hadoop之mapreduce编程实例（系统日志初步清洗过滤处理）
Posted zfszhangyuan
tags:
篇首语：本文由小常识网(cha138.com)小编为大家整理，主要介绍了hadoop之mapreduce编程实例（系统日志初步清洗过滤处理）相关的知识，希望对你有一定的参考价值。
刚刚开始接触hadoop的时候，总觉得必须要先安装hadoop集群才能开始学习MR编程，其实并不用这样，当然如果你有条件有机器那最好是自己安装配置一个hadoop集群，这样你会更容易理解其工作原理。我们今天就是要给大家演示如何不用安装hadoop直接调试编程MapReduce函数。
开始之前我们先来理解一下mapreduce的工作原理：
hadoop集群是有DataNode和NameNode两种节点构成，DataNode负责存储数据本身而NameNode负责存储数据的元数据信息，在启动mapreduce任务时，数据首先是通过inputformat模块从集群的文件库中读出，然后按照设定的Splitsize进行Split（默认是一个block大小128MB），通过ReadRecorder（RR）将每个split的数据块按行进行轮询访问结果给到map函数，由map函数按照编程的代码逻辑进行处理，输出key和value。由map到reduce的处理过程中包含三件事情，Combiner（map端的预先处理，相对于map段reduce）Partitioner（负责将map输出数据均衡的分配给reduce）Shulffling&&sort(根据map输出的key进行洗牌和排序，将结果根据partitioner的分配情况传输给指定的reduce)，最后reduce按照代码逻辑处理输出结果（也是key,value格式）。
注意：
map阶段的key-value对的格式是由输入的格式所决定的，如果是默认的TextInputFormat，则每行作为一个记录进程处理，其中key为此行的开头相对于文件的起始位置，value就是此行的字符文本
map阶段的输出的key-value对的格式必须同reduce阶段的输入key-value对的格式相对应
下面是wordcount的处理过程大家来理解一下：
现在我们开始我们的本地MR编程吧
首先我们得去官网下载一个hadoop安装包（本文用的hadoop2.6.0版本，不用安装，我们只要包中jars）
下载链接：https://archive.apache.org/dist/hadoop/common/（下载最多的那个就可以了，版本自己选个）
下面就上MR的代码吧：
package loganalysis;
import java.io.IOException;
import java.util.StringTokenizer;
import java.lang.*;
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;
import org.apache.hadoop.util.GenericOptionsParser;
public class WordCount
public static class TokenizerMapper
extends Mapper<Object, Text, Text, IntWritable>
private final static IntWritable one = new IntWritable(1);
private Text word = new Text();
private String imei = new String();
private String areacode = new String();
private String responsedata = new String();
private String requesttime = new String();
private String requestip = new String();
// map阶段的key-value对的格式是由输入的格式所决定的，如果是默认的TextInputFormat，则每行作为一个记录进程处理，其中key为此行的开头相对于文件的起始位置，value就是此行的字符文本
// map阶段的输出的key-value对的格式必须同reduce阶段的输入key-value对的格式相对应
public void map(Object key, Text value, Context context
) throws IOException, InterruptedException
//StringTokenizer itr = new StringTokenizer(value.toString());
int areai = value.toString().indexOf("areacode", 21);
int imeii = value.toString().indexOf("imei", 21);
int redatai = value.toString().indexOf("responsedata", 21);
int retimei = value.toString().indexOf("requesttime", 21);
int reipi = value.toString().indexOf("requestip", 21);
if (areai==-1)
areacode="";
else
areacode=value.toString().substring(areai+11);
int len2=areacode.indexOf("\\"");
if(len2 <= 1)
areacode="";
else
areacode=areacode.substring(0,len2);
if (imeii==-1)
imei="";
else
imei=value.toString().substring(imeii+9);
int len2=imei.indexOf("\\\\");
if(len2 <= 1)
imei="";
else
imei=imei.substring(0,len2);
if (redatai==-1)
responsedata="";
else
responsedata=value.toString().substring(redatai+15);
int len2=responsedata.indexOf("\\"");
