Hadoop和HBase的新功能。让我用一个例子来解释我的问题。为简洁起见,数据变得很小。从Reducer中的HBase中读取数据
假设我们有一个名为item.log的文件,它包含以下信息。
ITEM-1,PRODUCT-1 ITEM-2,PRODUCT-1 ITEM-3,PRODUCT-2 ITEM-4,PRODUCT-2 ITEM-5,PRODUCT-3 ITEM-6,PRODUCT-1 ITEM-7,PRODUCT-1 ITEM-8,PRODUCT-2 ITEM-9,PRODUCT-1
我有如下的地图减少代码,
package org.sanjus.hadoop;
import java.io.IOException;
import java.util.Iterator;
import org.apache.hadoop.fs.Path;
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.TextInputFormat;
import org.apache.hadoop.mapred.TextOutputFormat;
public class ProductMapReduce {
public static class Map extends MapReduceBase implements Mapper<LongWritable, Text, Text, LongWritable> {
public void map(LongWritable key, Text value, OutputCollector<Text, LongWritable> output, Reporter reporter) throws IOException {
String[] columns = value.toString().split(",");
if (columns.length != 2) {
System.out.println("Bad line/value " + value);
return;
}
Text word = new Text(columns[1]);
LongWritable counter = new LongWritable(1L);
output.collect(word, counter);
}
}
public static class Reduce extends MapReduceBase implements Reducer<Text, LongWritable, Text, LongWritable> {
public void reduce(Text key, Iterator<LongWritable> iterator, OutputCollector<Text, LongWritable> output, Reporter reporter) throws IOException {
long sum = 0L;
while (iterator.hasNext()) {
sum += iterator.next().get();
}
output.collect(key, new LongWritable(sum));
}
}
public static void main(String[] args) throws IOException {
JobConf conf = new JobConf(ProductMapReduce.class);
conf.setJobName("Product Analyzer");
conf.setOutputKeyClass(Text.class);
conf.setOutputValueClass(LongWritable.class);
conf.setMapperClass(Map.class);
conf.setCombinerClass(Reduce.class);
conf.setReducerClass(Reduce.class);
conf.setInputFormat(TextInputFormat.class);
conf.setOutputFormat(TextOutputFormat.class);
FileInputFormat.setInputPaths(conf, new Path(args[0]));
FileOutputFormat.setOutputPath(conf, new Path(args[1]));
JobClient.runJob(conf);
}
}
LABEL 1:地图后输出减少低于:
PRODUCT-1 5 PRODUCT-2 3 PRODUCT-3 1
这里是一个问题:
我在HBase中有一个表,它具有以下信息如下。
PRODUCT-1 10$ PRODUCT-2 20$ PRODUCT-3 30$
问题/需求:我想要的降低相的输出作为减少输出的合并在“LABEL 1:”及以上
HBase的表中规定PRODUCT-1 10$ * 5 = 50$ PRODUCT-2 20$ * 3 = 60$ PRODUCT-3 30$ * 1 = 30$
基本上,密钥是PRODUCT-1,该密钥的值为10 $,同一密钥的值为5,两个值相乘。 ($符号是为了解)
注:我发现的例子是基于输入或输出到HBase。我的情况是,输入和输出将是HDFS中的文件,而我需要使用HBase表中的信息处理reducer输出。
在你的reducer中,你扩展了TableReducer类吗? – Shash
@shash,我在我的reduce实现中扩展了'org.apache.hadoop.mapreduce.Reducer'类。 –