Thanks Ted. It's exactly where I was looking at now. I was close. I will take a deeper look.
Thanks Nitin for the link. I will read that too. JM 2013/4/10 Nitin Pawar <nitinpawar...@gmail.com> > To add what Ted said, > > the same discussion happened on the question Jean asked > > https://issues.apache.org/jira/browse/HBASE-1287 > > > On Wed, Apr 10, 2013 at 7:28 PM, Ted Yu <yuzhih...@gmail.com> wrote: > > > Jean-Marc: > > Take a look at HRegionPartitioner which is in both mapred and mapreduce > > packages: > > > > * This is used to partition the output keys into groups of keys. > > > > * Keys are grouped according to the regions that currently exist > > > > * so that each reducer fills a single region so load is distributed. > > > > Cheers > > > > On Wed, Apr 10, 2013 at 6:54 AM, Jean-Marc Spaggiari < > > jean-m...@spaggiari.org> wrote: > > > > > Hi Nitin, > > > > > > You got my question correctly. > > > > > > However, I'm wondering how it's working when it's done into HBase. Do > > > we have defaults partionners so we have the same garantee that records > > > mapping to one key go to the same reducer. Or do we have to implement > > > this one our own. > > > > > > JM > > > > > > 2013/4/10 Nitin Pawar <nitinpawar...@gmail.com>: > > > > I hope i understood what you are asking is this . If not then pardon > me > > > :) > > > > from the hadoop developer handbook few lines > > > > > > > > The*Partitioner* class determines which partition a given (key, > value) > > > pair > > > > will go to. The default partitioner computes a hash value for the key > > and > > > > assigns the partition based on this result. It garantees that all the > > > > records mapping to one key go to same reducer > > > > > > > > You can write your custom partitioner as well > > > > here is the link : > > > > http://developer.yahoo.com/hadoop/tutorial/module5.html#partitioning > > > > > > > > > > > > > > > > > > > > On Wed, Apr 10, 2013 at 6:19 PM, Jean-Marc Spaggiari < > > > > jean-m...@spaggiari.org> wrote: > > > > > > > >> Hi, > > > >> > > > >> quick question. How are the data from the map tasks partitionned for > > > >> the reducers? > > > >> > > > >> If there is 1 reducer, it's easy, but if there is more, are all they > > > >> same keys garanteed to end on the same reducer? Or not necessary? > If > > > >> they are not, how can we provide a partionning function? > > > >> > > > >> Thanks, > > > >> > > > >> JM > > > >> > > > > > > > > > > > > > > > > -- > > > > Nitin Pawar > > > > > > > > > -- > Nitin Pawar >