if(len2 <= 1)
responsedata="";
else
responsedata=responsedata.substring(0,len2);
if (retimei==-1)
requesttime="";
else
requesttime=value.toString().substring(retimei+14);
int len2=requesttime.indexOf("\\"");
if(len2 <= 1)
requesttime="";
else
requesttime=requesttime.substring(0,len2);
if (reipi==-1)
requestip="";
else
requestip=value.toString().substring(reipi+12);
int len2=requestip.indexOf("\\"");
if(len2 <= 1)
requestip="";
else
requestip=requestip.substring(0,len2);
/* while (itr.hasMoreTokens())
string tim;
word.set(itr.nextToken());
context.write(word, one);
*/
if(imei!=""&&areacode!=""&&responsedata!=""&&requesttime!=""&&requestip!="")
String wd=new String();
wd=imei+"\\t"+areacode+"\\t"+responsedata+"\\t"+requesttime+"\\t"+requestip;
//wd="areacode|"+areacode +"|imei|"+ imei +"|responsedata|"+ responsedata +"|requesttime|"+ requesttime +"|requestip|"+ requestip;
word.set(wd);
context.write(word, one);
public static class IntSumReducer
extends Reducer<Text,IntWritable,Text,IntWritable>
private IntWritable result = new IntWritable();
public void reduce(Text key, Iterable<IntWritable> values,
Context context
) throws IOException, InterruptedException
int sum = 0;
for (IntWritable val : values)
sum += val.get();
result.set(sum);
context.write(key, result);
public static void main(String[] args) throws Exception
Configuration conf = new Configuration();
// String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
String[] otherArgs=new String[]"/Users/mac/tmp/inputmr","/Users/mac/tmp/output1";
if (otherArgs.length != 2)
System.err.println("Usage: wordcount <in> <out>");
System.exit(2);
//Job job = new Job(conf, "word count");
Job job = Job.getInstance(conf);
job.setJarByClass(WordCount.class);
job.setMapperClass(TokenizerMapper.class);
job.setCombinerClass(IntSumReducer.class);
job.setReducerClass(IntSumReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
System.exit(job.waitForCompletion(true) ? 0 : 1);
如果你不知道那些包需要那就将share\\hadoop\\下面的所以得jar包都添加到项目中
注意：我的电脑是mac pro如果你的是Windows机器相关的路径需要修改一下，前面加上“file:///”（ file:///D:\\tmp\\input file:///D:\\tmp\\output)
String[] otherArgs=new String[]"file:///D:\\tmp\\input","file:///D:\\tmp\\output";
这个程序核心代码都是在map中，主要做了系统日志中相关核心字段的提取并拼接以key形式返回给reduce，value都是设置为1，是为了方便以后的统计。因为是实例所以简单的弄了几个字段，实际可不止这些。
下面给下测试的系统日志：
2016-04-18 16:00:00 "areacode":"浙江省丽水市","countAll":0,"countCorrect":0,"datatime":"4134362","logid":"201604181600001184409476","requestinfo":"\\"sign\\":\\"4\\",\\"timestamp\\":\\"1460966390499\\",\\"remark\\":\\"4\\",\\"subjectPro\\":\\"123456\\",\\"interfaceUserName\\":\\"12345678900987654321\\",\\"channelno\\":\\"100\\",\\"imei\\":\\"12345678900987654321\\",\\"subjectNum\\":\\"13989589062\\",\\"imsi\\":\\"12345678900987654321\\",\\"queryNum\\":\\"13989589062\\"","requestip":"36.16.128.234","requesttime":"2016-04-18 16:00:00","requesttype":"0","responsecode":"010005","responsedata":"无查询结果"
