用MapReduce处理一组流量数据，并按总流量排序
1、待处理的数据：
1363157985066 1372623050300-FD-07-A4-72-B8:CMCC120.196.100.82i02.c.aliimg.com2427248124681200
1363157995052 138265441015C-0E-8B-C7-F1-E0:CMCC120.197.40.4402640200
1363157991076 1392643565620-10-7A-28-CC-0A:CMCC120.196.100.99241321512200
1363154400022 139262511065C-0E-8B-8B-B1-50:CMCC120.197.40.4402400200
1363157993044 1821157596194-71-AC-CD-E6-18:CMCC-EASY120.196.100.99iface.qiyi.com视频网站151215272106200
1363157995074 841384135C-0E-8B-8C-E8-20:7DaysInn120.197.40.4122.72.52.12201641161432200
1363157993055 13560439658C4-17-FE-BA-DE-D9:CMCC120.196.100.9918151116954200
1363157995033 159201332575C-0E-8B-C7-BA-20:CMCC120.197.40.4sug.so.360.cn信息安全202031562936200
1363157983019 1371919941968-A1-B7-03-07-B1:CMCC-EASY120.196.100.82402400200
1363157984041 136605779915C-0E-8B-92-5C-20:CMCC-EASY120.197.40.4s19.cnzz.com站点统计2496960690200
1363157973098 150136858585C-0E-8B-C7-F7-90:CMCC120.197.40.4rank.ie.sogou.com搜索引擎282736593538200
1363157986029 15989002119E8-99-C4-4E-93-E0:CMCC-EASY120.196.100.99www.umeng.com站点统计331938180200
1363157992093 13560439658C4-17-FE-BA-DE-D9:CMCC120.196.100.991599184938200
1363157986041 134802531045C-0E-8B-C7-FC-80:CMCC-EASY120.197.40.433180180200
1363157984040 136028465655C-0E-8B-8B-B6-00:CMCC120.197.40.42052.flash2-http.qq.com综合门户151219382910200
1363157995093 1392231446600-FD-07-A2-EC-BA:CMCC120.196.100.82img.qfc.cn121230083720200
1363157982040 135024688235C-0A-5B-6A-0B-D4:CMCC-EASY120.196.100.99y0.ifengimg.com综合门户571027335110349200
1363157986072 1832017338284-25-DB-4F-10-1A:CMCC-EASY120.196.100.99input.shouji.sogou.com搜索引擎211895312412200
1363157990043 1392505741300-1F-64-E1-E6-9A:CMCC120.196.100.55t3.baidu.com搜索引擎69631105848243200
1363157988072 1376077871000-FD-07-A4-7B-08:CMCC120.196.100.8222120120200
1363157985066 1372623888800-FD-07-A4-72-B8:CMCC120.196.100.82i02.c.aliimg.com2427248124681200
1363157993055 13560436666C4-17-FE-BA-DE-D9:CMCC120.196.100.9918151116954200
2、新建一个FlowBean类，里面放置数据中需要的属性：
package cn.nanda.wordCount;3、书写Mapper获取需要的信息：
import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
import org.apache.hadoop.io.WritableComparable;
public class FlowBean implements WritableComparable<FlowBean> {
private String phoneNB;
private long up_flow;
private long d_flow;
private long s_flow;
public FlowBean() {
}
public FlowBean(String phoneNB, long up_flow, long d_flow) {
this.phoneNB = phoneNB;
this.up_flow = up_flow;
this.d_flow = d_flow;
this.s_flow = up_flow + d_flow;
}
public String getPhoneNB() {
return phoneNB;
}
public void setPhoneNB(String phoneNB) {
this.phoneNB = phoneNB;
}
public long getUp_flow() {
return up_flow;
}
public void setUp_flow(long up_flow) {
this.up_flow = up_flow;
}
public long getD_flow() {
return d_flow;
}
public void setD_flow(long d_flow) {
this.d_flow = d_flow;
}
public long getS_flow() {
return s_flow;
}
public void setS_flow(long s_flow) {
this.s_flow = s_flow;
}
public int compareTo(FlowBean o) {
// TODO Auto-generated method stub
return s_flow > o.getS_flow() ? -1 : 1;
}
public void write(DataOutput out) throws IOException {
out.writeUTF(phoneNB);
out.writeLong(up_flow);
out.writeLong(d_flow);
out.writeLong(s_flow);
}
public void readFields(DataInput in) throws IOException {
phoneNB = in.readUTF();
up_flow = in.readLong();
d_flow = in.readLong();
s_flow = in.readLong();
