Hi Shahab, I'm not sure if I understand right, but the problem is that you need to put the data you want to secondary sort into your key class. But, what I just realized is that the original key probably IS accessible, because of the Writable semantics. As you iterate through the Iterable passed to the reduce call the Key changes its contents. Am I right? This seems a bit weird but probably is how it works. I just overlooked this, because of the way the API looks and how all howtos on doing secondary sort look. All I have seen duplicate the secondary part of the key in value.
Jan -------- Original message -------- Subject: Re: Partitioner vs GroupComparator From: Shahab Yunus <shahab.yu...@gmail.com> To: "user@hadoop.apache.org" <user@hadoop.apache.org> CC: @Jan, why not, not send the 'hidden' part of the key as a value? Why not then pass value as null or with some other value part. So in the reducer side there is no duplication and you can extract the 'hidden' part of the key yourself (which should be possible as you will be encapsulating it in a some class/object model...? Regards, Shahab On Fri, Aug 23, 2013 at 12:22 PM, Jan Lukavský <jan.lukav...@firma.seznam.cz<mailto:jan.lukav...@firma.seznam.cz>> wrote: Hi all, when speaking about this, has anyone ever measured how much more data needs to be transferred over the network when using GroupingComparator the way Harsh suggests? What do I mean, when you use the GroupingComparator, it hides you the real key that you have emitted from Mapper. You just see the first key in the reduce group and any data that was carried in the key needs to be duplicated in the value in order to be accessible on the reduce end. Let's say you have key consisting of two parts (base, extension), you partition by the 'base' part and use GroupingComparator to group keys with the same base part. Than you have no other chance than to emit from Mapper something like this - (key: (base, extension), value: extension), which means the 'extension' part is duplicated in the data, that has to be transferred over the network. This overhead can be diminished by using compression between map and reduce side, but I believe that in some cases this can be significant. It would be nice if the API allowed to access the 'real' key for each value, not only the first key of the reduce group. The only
