在Loop之后，全局变量的值不会改变
我正在开发一个hadoop项目。我想在某一天找到客户，然后在当天写下那些最大消费的客户。在我的reducer类中，由于某种原因，全局变量 max 在for循环后不会改变它的值。
编辑我想在某一天找到最大消费的客户。我已经设法在我想要的日期找到客户，但我在Reducer类中遇到了问题。这是代码：
编辑＃2 我已经知道值（消费）是自然数。所以在我的输出文件中，我想成为某一天的客户，最大消费。
编辑＃3 我的输入文件由许多数据组成。它有三列;客户的ID，时间戳（yyyy-mm-DD HH：mm：ss）和消费量
驱动程序类
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.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
public class alicanteDriver {
public static void main(String[] args) throws Exception {
long t_start = System.currentTimeMillis();
long t_end;
Configuration conf = new Configuration();
Job job = Job.getInstance(conf, "Alicante");
job.setJarByClass(alicanteDriver.class);
job.setMapperClass(alicanteMapperC.class);
//job.setCombinerClass(alicanteCombiner.class);
job.setPartitionerClass(alicantePartitioner.class);
job.setNumReduceTasks(2);
job.setReducerClass(alicanteReducerC.class);
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(IntWritable.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
FileInputFormat.addInputPath(job, new Path("/alicante_1y.txt"));
FileOutputFormat.setOutputPath(job, new Path("/alicante_output"));
job.waitForCompletion(true);
t_end = System.currentTimeMillis();
System.out.println((t_end-t_start)/1000);
}
}
Mapper类
import java.io.IOException;
import java.text.ParseException;
import java.text.SimpleDateFormat;
import java.util.Date;
import java.util.StringTokenizer;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
public class alicanteMapperC extends
Mapper<LongWritable, Text, Text, IntWritable> {
String Customer = new String();
SimpleDateFormat ft = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
Date t = new Date();
IntWritable Consumption = new IntWritable();
int counter = 0;
// new vars
int max = 0;
@Override
public void map(LongWritable key, Text value, Context context)
throws IOException, InterruptedException {
Date d2 = null;
try {
d2 = ft.parse("2013-07-01 01:00:00");
} catch (ParseException e1) {
// TODO Auto-generated catch block
e1.printStackTrace();
}
if (counter > 0) {
String line = value.toString();
StringTokenizer itr = new StringTokenizer(line, ",");
while (itr.hasMoreTokens()) {
Customer = itr.nextToken();
try {
t = ft.parse(itr.nextToken());
} catch (ParseException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
Consumption.set(Integer.parseInt(itr.nextToken()));
//sort out as many values as possible
if(Consumption.get() > max) {
max = Consumption.get();
}
//find customers in a certain date
if (t.compareTo(d2) == 0 && Consumption.get() == max) {
context.write(new Text(Customer), Consumption);
}
}
}
counter++;
}
}
减速机等级
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;
import com.google.common.collect.Iterables;
public class alicanteReducerC extends
Reducer<Text, IntWritable, Text, IntWritable> {
public void reduce(Text key, Iterable<IntWritable> values, Context context)
throws IOException, InterruptedException {
int max = 0; //this var
// declaration of Lists
List<Text> l1 = new ArrayList<Text>();
List<IntWritable> l2 = new ArrayList<IntWritable>();
for (IntWritable val : values) {
if (val.get() > max) {
max = val.get();
}
l1.add(key);
l2.add(val);
}
for (int i = 0; i < l1.size(); i++) {
if (l2.get(i).get() == max) {
context.write(key, new IntWritable(max));
}
}
}
}
输入文件的某些值
C11FA586148,2013-07-01 01:00:00,3
C11FA586152,2015-09-01 15:22:22,3
C11FA586168,2015-02-01 15:22:22,1
C11FA586258,2013-07-01 01:00:00,5
C11FA586413,2013-07-01 01:00:00,5
C11UA487446,2013-09-01 15:22:22,3
C11UA487446,2013-07-01 01:00:00,3
C11FA586148,2013-07-01 01:00:00,4
输出
C11FA586258 5
C11FA586413 5
我在论坛上搜索了几个小时，但仍然找不到问题。有什么想法吗？
2 个答案:
答案 0 :(得分：1)
这里是重构代码： 您可以传递/更改消费日期的具体值。在这种情况下，您不需要减速机。我的第一个答案是从输入中查询max comsumption，这个答案是从输入中查询用户提供的消耗。
setup方法将为mapper.maxConsumption.date获取用户提供的值，并将其传递给map方法。减速器中的cleaup方法扫描所有最大消费客户并在输入中写入最终最大值（例如，在这种情况下为5） - 请参阅详细执行日志的屏幕截图：
以：
运行hadoop jar maxConsumption.jar -Dmapper.maxConsumption.date="2013-07-01 01:00:00" Data/input.txt output/maxConsupmtion5
#input:
C11FA586148,2013-07-01 01:00:00,3
C11FA586152,2015-09-01 15:22:22,3
C11FA586168,2015-02-01 15:22:22,1
C11FA586258,2013-07-01 01:00:00,5
C11FA586413,2013-07-01 01:00:00,5
C11UA487446,2013-09-01 15:22:22,3
C11UA487446,2013-07-01 01:00:00,3
C11FA586148,2013-07-01 01:00:00,4
#output:
C11FA586258 5
C11FA586413 5
public class maxConsumption extends Configured implements Tool{
public static class DataMapper extends Mapper<Object, Text, Text, IntWritable> {
SimpleDateFormat ft = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
Date dateInFile, filterDate;
int lineno=0;
private final static Text customer = new Text();
private final static IntWritable consumption = new IntWritable();
private final static Text maxConsumptionDate = new Text();
public void setup(Context context) {
Configuration config = context.getConfiguration();
maxConsumptionDate.set(config.get("mapper.maxConsumption.date"));
}
public void map(Object key, Text value, Context context) throws IOException, InterruptedException{
try{
lineno++;
filterDate = ft.parse(maxConsumptionDate.toString());
//map data from line/file
String[] fields = value.toString().split(",");
customer.set(fields[0].trim());
dateInFile = ft.parse(fields[1].trim());
consumption.set(Integer.parseInt(fields[2].trim()));
if(dateInFile.equals(filterDate)) //only send to reducer if date filter matches....