2016-04-18 16:00:00 "areacode":"宁夏银川市","countAll":0,"countCorrect":0,"datatime":"4715990","logid":"201604181600001858043208","requestinfo":"\\"sign\\":\\"4\\",\\"timestamp\\":\\"1460966400120\\",\\"remark\\":\\"4\\",\\"subjectPro\\":\\"123456\\",\\"interfaceUserName\\":\\"12345678900987654321\\",\\"channelno\\":\\"1210\\",\\"imei\\":\\"A0000044ABFD25\\",\\"subjectNum\\":\\"15379681917\\",\\"imsi\\":\\"460036951451601\\",\\"queryNum\\":\\"\\"","requestip":"115.168.93.87","requesttime":"2016-04-18 16:00:00","requesttype":"0","responsecode":"010005","responsedata":"无查询结果","userAgent":"ZTE-Me/Mobile"
2016-04-18 16:00:00 "areacode":"黑龙江省哈尔滨市","countAll":0,"countCorrect":0,"datatime":"5369561","logid":"201604181600001068429609","requestinfo":"\\"interfaceUserName\\":\\"12345678900987654321\\",\\"queryNum\\":\\"\\",\\"timestamp\\":\\"1460966400139\\",\\"sign\\":\\"4\\",\\"imsi\\":\\"460030301212545\\",\\"imei\\":\\"35460207765269\\",\\"subjectNum\\":\\"55588237\\",\\"subjectPro\\":\\"123456\\",\\"remark\\":\\"4\\",\\"channelno\\":\\"2100\\"","requestip":"42.184.41.180","requesttime":"2016-04-18 16:00:00","requesttype":"0","responsecode":"010005","responsedata":"无查询结果"
2016-04-18 16:00:00 "areacode":"浙江省丽水市","countAll":0,"countCorrect":0,"datatime":"4003096","logid":"201604181600001648238807","requestinfo":"\\"sign\\":\\"4\\",\\"timestamp\\":\\"1460966391025\\",\\"remark\\":\\"4\\",\\"subjectPro\\":\\"123456\\",\\"interfaceUserName\\":\\"12345678900987654321\\",\\"channelno\\":\\"100\\",\\"imei\\":\\"12345678900987654321\\",\\"subjectNum\\":\\"13989589062\\",\\"imsi\\":\\"12345678900987654321\\",\\"queryNum\\":\\"13989589062\\"","requestip":"36.16.128.234","requesttime":"2016-04-18 16:00:00","requesttype":"0","responsecode":"010005","responsedata":"无查询结果"
2016-04-18 16:00:00 "areacode":"广西南宁市","countAll":0,"countCorrect":0,"datatime":"4047993","logid":"201604181600001570024205","requestinfo":"\\"sign\\":\\"4\\",\\"timestamp\\":\\"1460966382871\\",\\"remark\\":\\"4\\",\\"subjectPro\\":\\"123456\\",\\"interfaceUserName\\":\\"12345678900987654321\\",\\"channelno\\":\\"1006\\",\\"imei\\":\\"A000004853168C\\",\\"subjectNum\\":\\"07765232589\\",\\"imsi\\":\\"460031210400007\\",\\"queryNum\\":\\"13317810717\\"","requestip":"219.159.72.3","requesttime":"2016-04-18 16:00:00","requesttype":"0","responsecode":"010005","responsedata":"无查询结果"
2016-04-18 16:00:00 "areacode":"海南省五指山市","countAll":0,"countCorrect":0,"datatime":"5164117","logid":"201604181600001227842048","requestinfo":"\\"sign\\":\\"4\\",\\"timestamp\\":\\"1460966399159\\",\\"remark\\":\\"4\\",\\"subjectPro\\":\\"123456\\",\\"interfaceUserName\\":\\"12345678900987654321\\",\\"channelno\\":\\"1017\\",\\"imei\\":\\"A000005543AFB7\\",\\"subjectNum\\":\\"089836329061\\",\\"imsi\\":\\"460036380954376\\",\\"queryNum\\":\\"13389875751\\"","requestip":"140.240.171.71","requesttime":"2016-04-18 16:00:00","requesttype":"0","responsecode":"010005","responsedata":"无查询结果"