}
@Override
public String toString() {
return "" + up_flow + "\t" + d_flow + "\t" + s_flow;
}
}
package cn.nanda.wordCount;
import java.io.IOException;
import org.apache.commons.lang.StringUtils;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
import com.google.common.io.Files;
public class FlowSumMapper extends Mapper<LongWritable, Text, Text, FlowBean> {
@Override
protected void map(LongWritable key, Text value, Context context)
throws IOException, InterruptedException {
// 拿第一行数据
String line = value.toString();
String[] fields = StringUtils.split(line, "\t");
// 拿到我们需要的字段
String phoneNB = fields[1];
long up_flow = Long.parseLong(fields[7]);
long d_flow = Long.parseLong(fields[8]);
// 封装数据kv并输出
context.write(new Text(phoneNB), new FlowBean(phoneNB, up_flow, d_flow));
}
}
4、书写Reducer，对Mapper传来的数据进行分类统计：
package cn.nanda.wordCount;
import java.io.IOException;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;
public class FlowSumReducer extends Reducer<Text, FlowBean, Text, FlowBean> {
@Override
protected void reduce(Text key, Iterable<FlowBean> values, Context context)
throws IOException, InterruptedException {
long up_flow_counter = 0;
long d_flow_counter = 0;
for (FlowBean bean : values) {
up_flow_counter += bean.getUp_flow();
d_flow_counter += bean.getD_flow();
}
context.write(key, new FlowBean(key.toString(), up_flow_counter, d_flow_counter));
}
}
5、申请一个job，并执行：
package cn.nanda.wordCount;6、运行过程：
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
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;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;
public class FlowSumRunner extends Configured implements Tool {
public int run(String[] args) throws Exception {
Configuration conf = new Configuration();
// 如果需要在hdfs云端运行MapReduce，需要加上下面的set，相应的路径填写hdfs上的路径
// conf.set("fs.defaultFS","hdfs://localhost:9000/");
Job job = Job.getInstance(conf);
job.setJarByClass(FlowSumRunner.class);
job.setMapperClass(FlowSumMapper.class);
job.setReducerClass(FlowSumReducer.class);
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(FlowBean.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(FlowBean.class);
FileInputFormat.setInputPaths(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
return job.waitForCompletion(true) ? 0 : 1;
}
public static void main(String[] args) throws Exception {
int run = ToolRunner
.run(new Configuration(), new FlowSumRunner(), args);
System.exit(run);
}
}
2016-05-13 14:54:27,248 WARN util.NativeCodeLoader (NativeCodeLoader.java:<clinit>(62)) - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable7、运行结果：
2016-05-13 14:54:27,466 INFO Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(1173)) - session.id is deprecated. Instead, use dfs.metrics.session-id
2016-05-13 14:54:27,468 INFO jvm.JvmMetrics (JvmMetrics.java:init(76)) - Initializing JVM Metrics with processName=JobTracker, sessionId=
2016-05-13 14:54:27,752 WARN mapreduce.JobResourceUploader (JobResourceUploader.java:uploadFiles(64)) - Hadoop command-line option parsing not performed. Implement the Tool interface and execute your application with ToolRunner to remedy this.
2016-05-13 14:54:27,757 WARN mapreduce.JobResourceUploader (JobResourceUploader.java:uploadFiles(171)) - No job jar file set. User classes may not be found. See Job or Job#setJar(String).
