package recommand;
import java.util.HashMap;
import java.util.Map;
import java.util.regex.Pattern;
import org.apache.hadoop.mapred.JobConf;
public class Recommend {
public static final String HDFS = "hdfs://115.28.167.22:9000";
public static final Pattern DELIMITER = Pattern.compile("[\t,]");
public static void main(String[] args) throws Exception {
Map<String, String> path = new HashMap<String, String>();
path.put("data", "C:\\Users\\Administrator\\Desktop\\maven_hadoop_template-master\\logfile\\small2.csv");
path.put("Step1Input", HDFS + "/user/hdfs/recommend");
path.put("Step1Output", path.get("Step1Input") + "/step1");
path.put("Step2Input", path.get("Step1Output"));
path.put("Step2Output", path.get("Step1Input") + "/step2");
path.put("Step3Input1", path.get("Step1Output"));
path.put("Step3Output1", path.get("Step1Input") + "/step3_1");
path.put("Step3Input2", path.get("Step2Output"));
path.put("Step3Output2", path.get("Step1Input") + "/step3_2");
path.put("Step4Input1", path.get("Step3Output1"));
path.put("Step4Input2", path.get("Step3Output2"));
path.put("Step4Output", path.get("Step1Input") + "/step4");
path.put("Step5Input1", path.get("Step3Output1"));
path.put("Step5Input2", path.get("Step3Output2"));
path.put("Step5Output", path.get("Step1Input") + "/step5");
path.put("Step6Input", path.get("Step5Output"));
path.put("Step6Output", path.get("Step1Input") + "/step6");
Step1.run(path);
Step2.run(path);
Step3.run1(path);
Step3.run2(path);
// Step4.run(path);
Step4_Update.run(path);
Step4_Update2.run(path);
// // hadoop fs -cat /user/hdfs/recommend/step4/part-00000
// JobConf conf = config();
// HdfsDAO hdfs = new HdfsDAO(HDFS, conf);
// hdfs.cat("/user/hdfs/recommend/step4/part-00000");
System.exit(0);
}
public static JobConf config() {
JobConf conf = new JobConf(Recommend.class);
conf.setJobName("Recommand");
//conf.addResource("classpath:/hadoop/core-site.xml");
// conf.addResource("classpath:/hadoop/hdfs-site.xml");
// conf.addResource("classpath:/hadoop/mapred-site.xml");
// conf.set("io.sort.mb", "1024");
return conf;
}
}
package recommand;
import java.io.IOException;
import java.net.URI;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FSDataInputStream;
import org.apache.hadoop.fs.FSDataOutputStream;
import org.apache.hadoop.fs.FileStatus;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IOUtils;
import org.apache.hadoop.mapred.JobConf;
public class HdfsDAO {
private static final String HDFS = "hdfs://115.28.167.22:9000/";
public HdfsDAO(Configuration conf) {
this(HDFS, conf);
}
public HdfsDAO(String hdfs, Configuration conf) {
this.hdfsPath = hdfs;
this.conf = conf;
}
private String hdfsPath;
private Configuration conf;
public static void main(String[] args) throws IOException {
JobConf conf = config();
HdfsDAO hdfs = new HdfsDAO(conf);
// hdfs.copyFile("datafile/item.csv", "/tmp/new");
// hdfs.ls("/tmp/new");
hdfs.rename("/user/hdfs/pagerank/tmp3", "/user/hdfs/pagerank/tmp4");
}
public static JobConf config() {
JobConf conf = new JobConf(HdfsDAO.class);
conf.setJobName("HdfsDAO");
// conf.addResource("classpath:/hadoop/core-site.xml");
// conf.addResource("classpath:/hadoop/hdfs-site.xml");
// conf.addResource("classpath:/hadoop/mapred-site.xml");
return conf;
}
public void mkdirs(String folder) throws IOException {
Path path = new Path(folder);
FileSystem fs = FileSystem.get(URI.create(hdfsPath), conf);
if (!fs.exists(path)) {
fs.mkdirs(path);
System.out.println("Create: " + folder);
}
fs.close();
}
public void rmr(String folder) throws IOException {
Path path = new Path(folder);
FileSystem fs = FileSystem.get(URI.create(hdfsPath), conf);
