• 重新认识mapreduce


    写这篇文章,是因为最近遇到了mapreduce的二次排序问题。以前的理解不完全正确。首先看一下mapreduce的过程

    相信这张图熟悉MR的人都应该见过,再来一张图

    wordcount也不细说了,hadoop里面的hello,world

    之前我的理解是map过来的<k,v>会形成(k,<v1,v2,v3...>)的格式,并且按照这种思路写出来不少的mapreduce程序,而且没有错。

    后来自定义Writable对象,封装一组值作为key,也没有什么问题,而且一直认为key只要在compareTo中重写 了方法就万事大吉,而且compareTo返回0的会作为相同的key。误区就在这里,之前一直认为key相同的value会合并到一个"list"中-。这句话就有错,key是key,value是value,根本不会将key对应的value合并在一起,真实情况是默认将key相同(compareTo返回0的)的合并成了一组,在组相同的里面去foreach里面的value,如果是自定义key的话你可以将key打印一下,或发现key并不相同。

    上代码:

    public class Entry implements WritableComparable<Entry> {
        private String yearMonth;
        private int count;
    
        public Entry() {
        }
    
        @Override
        public int compareTo(Entry entry) {
            int result = this.yearMonth.compareTo(entry.getYearMonth());
            if (result == 0) {
                result = Integer.compare(count, entry.getCount());
            }
            return result;
        }
    
        @Override
        public void write(DataOutput dataOutput) throws IOException {
            dataOutput.writeUTF(yearMonth);
            dataOutput.writeInt(count);
        }
    
        @Override
        public void readFields(DataInput dataInput) throws IOException {
            this.yearMonth = dataInput.readUTF();
            this.count = dataInput.readInt();
        }
    
        public String getYearMonth() {
            return yearMonth;
        }
    
        public void setYearMonth(String yearMonth) {
            this.yearMonth = yearMonth;
        }
    
        public int getCount() {
            return count;
        }
    
        public void setCount(int count) {
            this.count = count;
        }
    
        
    
        
        @Override
        public String toString() {
            return yearMonth;
        }
    }

    自定义分区 EntryPartitioner.java

    public class EntryPartitioner extends Partitioner<Entry, Text> {
    
        @Override
        public int getPartition(Entry entry, Text paramVALUE, int numberPartitions) {
            return Math.abs((entry.getYearMonth().hashCode() % numberPartitions));
        }
    }

    自定义分组 

    public class EntryGroupingComparator extends WritableComparator {
        public EntryGroupingComparator() {
            super(Entry.class, true);
        }
    
        @Override
        public int compare(WritableComparable a, WritableComparable b) {
            Entry a1 = (Entry) a;
            Entry b1 = (Entry) b;
            return a1.getYearMonth().compareTo(b1.getYearMonth());
        }
    }

    mapper类

    public class SecondarySortMapper extends
            Mapper<LongWritable, Text, Entry, Text> {
    
        private Entry entry = new Entry();
        private Text value = new Text();
    
        @Override
        protected void map(LongWritable key, Text lines, Context context)
                throws IOException, InterruptedException {
            String line = lines.toString();
            String[] tokens = line.split(",");
            String yearMonth = tokens[0] + "-" + tokens[1];
            int count = Integer.parseInt(tokens[2]);
            
            entry.setYearMonth(yearMonth);
            entry.setCount(count);
            value.set(tokens[2]);
            context.write(entry, value);
            
        }
    }

    reducer类

    public class SecondarySortReducer extends Reducer<Entry, Text, Entry, Text> {
        @Override
        protected void reduce(Entry key, Iterable<Text> values, Context context)
                throws IOException, InterruptedException {
            System.out.println("-----------------华丽的分割线-----------------");
            StringBuilder builder = new StringBuilder();
            for (Text value : values) {
                System.out.println(key+"==>"+value);
                builder.append(value.toString());
                builder.append(",");
            }
            context.write(key, new Text(builder.toString()));
        }
    }

    reducer中打印出来的跟原来想的不一样,一组的值除了自定义分组的属性相同外,其他的属性有不同的。看来以前是自己理解不够深入啊,特此写出,以示警戒

     
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  • 原文地址:https://www.cnblogs.com/rilweic/p/6078583.html
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