2016-05-13 14:54:27,772 INFO input.FileInputFormat (FileInputFormat.java:listStatus(283)) - Total input paths to process : 1
2016-05-13 14:54:27,831 INFO mapreduce.JobSubmitter (JobSubmitter.java:submitJobInternal(198)) - number of splits:1
2016-05-13 14:54:27,998 INFO mapreduce.JobSubmitter (JobSubmitter.java:printTokens(287)) - Submitting tokens for job: job_local416636006_0001
2016-05-13 14:54:28,288 INFO mapreduce.Job (Job.java:submit(1294)) - The url to track the job: http://localhost:8080/
2016-05-13 14:54:28,289 INFO mapreduce.Job (Job.java:monitorAndPrintJob(1339)) - Running job: job_local416636006_0001
2016-05-13 14:54:28,297 INFO mapred.LocalJobRunner (LocalJobRunner.java:createOutputCommitter(471)) - OutputCommitter set in config null
2016-05-13 14:54:28,304 INFO output.FileOutputCommitter (FileOutputCommitter.java:<init>(100)) - File Output Committer Algorithm version is 1
2016-05-13 14:54:28,308 INFO mapred.LocalJobRunner (LocalJobRunner.java:createOutputCommitter(489)) - OutputCommitter is org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter
2016-05-13 14:54:28,406 INFO mapred.LocalJobRunner (LocalJobRunner.java:runTasks(448)) - Waiting for map tasks
2016-05-13 14:54:28,407 INFO mapred.LocalJobRunner (LocalJobRunner.java:run(224)) - Starting task: attempt_local416636006_0001_m_000000_0
2016-05-13 14:54:28,446 INFO output.FileOutputCommitter (FileOutputCommitter.java:<init>(100)) - File Output Committer Algorithm version is 1
2016-05-13 14:54:28,460 INFO mapred.Task (Task.java:initialize(612)) - Using ResourceCalculatorProcessTree : [ ]
2016-05-13 14:54:28,465 INFO mapred.MapTask (MapTask.java:runNewMapper(756)) - Processing split: file:/home/kun/soft/hadoop-2.7.1/input/HTTP_20130313143750.dat:0+2229
2016-05-13 14:54:28,590 INFO mapred.MapTask (MapTask.java:setEquator(1205)) - (EQUATOR) 0 kvi 26214396(104857584)
2016-05-13 14:54:28,590 INFO mapred.MapTask (MapTask.java:init(998)) - mapreduce.task.io.sort.mb: 100
2016-05-13 14:54:28,590 INFO mapred.MapTask (MapTask.java:init(999)) - soft limit at 83886080
2016-05-13 14:54:28,590 INFO mapred.MapTask (MapTask.java:init(1000)) - bufstart = 0; bufvoid = 104857600
2016-05-13 14:54:28,591 INFO mapred.MapTask (MapTask.java:init(1001)) - kvstart = 26214396; length = 6553600
2016-05-13 14:54:28,594 INFO mapred.MapTask (MapTask.java:createSortingCollector(403)) - Map output collector class = org.apache.hadoop.mapred.MapTask$MapOutputBuffer
2016-05-13 14:54:28,598 INFO input.LineRecordReader (LineRecordReader.java:skipUtfByteOrderMark(156)) - Found UTF-8 BOM and skipped it
2016-05-13 14:54:28,602 INFO mapred.LocalJobRunner (LocalJobRunner.java:statusUpdate(591)) -
2016-05-13 14:54:28,603 INFO mapred.MapTask (MapTask.java:flush(1460)) - Starting flush of map output
2016-05-13 14:54:28,603 INFO mapred.MapTask (MapTask.java:flush(1482)) - Spilling map output
2016-05-13 14:54:28,603 INFO mapred.MapTask (MapTask.java:flush(1483)) - bufstart = 0; bufend = 1072; bufvoid = 104857600
2016-05-13 14:54:28,603 INFO mapred.MapTask (MapTask.java:flush(1485)) - kvstart = 26214396(104857584); kvend = 26214312(104857248); length = 85/6553600
2016-05-13 14:54:28,613 INFO mapred.MapTask (MapTask.java:sortAndSpill(1667)) - Finished spill 0
2016-05-13 14:54:28,620 INFO mapred.Task (Task.java:done(1038)) - Task:attempt_local416636006_0001_m_000000_0 is done. And is in the process of committing
2016-05-13 14:54:28,634 INFO mapred.LocalJobRunner (LocalJobRunner.java:statusUpdate(591)) - map
2016-05-13 14:54:28,634 INFO mapred.Task (Task.java:sendDone(1158)) - Task 'attempt_local416636006_0001_m_000000_0' done.
2016-05-13 14:54:28,634 INFO mapred.LocalJobRunner (LocalJobRunner.java:run(249)) - Finishing task: attempt_local416636006_0001_m_000000_0
2016-05-13 14:54:28,635 INFO mapred.LocalJobRunner (LocalJobRunner.java:runTasks(456)) - map task executor complete.