fs.deleteOnExit(path);
System.out.println("Delete: " + folder);
fs.close();
}
public void rename(String src, String dst) throws IOException {
Path name1 = new Path(src);
Path name2 = new Path(dst);
FileSystem fs = FileSystem.get(URI.create(hdfsPath), conf);
fs.rename(name1, name2);
System.out.println("Rename: from " + src + " to " + dst);
fs.close();
}
public void ls(String folder) throws IOException {
Path path = new Path(folder);
FileSystem fs = FileSystem.get(URI.create(hdfsPath), conf);
FileStatus[] list = fs.listStatus(path);
System.out.println("ls: " + folder);
System.out.println("==========================================================");
for (FileStatus f : list) {
System.out.printf("name: %s, folder: %s, size: %d\n", f.getPath(), f.isDir(), f.getLen());
}
System.out.println("==========================================================");
fs.close();
}
public void createFile(String file, String content) throws IOException {
FileSystem fs = FileSystem.get(URI.create(hdfsPath), conf);
byte[] buff = content.getBytes();
FSDataOutputStream os = null;
try {
os = fs.create(new Path(file));
os.write(buff, 0, buff.length);
System.out.println("Create: " + file);
} finally {
if (os != null)
os.close();
}
fs.close();
}
public void copyFile(String local, String remote) throws IOException {
FileSystem fs = FileSystem.get(URI.create(hdfsPath), conf);
fs.copyFromLocalFile(new Path(local), new Path(remote));
System.out.println("copy from: " + local + " to " + remote);
fs.close();
}
public void download(String remote, String local) throws IOException {
Path path = new Path(remote);
FileSystem fs = FileSystem.get(URI.create(hdfsPath), conf);
fs.copyToLocalFile(path, new Path(local));
System.out.println("download: from" + remote + " to " + local);
fs.close();
}
public void cat(String remoteFile) throws IOException {
Path path = new Path(remoteFile);
FileSystem fs = FileSystem.get(URI.create(hdfsPath), conf);
FSDataInputStream fsdis = null;
System.out.println("cat: " + remoteFile);
try {
fsdis = fs.open(path);
IOUtils.copyBytes(fsdis, System.out, 4096, false);
} finally {
IOUtils.closeStream(fsdis);
fs.close();
}
}
public void location() throws IOException {
// String folder = hdfsPath + "create/";
// String file = "t2.txt";
// FileSystem fs = FileSystem.get(URI.create(hdfsPath), new
// Configuration());
// FileStatus f = fs.getFileStatus(new Path(folder + file));
// BlockLocation[] list = fs.getFileBlockLocations(f, 0, f.getLen());
//
// System.out.println("File Location: " + folder + file);
// for (BlockLocation bl : list) {
// String[] hosts = bl.getHosts();
// for (String host : hosts) {
// System.out.println("host:" + host);
// }
// }
// fs.close();
}
}
package recommand;
import java.io.File;
import java.io.IOException;
import java.util.Iterator;
import java.util.Map;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.FileInputFormat;
import org.apache.hadoop.mapred.FileOutputFormat;
import org.apache.hadoop.mapred.JobClient;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapred.MapReduceBase;
import org.apache.hadoop.mapred.Mapper;
import org.apache.hadoop.mapred.OutputCollector;
import org.apache.hadoop.mapred.Reducer;
import org.apache.hadoop.mapred.Reporter;
import org.apache.hadoop.mapred.RunningJob;
import org.apache.hadoop.mapred.TextInputFormat;
import org.apache.hadoop.mapred.TextOutputFormat;
import org.apache.hadoop.vod.Ejob;
public class Step1 {
public static class Step1_ToItemPreMapper extends MapReduceBase implements Mapper<Object, Text, IntWritable, Text> {
private final static IntWritable k = new IntWritable();
private final static Text v = new Text();
