Probably the most direct route to get your desired result is to save the objects to either a SequenceFile or plain text file on DFS. Then in the configure() section of your mapreduce jobs, you open the file on DFS, stream contents into a local variable and refer to it as you need to. Either way, you'll need some sort of serialization via Writable or plain text.
On Tue, May 11, 2010 at 4:19 PM, Renato Marroquín Mogrovejo <[email protected]> wrote: > Hi Aaron, > > The thing is that I had a data structure that is saved into a vector, and > this vector needs to be available for my MapReduce jobs while iterating. So > would you think it would a good and easy way to serialize this objects? It's > a vector that each node contains another user define data structure. Maybe I > will try to do it first just using files, and see how the throughput goes. > Hey do you know where I can find some examples of serializing objects for > Hadoop to save them into SequenceFiles? > Thanks in advance. > > Renato M. > > > 2010/5/11 Aaron Kimball <[email protected]> > >> Perhaps this is guidance in the area you were hoping for: If your data is >> in >> objects that implement the interface 'Writable', then you can use the >> SequenceFileOutputFormat and SequenceFileInputFormat to store your >> intermediate data in binary form in disk-backed files called SequenceFiles. >> The serialization will happen through the write() and readFields() methods >> of your objects, which will automatically be called by the >> OutputFormat/InputFormat as they move through the system. So your >> subsequent >> MR pass will receive objects back in the same form as they were emitted. >> This is a considerably better idea (from both a throughput and a sanity >> perspective) in a chained MapReduce job. >> >> - Aaron >> >> On Tue, May 11, 2010 at 10:31 AM, Aaron Kimball <[email protected]> >> wrote: >> >> > What objects are you referring to? I'm not sure I understand your >> question. >> > - Aaron >> > >> > >> > On Tue, May 11, 2010 at 6:38 AM, Renato Marroquín Mogrovejo < >> > [email protected]> wrote: >> > >> >> Thanks Aaron! I was thinking the same after doing some reading. >> >> Man what about serialize the objects? Would you think that is a good >> idea? >> >> Thanks again. >> >> >> >> Renato M. >> >> >> >> >> >> 2010/5/5 Aaron Kimball <[email protected]> >> >> >> >> > Renato, >> >> > >> >> > In general if you need to perform a multi-pass MapReduce workflow, >> each >> >> > pass >> >> > materializes its output to files. The subsequent pass then reads those >> >> same >> >> > files back in as input. This allows the workflow to start at the last >> >> > "checkpoint" if it gets interrupted. There is no persistent in-memory >> >> > distributed storage feature in Hadoop that would allow a MapReduce job >> >> to >> >> > post results to memory for consumption by a subsequent job. >> >> > >> >> > So you would just read your initial data from /input, and write your >> >> > interim >> >> > results to /iteration0. Then the next pass reads from /iteration0 and >> >> > writes >> >> > to /iteration1, etc.. >> >> > >> >> > If your data is reasonably small and you think it could fit in memory >> >> > somewhere, then you could experiment with using other distributed >> >> key-value >> >> > stores (memcached[b], hbase, cassandra, etc..) to hold intermediate >> >> > results. >> >> > But this will require some integration work on your part. >> >> > - Aaron >> >> > >> >> > On Wed, May 5, 2010 at 8:29 AM, Renato Marroquín Mogrovejo < >> >> > [email protected]> wrote: >> >> > >> >> > > Hi everyone, I have recently started to play around with hadoop, but >> I >> >> am >> >> > > getting some into some "design" problems. >> >> > > I need to make a loop to execute the same job several times, and in >> >> each >> >> > > iteration get the processed values (not using a file because I would >> >> need >> >> > > to >> >> > > read it). I was using an static vector in my main class (the one >> that >> >> > > iterates and executes the job in each iteration) to retrieve those >> >> > values, >> >> > > and it did work while I was using a standalone mode. Now I tried to >> >> test >> >> > it >> >> > > on a pseudo-distributed manner and obviously is not working. >> >> > > Any suggestions, please??? >> >> > > >> >> > > Thanks in advance, >> >> > > >> >> > > >> >> > > Renato M. >> >> > > >> >> > >> >> >> > >> > >> >
