MachineLearning.Bayes.Predict; import java.io.IOException;
import java.util.HashMap;
import java.util.Map; import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper; public class MyMapper extends Mapper<LongWritable, Text, Text, Text> { public Map<String,Integer> map=new HashMap(); public void setup(Context context) throws IOException{
Configuration conf=context.getConfiguration();
String proPath=conf.get("proPath");
map=Utils.getMapFormHDFS(proPath);
} public void map(LongWritable ikey, Text ivalue, Context context)
throws IOException, InterruptedException {
for(Map.Entry<String,Integer> entry:map.entrySet()){
context.write(new Text(entry.getKey()),ivalue);//对每一行数据,打上所有类别,方便后续的求条件概率
}
} } package hadoop.MachineLearning.Bayes.Predict; import java.io.IOException;
import java.util.HashMap;
import java.util.Map; import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.io.DoubleWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer; public class MyReducer extends Reducer<Text, Text, Text, DoubleWritable> { public Map<String,Double> mapDouble=new HashMap();//存放条件概率 public Map<String,Integer> mapInteger=new HashMap();//存放各个类别下的单词数 public Map<String,Double> noFind=new HashMap();//用于那些单词没有出现在某个类别中的 public Map<String,Double> prePro=new HashMap();//求的后的先验概率 public void setup(Context context) throws IOException{
Configuration conf=context.getConfiguration(); String condiProPath=conf.get("condiProPath");
String proPath=conf.get("proPath");
String countPath=conf.get("countPath");
mapDouble=Utils.getMapFormHDFS(condiProPath,true);
mapInteger=Utils.getMapFormHDFS(proPath);
int count=Utils.getCountFromHDFS(countPath);
for(Map.Entry<String,Integer> entry:mapInteger.entrySet()){
double pro=0.0;
noFind.put(entry.getKey(),(1.0/(count+entry.getValue())));
}
int sum=0;
for(Map.Entry<String,Integer> entry:mapInteger.entrySet()){
sum+=entry.getValue();
} for(Map.Entry<String,Integer> entry:mapInteger.entrySet()){
prePro.put(entry.getKey(),(entry.getValue()*1.0/sum));
} } public void reduce(Text _key, Iterable<Text> values, Context context)
throws IOException, InterruptedException {
// process values
String type=_key.toString();
double pro=1.0;
for (Text val : values) {
String[] words=val.toString().split(" ");
for(int i=0;i<words.length;i++){
String condi=type+":"+words[i];
if(mapDouble.get(condi)!=null){//如果该单词出现在该类别中,说明有条件概率
pro=pro*mapDouble.get(condi);
}else{//如果该单词不在该类别中,就采用默认的条件概率
pro=pro*noFind.get(type);
}
}
}
pro=pro*prePro.get(type);
context.write(new Text(type),new DoubleWritable(pro));
} } package hadoop.MachineLearning.Bayes.Predict; import java.io.IOException;
import java.util.HashMap;
import java.util.Map; import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FSDataInputStream;
import org.apache.hadoop.fs.FileStatus;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.util.LineReader; public class Utils { /**
* @param args
* @throws IOException
*/ public static Map<String,Integer> getMapFormHDFS(String input) throws IOException{
Configuration conf=new Configuration();
Path path=new Path(input);
FileSystem fs=path.getFileSystem(conf); FileStatus[] stats=fs.listStatus(path);
Map<String,Integer> map=new HashMap();
for(int i=0;i<stats.length;i++){
if(stats[i].isFile()){
FSDataInputStream infs=fs.open(stats[i].getPath());
LineReader reader=new LineReader(infs,conf);
Text line=new Text();
while(reader.readLine(line)>0){
String[] temp=line.toString().split(" ");
//System.out.println(temp.length);
map.put(temp[0],Integer.parseInt(temp[1]));
}
reader.close();
}
} return map; } public static Map<String,Double> getMapFormHDFS(String input,boolean j) throws IOException{
Configuration conf=new Configuration();
Path path=new Path(input);
FileSystem fs=path.getFileSystem(conf); FileStatus[] stats=fs.listStatus(path);
Map<String,Double> map=new HashMap();
for(int i=0;i<stats.length;i++){
if(stats[i].isFile()){
FSDataInputStream infs=fs.open(stats[i].getPath());
LineReader reader=new LineReader(infs,conf);
Text line=new Text();
while(reader.readLine(line)>0){
String[] temp=line.toString().split(" ");
//System.out.println(temp.length);
map.put(temp[0],Double.parseDouble(temp[1]));
}
reader.close();
}
} return map; } public static int getCountFromHDFS(String input) throws IOException{
Configuration conf=new Configuration();
Path path=new Path(input);
FileSystem fs=path.getFileSystem(conf); FileStatus[] stats=fs.listStatus(path); int count=0;
for(int i=0;i<stats.length;i++){
if(stats[i].isFile()){
FSDataInputStream infs=fs.open(stats[i].getPath());
LineReader reader=new LineReader(infs,conf);
Text line=new Text();
while(reader.readLine(line)>0){
String[] temp=line.toString().split(" ");
//System.out.println(temp.length);
count=Integer.parseInt(temp[1]);
}
reader.close();
}
}
return count;
} public static void main(String[] args) throws IOException {
// TODO Auto-generated method stub
String proPath="hdfs://10.107.8.110:9000/Bayes/Bayes_output/Pro";
String countPath="hdfs://10.107.8.110:9000/Bayes/Bayes_output/Count/";
Map<String,Integer> map=Utils.getMapFormHDFS(proPath);
for(Map.Entry<String,Integer> entry:map.entrySet()){
System.out.println(entry.getKey()+"->"+entry.getValue());
} int count=Utils.getCountFromHDFS(countPath);
System.out.println("count is "+count);
} }
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