@Override
public void map(Object key, Text value, OutputCollector<IntWritable, Text> output, Reporter reporter) throws IOException {
String[] tokens = Recommend.DELIMITER.split(value.toString());
int userID = Integer.parseInt(tokens[0]);
String itemID = tokens[1];
String pref = tokens[2];
k.set(userID);
v.set(itemID + ":" + pref);
output.collect(k, v);
}
}
public static class Step1_ToUserVectorReducer extends MapReduceBase implements Reducer<IntWritable, Text, IntWritable, Text> {
private final static Text v = new Text();
@Override
public void reduce(IntWritable key, Iterator<Text> values, OutputCollector<IntWritable, Text> output, Reporter reporter) throws IOException {
StringBuilder sb = new StringBuilder();
while (values.hasNext()) {
sb.append("," + values.next());
}
v.set(sb.toString().replaceFirst(",", ""));
output.collect(key, v);
}
}
public static void run(Map<String, String> path) throws IOException {
File jar=Ejob.createTempJar("bin");
Thread.currentThread().setContextClassLoader(Ejob.getClassLoader());
JobConf conf = Recommend.config();
conf.setJar(jar.toString());
String input = path.get("Step1Input");
String output = path.get("Step1Output");
HdfsDAO hdfs = new HdfsDAO(Recommend.HDFS, conf);
// hdfs.rmr(output);
hdfs.rmr(input);
hdfs.mkdirs(input);
hdfs.copyFile(path.get("data"), input);
conf.setMapOutputKeyClass(IntWritable.class);
conf.setMapOutputValueClass(Text.class);
conf.setOutputKeyClass(IntWritable.class);
conf.setOutputValueClass(Text.class);
conf.setMapperClass(Step1_ToItemPreMapper.class);
conf.setCombinerClass(Step1_ToUserVectorReducer.class);
conf.setReducerClass(Step1_ToUserVectorReducer.class);
conf.setInputFormat(TextInputFormat.class);
conf.setOutputFormat(TextOutputFormat.class);
FileInputFormat.setInputPaths(conf, new Path(input));
FileOutputFormat.setOutputPath(conf, new Path(output));
RunningJob job = JobClient.runJob(conf);
while (!job.isComplete()) {
job.waitForCompletion();
}
}
}
package recommand;
import java.io.File;
import java.io.IOException;
import java.util.Iterator;
import java.util.Map;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.FileInputFormat;
import org.apache.hadoop.mapred.FileOutputFormat;
import org.apache.hadoop.mapred.JobClient;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapred.MapReduceBase;
import org.apache.hadoop.mapred.Mapper;
import org.apache.hadoop.mapred.OutputCollector;
import org.apache.hadoop.mapred.Reducer;
import org.apache.hadoop.mapred.Reporter;
import org.apache.hadoop.mapred.RunningJob;
import org.apache.hadoop.mapred.TextInputFormat;
import org.apache.hadoop.mapred.TextOutputFormat;
import org.apache.hadoop.vod.Ejob;
public class Step2 {
public static class Step2_UserVectorToCooccurrenceMapper extends MapReduceBase implements Mapper<LongWritable, Text, Text, IntWritable> {
private final static Text k = new Text();
private final static IntWritable v = new IntWritable(1);
@Override
public void map(LongWritable key, Text values, OutputCollector<Text, IntWritable> output, Reporter reporter) throws IOException {
String[] tokens = Recommend.DELIMITER.split(values.toString());
for (int i = 1; i < tokens.length; i++) {
String itemID = tokens[i].split(":")[0];
for (int j = 1; j < tokens.length; j++) {
String itemID2 = tokens[j].split(":")[0];
k.set(itemID + ":" + itemID2);
output.collect(k, v);
}
}
}
}
public static class Step2_UserVectorToConoccurrenceReducer extends MapReduceBase implements Reducer<Text, IntWritable, Text, IntWritable> {
private IntWritable result = new IntWritable();
@Override
