What exactly is output of mapper and reducer function

问题

This is a follow up question of Extracting rows containing specific value using mapReduce and hadoop
Mapper function

public static class MapForWordCount extends Mapper<Object, Text, Text, IntWritable>{

private IntWritable saleValue = new IntWritable();
private Text rangeValue = new Text();

public void map(Object key, Text value, Context con) throws IOException, InterruptedException
{
    String line = value.toString();
    String[] words = line.split(",");
    for(String word: words )
    {
        if(words[3].equals("40")){  
            saleValue.set(Integer.parseInt(words[0]));
            rangeValue.set(words[3]);
            con.write( rangeValue , saleValue );
        }
    }
}   
}

Reducer function

public static class ReduceForWordCount extends Reducer<Text, IntWritable, Text, IntWritable>  
{  
    private IntWritable result = new IntWritable();  
    public void reduce(Text word, Iterable<IntWritable> values, Context con) throws IOException, InterruptedException  
    {  
        for(IntWritable value : values)  
        {  
            result.set(value.get());  
            con.write(word, result);  
        }  
    }  
}

Output obtained is

EDIT 1 : But the Expected output is

40 102  
40 104  
40 105

What am I doing wrong ?

What exactly is happening here in mapper and reducer function ?

回答1:

In the context of the original question - you don't need the loop not in the mapper nor in the reducer as you are duplicating entries:

public static class MapForWordCount extends Mapper<Object, Text, Text, IntWritable>{

private IntWritable saleValue = new IntWritable();
private Text rangeValue = new Text();

public void map(Object key, Text value, Context con) throws IOException, InterruptedException
{
    String line = value.toString();
    String[] words = line.split(",");
    if(words[3].equals("40")){  
       saleValue.set(Integer.parseInt(words[0]));
       rangeValue.set(words[3]);
       con.write(rangeValue , saleValue );
    }
}   
}

And in the reducer, as suggested by @Serhiy in the original question you need only one line of code:

public static class ReduceForWordCount extends Reducer<Text, IntWritable, Text, IntWritable>  
{  
private IntWritable result = new IntWritable();  
public void reduce(Text word, Iterable<IntWritable> values, Context con) throws IOException, InterruptedException  
{  
    con.write(word, null);  
}

Regrading "Edit 1" - I will leave it a trivial practice :)

回答2:

What exactly is happening

You are consuming lines of comma-delimited text, splitting the commas, and filtering out some values. con.write() should only be called once per line if all you are doing is extracting only those values.

The mapper will group all the "40" keys that you output and form a list of all the values that were written with that key. And that is what the reducer is reading over.

You should probably try this for your map function.

// Set the values to write 
saleValue.set(Integer.parseInt(words[0]));
rangeValue.set(words[3]);

// Filter out only the 40s
if(words[3].equals("40")) {
    // Write out "(40, safeValue)" words.length times 
    for(String word: words )
    {
        con.write( rangeValue , saleValue );
    }
}

If you don't want duplicate values for the length of the split string, then get rid of the for loop.

All your reducer is doing is just printing out what it received from the mapper.

回答3:

Mapper output would be something like this :

<word,count>

Reducer output would be like this :

<unique word, its total count>

Eg: A line is read and all words in it are counted and put in a <key,value> pair:

<40,1>
<140,1>
<50,1>
<40,1> ..

here 40,50,140, .. are all keys and the value is the count of number of occurrences of that key in a line. This happens in the mapper.

Then, these key,valuepairs are sent to the reducer where similar keys are all reduced to a single key and all the values associates with that key is summed to give a value to the key-value pair. So, the result of the reducer would be something like: