Hadoop学习之网络爬虫+分词+倒排索引实现搜索引擎案例

本项目实现的是：自己写一个网络爬虫，对搜狐(或者csdn)爬取新闻(博客)标题,然后把这些新闻标题和它的链接地址上传到hdfs多个文件上，一个文件对应一个标题和链接地址，然后通过分词技术对每个文件中的标题进行分词，分词后建立倒排索引以此来实现搜索引擎的功能，建立倒排索引不熟悉的朋友可以看看我上篇博客

Hadoop–倒排索引过程详解

首先 要自己写一个网络爬虫

由于我开始写爬虫的时候用了htmlparser，把所有搜到的链接存到队列，并且垂直搜索，这个工作量太大，爬了一个小时还没爬完造成了我电脑的死机，所以，现在我就去掉了垂直搜索，只爬搜狐的主页的新闻文章链接

不多说，看代码

首先看下载工具类，解释看注释

package com.yc.spider;

import java.io.BufferedInputStream;
import java.io.BufferedOutputStream;
import java.io.File;
import java.io.FileOutputStream;
import java.io.IOException;
import java.net.HttpURLConnection;
import java.net.MalformedURLException;
import java.net.URL;
import java.text.DateFormat;
import java.text.SimpleDateFormat;
import java.util.Date;
import java.util.List;
import java.util.Random;
import java.util.Scanner;
import java.util.Set;
import java.util.regex.Matcher;
import java.util.regex.Pattern;
/**
* 下载工具类
* @author 汤高
*
*/
public class DownLoadTool {
/**
* 下载页面的内容
* 就是根据地址下载整个html标签
*
* @param addr
* @return
*/
public String downLoadUrl(final String addr) {
StringBuffer sb = new StringBuffer();
try {
URL url;
if(addr.startsWith("http://")==false){
String urladdr=addr+"http://";
url = new URL(urladdr);
}else{
System.out.println(addr);
url = new URL(addr);
}
HttpURLConnection con = (HttpURLConnection) url.openConnection();
con.setConnectTimeout(5000);
con.connect();
if (con.getResponseCode() == 200) {
BufferedInputStream bis = new BufferedInputStream(con
.getInputStream());
Scanner sc = new Scanner(bis,"gbk");
while (sc.hasNextLine()) {
sb.append(sc.nextLine());
}
}
} catch (IOException e) {
e.printStackTrace();
}
return sb.toString();
}

}

然后看一个文章链接的匹配类

package com.yc.spider;

import java.io.BufferedInputStream;
import java.io.IOException;
import java.net.HttpURLConnection;
import java.net.URL;
import java.util.ArrayList;
import java.util.HashSet;
import java.util.List;
import java.util.Scanner;
import java.util.Set;
import java.util.regex.Matcher;
import java.util.regex.Pattern;

/**
* 文章下载类
*
* @author 汤高
*
*
*/
public class ArticleDownLoad {
/**
* 取出文章的a标记href
*/
static String ARTICLE_URL = "<a\\s+[^<>]*\\s+href=\"?(http[^<>\"]*)\"[^<>]*>([^<]*)</a>";

static Set<String> getImageLink(String html) {
Set<String> result = new HashSet<String>();
// 创建一个Pattern模式类，编译这个正则表达式
Pattern p = Pattern.compile(ARTICLE_URL, Pattern.CASE_INSENSITIVE);
// 定义一个匹配器的类
Matcher matcher = p.matcher(html);
while (matcher.find()) {
System.out.println("======="+matcher.group(1)+"\t"+matcher.group(2));
result.add(matcher.group(1)+"\t"+matcher.group(2));
}
return result;

}

}

下面看爬虫类

package com.yc.spider;

import java.io.IOException;
import java.net.URI;
import java.net.URISyntaxException;
import java.util.List;
import java.util.Set;
import java.util.regex.Matcher;
import java.util.regex.Pattern;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FSDataOutputStream;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.htmlparser.util.ParserException;
/**
* 把爬到的内容上传到hdfs
* @author 汤高
*
*
*/
public class Spider {
private DownLoadTool dlt = new DownLoadTool();
private ArticleDownLoad pdl = new ArticleDownLoad();
public void crawling(String url) {
try {
Configuration conf = new Configuration();
URI uri = new URI("hdfs://192.168.52.140:9000");
FileSystem hdfs = FileSystem.get(uri, conf);

String html = dlt.downLoadUrl(url);
Set<String> allneed = pdl.getImageLink(html);
for (String addr : allneed) {
//生成文件路径
Path p1 = new Path("/myspider/" + System.currentTimeMillis());
FSDataOutputStream dos = hdfs.create(p1);
String a = addr + "\n";
//把内容写入文件
dos.write(a.getBytes());
}
} catch (IllegalArgumentException e) {
e.printStackTrace();
} catch (URISyntaxException e) {
e.printStackTrace();
} catch (IOException e) {
e.printStackTrace();
}
}
}