public void reduce(Text key, Iterator<IntWritable> values, OutputCollector<Text, IntWritable> output, Reporter reporter) throws IOException {
int sum = 0;
while (values.hasNext()) {
sum += values.next().get();
}
result.set(sum);
output.collect(key, result);
}
}
public static void run(Map<String, String> path) throws IOException {
File jar=Ejob.createTempJar("bin");
Thread.currentThread().setContextClassLoader(Ejob.getClassLoader());
JobConf conf = Recommend.config();
conf.setJar(jar.toString());
String input = path.get("Step2Input");
String output = path.get("Step2Output");
HdfsDAO hdfs = new HdfsDAO(Recommend.HDFS, conf);
hdfs.rmr(output);
conf.setOutputKeyClass(Text.class);
conf.setOutputValueClass(IntWritable.class);
conf.setMapperClass(Step2_UserVectorToCooccurrenceMapper.class);
conf.setCombinerClass(Step2_UserVectorToConoccurrenceReducer.class);
conf.setReducerClass(Step2_UserVectorToConoccurrenceReducer.class);
conf.setInputFormat(TextInputFormat.class);
conf.setOutputFormat(TextOutputFormat.class);
FileInputFormat.setInputPaths(conf, new Path(input));
FileOutputFormat.setOutputPath(conf, new Path(output));
RunningJob job = JobClient.runJob(conf);
while (!job.isComplete()) {
job.waitForCompletion();
}
}
}
package recommand;
import java.io.File;
import java.io.IOException;
import java.util.Map;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.FileInputFormat;
import org.apache.hadoop.mapred.FileOutputFormat;
import org.apache.hadoop.mapred.JobClient;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapred.MapReduceBase;
import org.apache.hadoop.mapred.Mapper;
import org.apache.hadoop.mapred.OutputCollector;
import org.apache.hadoop.mapred.Reporter;
import org.apache.hadoop.mapred.RunningJob;
import org.apache.hadoop.mapred.TextInputFormat;
import org.apache.hadoop.mapred.TextOutputFormat;
import org.apache.hadoop.vod.Ejob;
public class Step3 {
public static class Step31_UserVectorSplitterMapper extends MapReduceBase implements Mapper<LongWritable, Text, IntWritable, Text> {
private final static IntWritable k = new IntWritable();
private final static Text v = new Text();
@Override
public void map(LongWritable key, Text values, OutputCollector<IntWritable, Text> output, Reporter reporter) throws IOException {
String[] tokens = Recommend.DELIMITER.split(values.toString());
for (int i = 1; i < tokens.length; i++) {
String[] vector = tokens[i].split(":");
int itemID = Integer.parseInt(vector[0]);
String pref = vector[1];
k.set(itemID);
v.set(tokens[0] + ":" + pref);
output.collect(k, v);
}
}
}
public static void run1(Map<String, String> path) throws IOException {
File jar=Ejob.createTempJar("bin");
Thread.currentThread().setContextClassLoader(Ejob.getClassLoader());
JobConf conf = Recommend.config();
conf.setJar(jar.toString());
String input = path.get("Step3Input1");
String output = path.get("Step3Output1");
HdfsDAO hdfs = new HdfsDAO(Recommend.HDFS, conf);
hdfs.rmr(output);
conf.setOutputKeyClass(IntWritable.class);
conf.setOutputValueClass(Text.class);
conf.setMapperClass(Step31_UserVectorSplitterMapper.class);
conf.setInputFormat(TextInputFormat.class);
conf.setOutputFormat(TextOutputFormat.class);
FileInputFormat.setInputPaths(conf, new Path(input));
FileOutputFormat.setOutputPath(conf, new Path(output));
RunningJob job = JobClient.runJob(conf);
while (!job.isComplete()) {
job.waitForCompletion();
}
}
public static class Step32_CooccurrenceColumnWrapperMapper extends MapReduceBase implements Mapper<LongWritable, Text, Text, IntWritable> {
private final static Text k = new Text();
private final static IntWritable v = new IntWritable();
@Override