2016-05-13 14:54:28,637 INFO mapred.LocalJobRunner (LocalJobRunner.java:runTasks(448)) - Waiting for reduce tasks
2016-05-13 14:54:28,637 INFO mapred.LocalJobRunner (LocalJobRunner.java:run(302)) - Starting task: attempt_local416636006_0001_r_000000_0
2016-05-13 14:54:28,648 INFO output.FileOutputCommitter (FileOutputCommitter.java:<init>(100)) - File Output Committer Algorithm version is 1
2016-05-13 14:54:28,649 INFO mapred.Task (Task.java:initialize(612)) - Using ResourceCalculatorProcessTree : [ ]
2016-05-13 14:54:28,651 INFO mapred.ReduceTask (ReduceTask.java:run(362)) - Using ShuffleConsumerPlugin: org.apache.hadoop.mapreduce.task.reduce.Shuffle@43161b5e
2016-05-13 14:54:28,663 INFO reduce.MergeManagerImpl (MergeManagerImpl.java:<init>(196)) - MergerManager: memoryLimit=1284138624, maxSingleShuffleLimit=321034656, mergeThreshold=847531520, ioSortFactor=10, memToMemMergeOutputsThreshold=10
2016-05-13 14:54:28,666 INFO reduce.EventFetcher (EventFetcher.java:run(61)) - attempt_local416636006_0001_r_000000_0 Thread started: EventFetcher for fetching Map Completion Events
2016-05-13 14:54:28,720 INFO reduce.LocalFetcher (LocalFetcher.java:copyMapOutput(144)) - localfetcher#1 about to shuffle output of map attempt_local416636006_0001_m_000000_0 decomp: 1118 len: 1122 to MEMORY
2016-05-13 14:54:28,726 INFO reduce.InMemoryMapOutput (InMemoryMapOutput.java:shuffle(100)) - Read 1118 bytes from map-output for attempt_local416636006_0001_m_000000_0
2016-05-13 14:54:28,728 INFO reduce.MergeManagerImpl (MergeManagerImpl.java:closeInMemoryFile(314)) - closeInMemoryFile -> map-output of size: 1118, inMemoryMapOutputs.size() -> 1, commitMemory -> 0, usedMemory ->1118
2016-05-13 14:54:28,730 INFO reduce.EventFetcher (EventFetcher.java:run(76)) - EventFetcher is interrupted.. Returning
2016-05-13 14:54:28,731 INFO mapred.LocalJobRunner (LocalJobRunner.java:statusUpdate(591)) - 1 / 1 copied.
2016-05-13 14:54:28,732 INFO reduce.MergeManagerImpl (MergeManagerImpl.java:finalMerge(674)) - finalMerge called with 1 in-memory map-outputs and 0 on-disk map-outputs
2016-05-13 14:54:28,771 INFO mapred.Merger (Merger.java:merge(606)) - Merging 1 sorted segments
2016-05-13 14:54:28,771 INFO mapred.Merger (Merger.java:merge(705)) - Down to the last merge-pass, with 1 segments left of total size: 1104 bytes
2016-05-13 14:54:28,776 INFO reduce.MergeManagerImpl (MergeManagerImpl.java:finalMerge(751)) - Merged 1 segments, 1118 bytes to disk to satisfy reduce memory limit
2016-05-13 14:54:28,777 INFO reduce.MergeManagerImpl (MergeManagerImpl.java:finalMerge(781)) - Merging 1 files, 1122 bytes from disk
2016-05-13 14:54:28,778 INFO reduce.MergeManagerImpl (MergeManagerImpl.java:finalMerge(796)) - Merging 0 segments, 0 bytes from memory into reduce
2016-05-13 14:54:28,778 INFO mapred.Merger (Merger.java:merge(606)) - Merging 1 sorted segments
2016-05-13 14:54:28,780 INFO mapred.Merger (Merger.java:merge(705)) - Down to the last merge-pass, with 1 segments left of total size: 1104 bytes
2016-05-13 14:54:28,781 INFO mapred.LocalJobRunner (LocalJobRunner.java:statusUpdate(591)) - 1 / 1 copied.
2016-05-13 14:54:28,807 INFO Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(1173)) - mapred.skip.on is deprecated. Instead, use mapreduce.job.skiprecords
2016-05-13 14:54:28,824 INFO mapred.Task (Task.java:done(1038)) - Task:attempt_local416636006_0001_r_000000_0 is done. And is in the process of committing
2016-05-13 14:54:28,837 INFO mapred.LocalJobRunner (LocalJobRunner.java:statusUpdate(591)) - 1 / 1 copied.
2016-05-13 14:54:28,837 INFO mapred.Task (Task.java:commit(1199)) - Task attempt_local416636006_0001_r_000000_0 is allowed to commit now
2016-05-13 14:54:28,839 INFO output.FileOutputCommitter (FileOutputCommitter.java:commitTask(482)) - Saved output of task 'attempt_local416636006_0001_r_000000_0' to file:/home/kun/soft/hadoop-2.7.1/output/4/_temporary/0/task_local416636006_0001_r_000000
2016-05-13 14:54:28,841 INFO mapred.LocalJobRunner (LocalJobRunner.java:statusUpdate(591)) - reduce > reduce
2016-05-13 14:54:28,841 INFO mapred.Task (Task.java:sendDone(1158)) - Task 'attempt_local416636006_0001_r_000000_0' done.
