我有一个巨大的CSV文件，我想使用Hadoop麻preduce在亚马逊EMR（蟒蛇）来处理。

该文件有7场，但是，我只在看日和量字段。

 日期，receiptIdproductId参数，量价posIdcashierId
 

首先，我mapper.py

 进口SYS

高清主（argv的）：
    行= sys.stdin.readline（）
    尝试：
        而行：
            表= line.split（'\ t'）

            ＃如果日期符合标准，加量至前preSS关键
                如果INT（名单[0] [11:13]）＆GT; = 17和INT（名单[0] [11:13]）＆LT; = 19：
                    打印％S \ t％s的％（前preSS，INT（名单[3]））
            #ELSE，加量不-EX preSS关键
                其他：
                    打印％S \ t％s的％（非-EX preSS，INT（名单[3]））

            行= sys.stdin.readline（）
除了文件结尾：
        返回None
如果__name__ ==__main__：
        主（sys.argv中）
 

有关减速，我将使用流命令：聚合

问：

是我的code吗？我跑了它在亚马逊电子病历，但我有一个空的输出。

所以，我的最终结果应该是：EX preSS，XXX和非EX preSS，YYY。我可以返回结果之前，做一个除法操作？ XXX / YYY的只是结果。我应该在哪里把这个code？减速??

此外，这是一个巨大的CSV文件，所以会映射分割成几个分区？或者我需要显式调用FileSplit？如果是这样，我该怎么做呢？

在这里回答我的问题！

在code是错误的。如果您使用的是总库减少，你的输出不按照通常的键值对。它需要一个preFIX。

 如果INT（名单[0] [11:13]）＆GT; = 17和INT（名单[0] [11:13]）＆LT; = 19：
    ＃这个是打印的总库的正确方法
    #PRINT都作为一个字符串。
    打印LongValueSum：+前preSS+\ t+列表[3]
 

其他prefixes可用的有：DoubleValueSum，LongValueMax，LongValueMin，StringValueMax，StringValueMin，UniqValueCount，ValueHistogram。欲了解更多信息，请看这里http://hadoop.apache.org/common/docs/r0.15.2/api/org/apache/hadoop/ma$p$pd/lib/aggregate/package-summary.html.

是的，如果你想要做的不仅仅是基本的总和，最小值，最大值或计数，你需要编写自己减速。

我还没有答案。

I have a huge CSV file I would like to process using Hadoop MapReduce on Amazon EMR (python).

The file has 7 fields, however, I am only looking at the date and quantity field.

 "date" "receiptId" "productId" "quantity"  "price" "posId" "cashierId"

Firstly, my mapper.py

import sys

def main(argv):
    line = sys.stdin.readline()
    try:
        while line:
            list = line.split('\t')

            #If date meets criteria, add quantity to express key
                if int(list[0][11:13])>=17 and int(list[0][11:13])<=19:
                    print '%s\t%s' % ("Express", int(list[3]))
            #Else, add quantity to non-express key
                else:
                    print '%s\t%s' % ("Non-express", int(list[3]))

            line =  sys.stdin.readline()
except "end of file":
        return None
if __name__ == "__main__":
        main(sys.argv)

For the reducer, I will be using the streaming command: aggregate.

Question:

Is my code right? I ran it in Amazon EMR but i got an empty output.

So my end result should be: express, XXX and non-express, YYY. Can I have it do a divide operation before returning the result? Just the result of XXX/YYY. Where should i put this code? A reducer??

Also, this is a huge CSV file, so will mapping break it up into a few partitions? Or do I need to explicitly call a FileSplit? If so, how do I do that?

Answering my own question here!

The code is wrong. If you're using aggregate library to reduce, your output does not follow the usual key value pair. It requires a "prefix".

if int(list[0][11:13])>=17 and int(list[0][11:13])<=19:
    #This is the correct way of printing for aggregate library
    #Print all as a string.
    print  "LongValueSum:" + "Express" + "\t" + list[3]

The other "prefixes" available are: DoubleValueSum, LongValueMax, LongValueMin, StringValueMax, StringValueMin, UniqValueCount, ValueHistogram. For more info, look here http://hadoop.apache.org/common/docs/r0.15.2/api/org/apache/hadoop/mapred/lib/aggregate/package-summary.html.

Yes, if you want to do more than just the basic sum, min, max or count, you need to write your own reducer.

I do not yet have the answer.