public void map(LongWritable key, Text values, OutputCollector<Text, IntWritable> output, Reporter reporter) throws IOException {
String[] tokens = Recommend.DELIMITER.split(values.toString());
k.set(tokens[0]);
v.set(Integer.parseInt(tokens[1]));
output.collect(k, v);
}
}
public static void run2(Map<String, String> path) throws IOException {
File jar=Ejob.createTempJar("bin");
Thread.currentThread().setContextClassLoader(Ejob.getClassLoader());
JobConf conf = Recommend.config();
conf.setJar(jar.toString());
String input = path.get("Step3Input2");
String output = path.get("Step3Output2");
HdfsDAO hdfs = new HdfsDAO(Recommend.HDFS, conf);
hdfs.rmr(output);
conf.setOutputKeyClass(Text.class);
conf.setOutputValueClass(IntWritable.class);
conf.setMapperClass(Step32_CooccurrenceColumnWrapperMapper.class);
conf.setInputFormat(TextInputFormat.class);
conf.setOutputFormat(TextOutputFormat.class);
FileInputFormat.setInputPaths(conf, new Path(input));
FileOutputFormat.setOutputPath(conf, new Path(output));
RunningJob job = JobClient.runJob(conf);
while (!job.isComplete()) {
job.waitForCompletion();
}
}
}
package recommand;
import java.io.File;
import java.io.IOException;
import java.util.HashMap;
import java.util.Iterator;
import java.util.Map;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.JobConf;
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.FileSplit;
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.vod.Ejob;
public class Step4_Update {
public static class Step4_PartialMultiplyMapper extends Mapper<LongWritable, Text, Text, Text> {
private String flag;// A同现矩阵 or B评分矩阵
@Override
protected void setup(Context context) throws IOException, InterruptedException {
FileSplit split = (FileSplit) context.getInputSplit();
flag = split.getPath().getParent().getName();// 判断读的数据集
// System.out.println(flag);
}
@Override
public void map(LongWritable key, Text values, Context context) throws IOException, InterruptedException {
String[] tokens = Recommend.DELIMITER.split(values.toString());
if (flag.equals("step3_2")) {// 同现矩阵
String[] v1 = tokens[0].split(":");
String itemID1 = v1[0];
String itemID2 = v1[1];
String num = tokens[1];
Text k = new Text(itemID1);
Text v = new Text("A:" + itemID2 + "," + num);
context.write(k, v);
// System.out.println(k.toString() + " " + v.toString());
} else if (flag.equals("step3_1")) {// 评分矩阵
String[] v2 = tokens[1].split(":");
String itemID = tokens[0];
String userID = v2[0];
String pref = v2[1];
Text k = new Text(itemID);
Text v = new Text("B:" + userID + "," + pref);
context.write(k, v);
// System.out.println(k.toString() + " " + v.toString());
}
}
}
public static class Step4_AggregateReducer extends Reducer<Text, Text, Text, Text> {
@Override
public void reduce(Text key, Iterable<Text> values, Context context) throws IOException, InterruptedException {
System.out.println(key.toString() + ":");
Map<String, String> mapA = new HashMap<String, String>();
Map<String, String> mapB = new HashMap<String, String>();
for (Text line : values) {
String val = line.toString();
System.out.println(val);
if (val.startsWith("A:")) {
String[] kv = Recommend.DELIMITER.split(val.substring(2));
mapA.put(kv[0], kv[1]);
} else if (val.startsWith("B:")) {
String[] kv = Recommend.DELIMITER.split(val.substring(2));
mapB.put(kv[0], kv[1]);
}
}
double result = 0;
Iterator<String> iter = mapA.keySet().iterator();
while (iter.hasNext()) {
String mapk = iter.next();// itemID
int num = Integer.parseInt(mapA.get(mapk));
Iterator<String> iterb = mapB.keySet().iterator();
while (iterb.hasNext()) {
String mapkb = iterb.next();// userID
double pref = Double.parseDouble(mapB.get(mapkb));
result = num * pref;// 矩阵乘法相乘计算
