Hi, The provided example records are perfect. With that I doubt there will be any confusion about what kind of data is available and it should be manipulated. However, "the output is not coming as desired" is vague. It's hard to say why you are not getting your expected result without a bit more information about what has been done.
The aim is to compute cumulative credit & debit amounts (like you said) using a sequence of records that need be sorted by date (and transaction id if the order inside the day is relevant and if the transaction id is monotonically increasing.) The mapper won't have much logic and will be only responsible for transforming the records so that the sort happens as expect. The <key,value> would be something like <[date,transactionId],[CR/DR,amount]>. And the reducer would apply the logic of calculating the cumulative sums. I can see different variations. Like * what exactly should be the reducer input value : [CR/DR,amount] or only a signed amount. It doesn't change the logic much but it could help reducing the volume of data. Alternatives for serialization and compression should also be explored. * whether several reducers should be used or not. More than one could be used but then in order to have the full cumulative sums, a kind of post-reduce merge should be performed. The last results of a file will be CR/DR offsets that should be applied to the results of the next file. The partitioning will greatly depends on the processed time range and the associated data volumes. * what group should be used by the reducer : only one group (with all values sorted inside this single group) or one group per date with internal sorting per transaction id or one group per [date,transactionId]. I honestly don't know the impact that each would have without doing benchmarks. Yet, all these details might be way of your real problems. So if you provide more details about your actual computation and results, you might receive more constructive answers with regard to your problem. Regards Bertrand On Fri, Oct 5, 2012 at 6:56 AM, Sarath < sarathchandra.jos...@algofusiontech.com> wrote: > Thanks for all your responses. As suggested will go through the > documentation once again. > > But just to clarify, this is not my first map-reduce program. I've already > written a map-reduce for our product which does filtering and > transformation of the financial data. This is a new requirement we've got. > I have also did the logic of calculating the cumulative sums. But the > output is not coming as desired and I feel I'm not doing it right way and > missing something. So thought of taking a quick help from the mailing list. > > As an example, say we have records as below - > Txn ID > Txn Date > Cr/Dr Indicator > Amount > 1001 > 9/22/2012 > CR > 1000 > 1002 > 9/25/2012 > DR > 500 > 1003 > 10/1/2012 > DR > 1500 > 1004 > 10/4/2012 > CR > 2000 > > When this file passed the logic should append the below 2 columns to the > output for each record above - > CR Cumulative Amount > DR Cumulative Amount > 1000 > 0 > 1000 > 500 > 1000 > 2000 > 3000 > 2000 > > Hope the problem is clear now. Please provide your suggestions on the > approach to the solution. > > Regards, > Sarath. > > > On Friday 05 October 2012 02:51 AM, Bertrand Dechoux wrote: > > I indeed didn't catch the cumulative sum part. Then I guess it begs for > what-is-often-called-a-secondary-sort, if you want to compute different > cumulative sums during the same job. It can be more or less easy to > implement depending on which API/library/tool you are using. Ted comments > on performance are spot on. > > Regards > > Bertrand > > On Thu, Oct 4, 2012 at 9:02 PM, java8964 java8964 <java8...@hotmail.com>wrote: > >> I did the cumulative sum in the HIVE UDF, as one of the project for my >> employer. >> >> 1) You need to decide the grouping elements for your cumulative. For >> example, an account, a department etc. In the mapper, combine these >> information as your omit key. >> 2) If you don't have any grouping requirement, you just want a cumulative >> sum for all your data, then send all the data to one common key, so they >> will all go to the same reducer. >> 3) When you calculate the cumulative sum, does the output need to have a >> sorting order? If so, you need to do the 2nd sorting, so the data will be >> sorted as the order you want in the reducer. >> 4) In the reducer, just do the sum, omit every value per original record >> (Not per key). >> >> I will suggest you do this in the UDF of HIVE, as it is much easy, if >> you can build a HIVE schema on top of your data. >> >> Yong >> >> ------------------------------ >> From: tdunn...@maprtech.com >> Date: Thu, 4 Oct 2012 18:52:09 +0100 >> Subject: Re: Cumulative value using mapreduce >> To: user@hadoop.apache.org >> >> >> Bertrand is almost right. >> >> The only difference is that the original poster asked about cumulative >> sum. >> >> This can be done in reducer exactly as Bertrand described except for >> two points that make it different from word count: >> >> a) you can't use a combiner >> >> b) the output of the program is as large as the input so it will have >> different performance characteristics than aggregation programs like >> wordcount. >> >> Bertrand's key recommendation to go read a book is the most important >> advice. >> >> On Thu, Oct 4, 2012 at 5:20 PM, Bertrand Dechoux <decho...@gmail.com>wrote: >> >> Hi, >> >> It sounds like a >> 1) group information by account >> 2) compute sum per account >> >> If that not the case, you should precise a bit more about your context. >> >> This computing looks like a small variant of wordcount. If you do not >> know how to do it, you should read books about Hadoop MapReduce and/or >> online tutorial. Yahoo's is old but still a nice read to begin with : >> http://developer.yahoo.com/hadoop/tutorial/ >> >> Regards, >> >> Bertrand >> >> >> On Thu, Oct 4, 2012 at 3:58 PM, Sarath < >> sarathchandra.jos...@algofusiontech.com> wrote: >> >> Hi, >> >> I have a file which has some financial transaction data. Each transaction >> will have amount and a credit/debit indicator. >> I want to write a mapreduce program which computes cumulative credit & >> debit amounts at each record >> and append these values to the record before dumping into the output file. >> >> Is this possible? How can I achieve this? Where should i put the logic of >> computing the cumulative values? >> >> Regards, >> Sarath. >> >> >> >> >> -- >> Bertrand Dechoux >> >> >> > > > -- > Bertrand Dechoux > > -- Bertrand Dechoux
