[英]Global variable's value doesn't change after for Loop
我正在開發一個 hadoop 項目。 我想找到某一天的客戶,然后寫出當天消費量最大的那些。 在我的 reducer 類中,由於某種原因,全局變量max在 for 循環后不會改變它的值。
編輯我想找到某一天消費量最大的客戶。 我已經設法在我想要的日期找到客戶,但我在我的 Reducer 課程中遇到了問題。 這是代碼:
編輯 #2我已經知道值(消耗)是自然數。 因此,在我的輸出文件中,我只想成為某天消費量最大的客戶。
編輯 #3我的輸入文件由許多數據組成。 它有三列; 客戶的 id、時間戳 (yyyy-mm-DD HH:mm:ss) 和消費
驅動程序類
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);
}
}
映射器類
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++;
}
}
減速機類
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));
}
}
}
}
輸入文件的一些值
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
輸出應該是
C11FA586258 5
C11FA586413 5
我在論壇上搜索了幾個小時,仍然找不到問題。 有任何想法嗎?
這是重構后的代碼:您可以傳遞/更改消費日期的特定值。 在這種情況下,您不需要減速器。 我的第一個答案是從輸入中查詢最大消耗,這個答案是從輸入中查詢用戶提供的消耗。
setup
方法將獲取用戶提供的mapper.maxConsumption.date
值並將它們傳遞給map
方法。
cleaup
方法掃描所有最大消費客戶並在輸入中寫入最終最大值(即,在這種情況下為 5) - 有關詳細執行日志,請參見屏幕截圖:
運行為:
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;
}
}
可能所有進入您的減速器的值都在 0 以下。嘗試使用 min 值來確定您的變量是否發生變化。
max = MIN_VALUE;
根據您的說法,輸出應僅為 0(在此減速器中的最大值為 0)或無輸出(所有值均小於 0)。 還有,看這個
context.write(key, new IntWritable());
它應該是
context.write(key, new IntWritable(max));
編輯:我剛剛看到你的 Mapper 類,它有很多問題。 以下代碼跳過每個映射器中的第一個元素。 為什么?
if (counter > 0) {
我猜,你得到這樣的東西對嗎? "customer, 2013-07-01 01:00:00, 2,..." 如果是這種情況並且您已經在過濾值,您應該將 max 變量聲明為本地變量,而不是在映射器范圍內,它會影響多個客戶。
關於這個有很多問題..你可以解釋你對每個映射器的輸入以及你想要做什么。
EDIT2:根據你的回答,我會試試這個
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 非常簡單地為每個客戶發出 1 條記錄
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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