context.write(new Text(customer), consumption);
}catch(Exception e){
System.err.println("Invaid Data at line: " + lineno + " Error: " + e.getMessage());
}
}
}
public static class DataReducer extends Reducer<Text, IntWritable, Text, IntWritable> {
LinkedHashMap<String, Integer> maxConsumption = new LinkedHashMap<String,Integer>();
@Override
public void reduce(Text key, Iterable<IntWritable> values, Context context)
throws IOException, InterruptedException {
int max=0;
System.out.print("reducer received: " + key + " [ ");
for(IntWritable value: values){
System.out.print( value.get() + " ");
if(value.get() > max)
max=value.get();
}
System.out.println( " ]");
System.out.println(key.toString() + " max is " + max);
maxConsumption.put(key.toString(), max);
}
@Override
protected void cleanup(Context context)
throws IOException, InterruptedException {
int max=0;
//first find the max from reducer
for (String key : maxConsumption.keySet()){
System.out.println("cleaup customer : " + key.toString() + " consumption : " + maxConsumption.get(key)
+ " max: " + max);
if(maxConsumption.get(key) > max)
max=maxConsumption.get(key);
}
System.out.println("final max is: " + max);
//write only the max value from map
for (String key : maxConsumption.keySet()){
if(maxConsumption.get(key) == max)
context.write(new Text(key), new IntWritable(maxConsumption.get(key)));
}
}
}
public static void main(String[] args) throws Exception {
int res = ToolRunner.run(new Configuration(), new maxConsumption(), args);
System.exit(res);
}
public int run(String[] args) throws Exception {
if (args.length != 2) {
System.err.println("Usage: -Dmapper.maxConsumption.date=\"2013-07-01 01:00:00\" <in> <out>");
System.exit(2);
}
Configuration conf = this.getConf();
Job job = Job.getInstance(conf, "get-max-consumption");
job.setJarByClass(maxConsumption.class);
job.setMapperClass(DataMapper.class);
job.setReducerClass(DataReducer.class);
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(IntWritable.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
FileInputFormat.addInputPath(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
FileSystem fs = null;
Path dstFilePath = new Path(args[1]);
try {
fs = dstFilePath.getFileSystem(conf);
if (fs.exists(dstFilePath))
fs.delete(dstFilePath, true);
} catch (IOException e1) {
e1.printStackTrace();
}
return job.waitForCompletion(true) ? 0 : 1;
}
}
答案 1 :(得分：0)
可能所有转到减速器的值都小于0.尝试使用最小值来确定变量是否变化。
max = MIN_VALUE;
根据你所说的，输出应该只有0（在这里，reducers中的最大值是0）或没有输出（所有值都小于0）。另外，看看这个
context.write(key, new IntWritable());
应该是
context.write(key, new IntWritable(max));
if (counter > 0) {
我想，你得到这样的东西吧？ ＆＃34; customer，2013-07-01 01：00：00,2，...＆＃34;如果是这种情况并且您已经在过滤值，则应将max变量声明为local，而不是在mapper范围内，它会影响多个客户。
围绕这个问题有很多问题......你可以解释每个映射器的输入以及你想要做什么。
EDIT2：根据你的回答，我会尝试这个
import java.io.IOException;
import java.text.ParseException;
import java.text.SimpleDateFormat;
import java.util.Date;
import java.util.StringTokenizer;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
public class AlicanteMapperC extends Mapper<LongWritable, Text, Text, IntWritable> {
private final int max = 5;
private SimpleDateFormat ft = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
@Override
public void map(LongWritable key, Text value, Context context)
throws IOException, InterruptedException {
Date t = null;
String[] line = value.toString().split(",");
String customer = line[0];
try {
t = ft.parse(line[1]);
} catch (ParseException e) {
// TODO Auto-generated catch block
throw new RuntimeException("something wrong with the date!" + line[1]);
}
Integer consumption = Integer.parseInt(line[2]);
//find customers in a certain date
if (t.compareTo(ft.parse("2013-07-01 01:00:00")) == 0 && consumption == max) {
context.write(new Text(customer), new IntWritable(consumption));
}
counter++;
}
}
和reducer非常简单，每个客户发出1条记录
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;
import com.google.common.collect.Iterables;
public class AlicanteReducerC extends
Reducer<Text, IntWritable, Text, IntWritable> {
public void reduce(Text key, Iterable<IntWritable> values, Context context)
throws IOException, InterruptedException {
//We already now that it is 5
context.write(key, new IntWritable(5));
//If you want something different, for example report customer with different values, you could iterate over the iterator like this
//for (IntWritable val : values) {
// context.write(key, new IntWritable(val));
//}
}
}
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