2016-04-18 16:00:00 "areacode":"山西省","countAll":0,"countCorrect":0,"datatime":"14075772","logid":"201604181600001284030648","requestinfo":"\\"sign\\":\\"4\\",\\"timestamp\\":\\"1460966400332\\",\\"remark\\":\\"4\\",\\"subjectPro\\":\\"123456\\",\\"interfaceUserName\\":\\"12345678900987654321\\",\\"channelno\\":\\"1006\\",\\"imei\\":\\"A000004FE0218A\\",\\"subjectNum\\":\\"03514043633\\",\\"imsi\\":\\"460037471517070\\",\\"queryNum\\":\\"\\"","requestip":"1.68.5.227","requesttime":"2016-04-18 16:00:00","requesttype":"0","responsecode":"010005","responsedata":"无查询结果"
2016-04-18 16:00:00 "areacode":"四川省","countAll":0,"countCorrect":0,"datatime":"6270982","logid":"201604181600001173504863","requestinfo":"\\"sign\\":\\"4\\",\\"timestamp\\":\\"1460966398896\\",\\"remark\\":\\"4\\",\\"subjectPro\\":\\"123456\\",\\"interfaceUserName\\":\\"12345678900987654321\\",\\"channelno\\":\\"100\\",\\"imei\\":\\"12345678900987654321\\",\\"subjectNum\\":\\"13666231300\\",\\"imsi\\":\\"12345678900987654321\\",\\"queryNum\\":\\"13666231300\\"","requestip":"182.144.66.97","requesttime":"2016-04-18 16:00:00","requesttype":"0","responsecode":"010005","responsedata":"无查询结果"
2016-04-18 16:00:00 "areacode":"浙江省","countAll":0,"countCorrect":0,"datatime":"4198522","logid":"201604181600001390637240","requestinfo":"\\"sign\\":\\"4\\",\\"timestamp\\":\\"1460966399464\\",\\"remark\\":\\"4\\",\\"subjectPro\\":\\"123456\\",\\"interfaceUserName\\":\\"12345678900987654321\\",\\"channelno\\":\\"100\\",\\"imei\\":\\"12345678900987654321\\",\\"subjectNum\\":\\"05533876327\\",\\"imsi\\":\\"12345678900987654321\\",\\"queryNum\\":\\"05533876327\\"","requestip":"36.23.9.49","requesttime":"2016-04-18 16:00:00","requesttype":"0","responsecode":"000000","responsedata":"操作成功"
2016-04-18 16:00:00 "areacode":"江苏省连云港市","countAll":0,"countCorrect":0,"datatime":"4408097","logid":"201604181600001249944032","requestinfo":"\\"sign\\":\\"4\\",\\"timestamp\\":\\"1460966395908\\",\\"remark\\":\\"4\\",\\"subjectPro\\":\\"123456\\",\\"interfaceUserName\\":\\"12345678900987654321\\",\\"channelno\\":\\"100\\",\\"imei\\":\\"12345678900987654321\\",\\"subjectNum\\":\\"18361451463\\",\\"imsi\\":\\"12345678900987654321\\",\\"queryNum\\":\\"18361451463\\"","requestip":"58.223.4.210","requesttime":"2016-04-18 16:00:00","requesttype":"0","responsecode":"010005","responsedata":"无查询结果"
最后给出运行结果截图：
以上是关于hadoop之mapreduce编程实例（系统日志初步清洗过滤处理）的主要内容，如果未能解决你的问题，请参考以下文章
Hadoop MapReduce编程 API入门系列之网页流量版本1（二十二）
Hadoop MapReduce编程 API入门系列之网页流量版本1（二十一）