我想用mapreduce来处理python中的矩阵乘法和hadoop。目标是计算a*b。输出应与输入相似。
输入两个矩阵a和b的格式如下：

A,0,0,0.0
A,0,1,1.0
...
A,1,3,8.0
A,1,4,9.0
B,0,0,0.0
B,0,1,1.0
...
B,4,0,12.0
B,4,1,13.0

a、 0,0,0.0表示索引为a（0,0），值为0.0，与b相同。
这是我的Map功能：

import sys
import string
import numpy

# Split line into array of entry data

entry = line.split(",")

# Set row, column, and value for this entry

row = int(entry[1])
col = int(entry[2])
value = float(entry[3])

# If this is an entry in matrix A...

if (entry[0] == "A"):

        #Generate the necessary key-value pairs
        for i in range(col):
                print('<{}{},{} {} {}}>'.format(row,i,A,col,value))

# Otherwise, if this is an entry in matrix B...

else:
        #Generate the necessary key-value pairs
        for i in range(row):
                print('<{}{},{} {} {}}>'.format(i,col,B,row,value))

我想知道如何写reduce函数。以下是我将使用的框架：

import sys
import string
import numpy

# number of columns of A/rows of B

n = int(sys.argv[1])

# Create data structures to hold the current row/column values (if needed; your code goes here)

currentkey = None

# input comes from STDIN (stream data that goes to the program)

for line in sys.stdin:

        #Remove leading and trailing whitespace
        line = line.strip()

        #Get key/value
        key, value = line.split('\t',1)

        #Parse key/value input (your code goes here)

    #If we are still on the same key...
    if key==currentkey:

            #Process key/value pair (your code goes here)

    #Otherwise, if this is a new key...
    else:
            #If this is a new key and not the first key we've seen
            if currentkey:

                    #compute/output result to STDOUT (your code goes here)

            currentkey = key

            #Process input for new key (your code goes here)

# Compute/output result for the last key (your code goes here)

为了运行这两个函数，我将使用一个小的测试数据集对它们进行测试，代码如下：

cat smalltest.txt | python src/map.py 2 3 | sort -n | python src/reduce.py 5

map给出的输出，然后使用 sort -n 为了对键进行排序，所以我将使用减速机来处理矩阵的计算。我的困惑是写减速机函数。