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package mobvista.dmp.datasource.gender;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.compress.GzipCodec;
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;
import java.io.IOException;
import java.math.BigDecimal;
import java.util.HashMap;
import java.util.Map;
import java.util.Set;
public class CalcPackageGenderMR {
/**
* author:liushuai
*
* @throws InterruptedException
* @throws IOException
* @throws ClassNotFoundException date :2017-01-18
* desc : 计算每个包名字下面性别所占比例
*/
public static void main(String[] args) throws ClassNotFoundException, IOException, InterruptedException {
Configuration conf = new Configuration();
conf.set("mapreduce.map.speculative", "true");
conf.set("mapreduce.reduce.speculative", "true");
conf.set("mapreduce.task.io.sort.mb", "500");
conf.set("mapreduce.reduce.java.opts", "-Xmx1536m");
conf.set("mapreduce.reduce.memory.mb", "2048");
conf.set("mapreduce.reduce.shuffle.parallelcopies", "50");
String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
Job job = Job.getInstance(conf, "CalcPackageGenderMR");
FileOutputFormat.setCompressOutput(job, true);
FileOutputFormat.setOutputCompressorClass(job, GzipCodec.class);
job.setJarByClass(CalcPackageGenderMR.class);
job.setMapperClass(CalcPackageGenderMapper.class);
job.setReducerClass(CalcPackageGenderReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(Text.class);
FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
System.exit(job.waitForCompletion(true) ? 0 : 1);
}
public static class CalcPackageGenderMapper extends Mapper<LongWritable, Text, Text, Text> {
Text outKey = new Text();
Text outValue = new Text();
public void map(LongWritable key, Text value, Context context) {
try {
String line = value.toString();
String[] fields = MRUtils.SPLITTER.split(line, -1);
if (fields.length != 5) {
return;
}
String[] packages = MRUtils.SPLITTER1.split(fields[2], -1);
String gender = "";
if (fields[3].equals("m")) { //gender
if (packages.length >= 30 || packages.length <= 3) {
gender = "null";
} else {
gender = fields[3];
}
} else {
gender = fields[3];
}
for (int i = 0; i < packages.length; i++) {
if (packages[i].length() < 2) {
continue;
}
outKey.set(packages[i]);
outValue.set(gender);
context.write(outKey, outValue);
}
} catch (Exception e) {
return;
}
}
}
public static class CalcPackageGenderReducer extends Reducer<Text, Text, Text, Text> {
Text outValue = new Text();
public void reduce(Text key, Iterable<Text> values, Context context) {
try {
StringBuilder value = new StringBuilder();
Map<String, Integer> genderNum = new HashMap<String, Integer>();
int inNum = 0; //总的数量
int valid = 0; //有性别标签的数量
int mGender = 0; //男性的数量
int fGender = 0;
BigDecimal gaRatioDouble = null; //小数转换
double mRatio = 0.0;//男性占总性别标签的比例
for (Text val : values) {
String pack = val.toString();
Integer sum = genderNum.get(pack);
if (sum == null) {
sum = 1;
} else {
sum++;
}
genderNum.put(pack, sum);
if (!pack.equals("null")) {
if (pack.equals("m")) {
mGender += 1;
} else if (pack.equals("f")) {
fGender += 1;
}
valid += 1;//有性别标签就+1
}
inNum += 1;//不管有没有性别标签都+1
}
Set<String> set = genderNum.keySet();
for (String name : set) {
int num = genderNum.get(name);
value.append("|"); //每个包下的性别标签加到一起
value.append(name);
value.append(":");
value.append(num);
}
if (valid != 0) {
mRatio = (double) (mGender) / valid;
}
outValue.set(MRUtils.JOINER.join(inNum, valid, mGender, fGender, mRatio, value.toString()));
context.write(key, outValue);
} catch (Exception e) {
return;
}
}
}
}