2016-05-13 14:54:28,842 INFO mapred.LocalJobRunner (LocalJobRunner.java:run(325)) - Finishing task: attempt_local416636006_0001_r_000000_0
2016-05-13 14:54:28,842 INFO mapred.LocalJobRunner (LocalJobRunner.java:runTasks(456)) - reduce task executor complete.
2016-05-13 14:54:29,294 INFO mapreduce.Job (Job.java:monitorAndPrintJob(1360)) - Job job_local416636006_0001 running in uber mode : false
2016-05-13 14:54:29,295 INFO mapreduce.Job (Job.java:monitorAndPrintJob(1367)) - map 100% reduce 100%
2016-05-13 14:54:29,296 INFO mapreduce.Job (Job.java:monitorAndPrintJob(1378)) - Job job_local416636006_0001 completed successfully
2016-05-13 14:54:29,308 INFO mapreduce.Job (Job.java:monitorAndPrintJob(1385)) - Counters: 30
File System Counters
FILE: Number of bytes read=7100
FILE: Number of bytes written=578006
FILE: Number of read operations=0
FILE: Number of large read operations=0
FILE: Number of write operations=0
Map-Reduce Framework
Map input records=22
Map output records=22
Map output bytes=1072
Map output materialized bytes=1122
Input split bytes=127
Combine input records=0
Combine output records=0
Reduce input groups=21
Reduce shuffle bytes=1122
Reduce input records=22
Reduce output records=21
Spilled Records=44
Shuffled Maps =1
Failed Shuffles=0
Merged Map outputs=1
GC time elapsed (ms)=0
Total committed heap usage (bytes)=525336576
Shuffle Errors
BAD_ID=0
CONNECTION=0
IO_ERROR=0
WRONG_LENGTH=0
WRONG_MAP=0
WRONG_REDUCE=0
File Input Format Counters
Bytes Read=2229
File Output Format Counters
Bytes Written=542
（第一列为电话号码，第二列为上传流量，第三列为下载流量，第四列为总流量）
134802531041802003809、排序后的结果为：
1350246882310273357437
135604366669542001154
1356043965858924006292
136028465651219381950
13660577991969606969
137191994190200200
1372623050324812468127162
1372623888824812468127162
13760778710120200320
138265441010200200
13922314466300837206728
13925057413631105811121
139262511060200200
1392643565615122001712
150136858582736593686
159201332572031563176
15989002119319381941
182115759611215271539
183201733821895319549
84138413411614325548
8、将此输出数据作为排序的输入数据，通过mapreduce进行排序
<pre name="code" class="java">package cn.nanda.sort;
import java.io.IOException;
import org.apache.commons.lang.StringUtils;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
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 cn.nanda.wordCount.FlowBean;
public class SortMR {
// Mapper
public static class SortMapper extends
Mapper<LongWritable, Text, FlowBean, NullWritable> {
// 拿到一行数据，切分出各字段，封装为一个flowbean，作为key输出
@Override
protected void map(LongWritable key, Text value, Context context)
throws IOException, InterruptedException {
String line = value.toString();
String[] fields = StringUtils.split(line, "\t");
String phoneNB = fields[0];
long up_flow = Long.parseLong(fields[1]);
long d_flow = Long.parseLong(fields[2]);
System.out.println(phoneNB +"#" +up_flow);
context.write(new FlowBean(phoneNB, up_flow, d_flow),NullWritable.get());
}
}
// Reducer
public static class SortReducer extends
Reducer<FlowBean, NullWritable, Text, FlowBean> {
@Override
protected void reduce(FlowBean key, Iterable<NullWritable> values,
Context context) throws IOException, InterruptedException {
String phoneNB = key.getPhoneNB();
context.write(new Text(phoneNB), key);
}
}
public static void main(String[] args) throws Exception {
Configuration conf = new Configuration();
Job job = Job.getInstance(conf);
job.setJarByClass(SortMR.class);
job.setMapperClass(SortMapper.class);
job.setReducerClass(SortReducer.class);
job.setMapOutputKeyClass(FlowBean.class);
job.setMapOutputValueClass(NullWritable.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(FlowBean.class);
FileInputFormat.setInputPaths(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
System.exit(job.waitForCompletion(true)?0:1);
}
}
1372623888824812468127162
1372623050324812468127162
13925057413631105811121
183201733821895319549
1350246882310273357437
13660577991969606969
13922314466300837206728
1356043965858924006292
84138413411614325548
150136858582736593686
159201332572031563176
136028465651219381950
15989002119319381941
1392643565615122001712
182115759611215271539
135604366669542001154
13480253104180200380
13760778710120200320
138265441010200200
139262511060200200
137191994190200200