最后看测试类来爬内容

package com.yc.spider;

import java.io.FileNotFoundException;

import org.htmlparser.util.ParserException;

public class Test {
public static void main(String[] args) throws ParserException {
Spider s=new Spider();
//  s.crawling("http://blog.csdn.net");
s.crawling("http://www.sohu.com");

}
}

看看结果



爬到的内容上传到hdfs上了

下面进行分词和建倒排索引

看分词所用到的包



我的分词用了lucenne5.5.1版本

中文分词用到了IKAnalyzer-5.0.1版本，但是与我的lucenne5.5.1不兼容，所以我做了一下兼容，然后自己打成了一个tanggao-IkAnalyzer.jar包，大家可以用现在最新的IKAnalyzer2012版本，应该可以兼容lucenne5.5.1版本

看代码

package com.tg.hadoop;

import java.io.IOException;
import java.io.StringReader;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
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.input.KeyValueTextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.lucene.analysis.Analyzer;
import org.apache.lucene.analysis.TokenStream;
import org.apache.lucene.analysis.tokenattributes.OffsetAttribute;

import com.tg.Ik.IKAnalyzer5x;

public class AriticleInvertedIndex {
/**
*
* @author 汤高
*
*/
public static class ArticleInvertedIndexMapper extends Mapper<Text, Text, Text, Text>{

private Text keyInfo = new Text();  // 存储单词和URI的组合
private Text valueInfo = new Text(); //存储词频
@Override
protected void map(Text key, Text value, Mapper<Text, Text, Text, Text>.Context context)
throws IOException, InterruptedException {

//把标题分词
Analyzer analyzer = new IKAnalyzer5x(true);
TokenStream ts = analyzer.tokenStream("field", new StringReader( value.toString().trim()  ));

OffsetAttribute offsetAtt = ts.addAttribute(OffsetAttribute.class);
try {
ts.reset();
while (ts.incrementToken()) {
System.out.println(offsetAtt.toString().trim());
keyInfo.set( offsetAtt.toString()+":"+key);
valueInfo.set("1");
System.out.println("key"+keyInfo);
System.out.println("value"+valueInfo);
context.write(keyInfo, valueInfo);
}
ts.end();
} finally {
ts.close();
}
}
}

public static class ArticleInvertedIndexCombiner extends Reducer<Text, Text, Text, Text>{
private Text info = new Text();
@Override
protected void reduce(Text key, Iterable<Text> values, Reducer<Text, Text, Text, Text>.Context context)
throws IOException, InterruptedException {

//统计词频
int sum = 0;
for (Text value : values) {
sum += Integer.parseInt(value.toString() );
}

int splitIndex = key.toString().indexOf(":");

//重新设置value值由URI和词频组成
info.set( key.toString().substring( splitIndex + 1) +":"+sum );

//重新设置key值为单词
key.set( key.toString().substring(0,splitIndex));

context.write(key, info);
System.out.println("key"+key);
System.out.println("value"+info);
}
}

public static class ArticleInvertedIndexReducer extends Reducer<Text, Text, Text, Text>{

private Text result = new Text();

@Override
protected void reduce(Text key, Iterable<Text> values, Reducer<Text, Text, Text, Text>.Context context)
throws IOException, InterruptedException {

//生成文档列表
String fileList = new String();
for (Text value : values) {
fileList += value.toString()+";";
}
result.set(fileList);

context.write(key, result);
}

}

public static void main(String[] args) {
try {
Configuration conf = new Configuration();

Job job = Job.getInstance(conf,"InvertedIndex");
job.setJarByClass(AriticleInvertedIndex.class);
job.setInputFormatClass(KeyValueTextInputFormat.class);
//实现map函数，根据输入的<key,value>对生成中间结果。
job.setMapperClass(ArticleInvertedIndexMapper.class);

job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(Text.class);

job.setCombinerClass(ArticleInvertedIndexCombiner.class);
job.setReducerClass(ArticleInvertedIndexReducer.class);

job.setOutputKeyClass(Text.class);
job.setOutputValueClass(Text.class);

FileInputFormat.addInputPath(job, new Path("hdfs://192.168.52.140:9000/myspider/"));
FileOutputFormat.setOutputPath(job, new Path("hdfs://192.168.52.140:9000/myspider_outindex"+System.currentTimeMillis()+"/"));

System.exit(job.waitForCompletion(true) ? 0 : 1);
} catch (IllegalStateException e) {
e.printStackTrace();
} catch (IllegalArgumentException e) {
e.printStackTrace();
} catch (ClassNotFoundException e) {
e.printStackTrace();
} catch (IOException e) {
e.printStackTrace();
} catch (InterruptedException e) {
e.printStackTrace();
}

}
}

结果：



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