Yeah, I thought about using counters but I was worried about what happens if a Mapper task fails. Does the counter get adjusted to remove any contributions that the failed Mapper made before another replacement Mapper is started? Otherwise in the case of any Mapper failure I'm going to get an overcount am I not?
Or is there some way to make sure that counters have the correct semantics in the face of failures? Peter Marron > -----Original Message----- > From: Dave Shine > [mailto:Dave.Shine@channelintelligence. > com] > Sent: 23 July 2012 15:35 > To: common-user@hadoop.apache.org > Subject: RE: Counting records > > You could just use a counter and never > emit anything from the Map(). Use the > getCounter("MyRecords", > "RecordTypeToCount").increment(1) > whenever you find the type of record you > are looking for. Never call > output.collect(). Call the job with > reduceTasks(0). When the job finishes, > you can programmatically get the values > of all counters including the one you > create in the Map() method. > > > Dave Shine > Sr. Software Engineer > 321.939.5093 direct | 407.314.0122 > mobile CI Boost(tm) Clients Outperform > Online(tm) www.ciboost.com > > > -----Original Message----- > From: Peter Marron > [mailto:Peter.Marron@trilliumsoftware. > com] > Sent: Monday, July 23, 2012 10:25 AM > To: common-user@hadoop.apache.org > Subject: Counting records > > Hi, > > I am a complete noob with Hadoop and > MapReduce and I have a question that is > probably silly, but I still don't know the > answer. > > For the purposes of discussion I'll assume > that I'm using a standard > TextInputFormat. > (I don't think that this changes things too > much.) > > To simplify (a fair bit) I want to count all > the records that meet specific criteria. > I would like to use MapReduce because I > anticipate large sources and I want to > get the performance and reliability that > MapReduce offers. > > So the obvious and simple approach is to > have my Mapper check whether each > record meets the criteria and emit a 0 or > a 1. Then I could use a combiner which > accumulates (like a LongSumReducer) > and use this as a reducer as well, and I > am sure that that would work fine. > > However it seems massive overkill to > have all those "1"s and "0"s emitted and > stored on disc. > It seems tempting to have the Mapper > accumulate the count for all of the > records that it sees and then just emit > once at the end the total value. This > seems simple enough, except that the > Mapper doesn't seem to have any easy > way to know when it is presented with > the last record. > > Now I could just make the Mapper take a > copy of the OutputCollector for each > record called and then in the close > method it could do a single emit. > However, although, this looks like it > would work with the current > implementation, there seem to be no > guarantees that the collector is valid at > the time that the close is called. This just > seems ugly. > > Or I could get the Mapper to record the > first offset that it sees and read the split > length using > report.getInputSplit().getLength() and > then it could monitor how far it is > through the split and it should be able to > detect the last record. It looks like the > MapRunner class creates a Mapper > object and uses it to process a split, and > so it looks like it's safe to store state in > the mapper class between invocations of > the map method. (But is this just an > implementation artefact? Is the mapper > class supposed to be completely > stateless?) > > Maybe I should have a custom > InputFormat class and have it flag the > last record by placing some extra > information in the key? (Assuming that > the InputFormant has enough > information from the split to be able to > detect the last record, which seems > reasonable enough.) > > Is there some "blessed" way to do this? > Or am I barking up the wrong tree > because I should really just generate all > those "1"s and "0"s and accept the > overhead? > > Regards, > > Peter Marron > Trillium Software UK Limited > > > The information contained in this email > message is considered confidential and > proprietary to the sender and is intended > solely for review and use by the named > recipient. Any unauthorized review, use > or distribution is strictly prohibited. If you > have received this message in error, > please advise the sender by reply email > and delete the message.