Text k = new Text(mapkb);
Text v = new Text(mapk + "," + result);
context.write(k, v);
System.out.println(k.toString() + " " + v.toString());
}
}
}
}
public static void run(Map<String, String> path) throws IOException, InterruptedException, ClassNotFoundException {
File jar=Ejob.createTempJar("bin");
Thread.currentThread().setContextClassLoader(Ejob.getClassLoader());
JobConf conf = Recommend.config();
conf.setJar(jar.toString());
String input1 = path.get("Step5Input1");
String input2 = path.get("Step5Input2");
String output = path.get("Step5Output");
HdfsDAO hdfs = new HdfsDAO(Recommend.HDFS, conf);
hdfs.rmr(output);
Job job = new Job(conf);
job.setJarByClass(Step4_Update.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(Text.class);
job.setMapperClass(Step4_Update.Step4_PartialMultiplyMapper.class);
job.setReducerClass(Step4_Update.Step4_AggregateReducer.class);
job.setInputFormatClass(TextInputFormat.class);
job.setOutputFormatClass(TextOutputFormat.class);
FileInputFormat.setInputPaths(job, new Path(input1), new Path(input2));
FileOutputFormat.setOutputPath(job, new Path(output));
job.waitForCompletion(true);
}
}
package recommand;
import java.io.File;
import java.io.IOException;
import java.util.HashMap;
import java.util.Iterator;
import java.util.Map;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.JobConf;
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.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.vod.Ejob;
public class Step4_Update2 {
public static class Step4_RecommendMapper extends Mapper<LongWritable, Text, Text, Text> {
@Override
public void map(LongWritable key, Text values, Context context) throws IOException, InterruptedException {
String[] tokens = Recommend.DELIMITER.split(values.toString());
Text k = new Text(tokens[0]);
Text v = new Text(tokens[1]+","+tokens[2]);
context.write(k, v);
}
}
public static class Step4_RecommendReducer extends Reducer<Text, Text, Text, Text> {
@Override
public void reduce(Text key, Iterable<Text> values, Context context) throws IOException, InterruptedException {
System.out.println(key.toString() + ":");
Map<String, Double> map = new HashMap<String, Double>();// 结果
for (Text line : values) {
System.out.println(line.toString());
String[] tokens = Recommend.DELIMITER.split(line.toString());
String itemID = tokens[0];
Double score = Double.parseDouble(tokens[1]);
if (map.containsKey(itemID)) {
map.put(itemID, map.get(itemID) + score);// 矩阵乘法求和计算
} else {
map.put(itemID, score);
}
}
Iterator<String> iter = map.keySet().iterator();
while (iter.hasNext()) {
String itemID = iter.next();
double score = map.get(itemID);
Text v = new Text(itemID + "," + score);
context.write(key, v);
}
}
}
public static void run(Map<String, String> path) throws IOException, InterruptedException, ClassNotFoundException {
File jar=Ejob.createTempJar("bin");
Thread.currentThread().setContextClassLoader(Ejob.getClassLoader());
JobConf conf = Recommend.config();
conf.setJar(jar.toString());
String input = path.get("Step6Input");
String output = path.get("Step6Output");
HdfsDAO hdfs = new HdfsDAO(Recommend.HDFS, conf);
hdfs.rmr(output);
Job job = new Job(conf);
job.setJarByClass(Step4_Update2.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(Text.class);
job.setMapperClass(Step4_Update2.Step4_RecommendMapper.class);
job.setReducerClass(Step4_Update2.Step4_RecommendReducer.class);
job.setInputFormatClass(TextInputFormat.class);
job.setOutputFormatClass(TextOutputFormat.class);
FileInputFormat.setInputPaths(job, new Path(input));
FileOutputFormat.setOutputPath(job, new Path(output));
job.waitForCompletion(true);
}
}