It is file size based, not file count based. For fewer files up the max-file-blocks setting.
On Wed, Jul 31, 2013 at 12:21 PM, Something Something <mailinglist...@gmail.com> wrote: > Thanks, John. But I don't see an option to specify the # of output files. > How does Crush decide how many files to create? Is it only based on file > sizes? > > On Wed, Jul 31, 2013 at 6:28 AM, John Meagher <john.meag...@gmail.com>wrote: > >> Here's a great tool for handling exactly that case: >> https://github.com/edwardcapriolo/filecrush >> >> On Wed, Jul 31, 2013 at 2:40 AM, Something Something >> <mailinglist...@gmail.com> wrote: >> > Each bz2 file after merging is about 50Megs. The reducers take about 9 >> > minutes. >> > >> > Note: 'getmerge' is not an option. There isn't enough disk space to do >> a >> > getmerge on the local production box. Plus we need a scalable solution >> as >> > these files will get a lot bigger soon. >> > >> > On Tue, Jul 30, 2013 at 10:34 PM, Ben Juhn <benjij...@gmail.com> wrote: >> > >> >> How big are your 50 files? How long are the reducers taking? >> >> >> >> On Jul 30, 2013, at 10:26 PM, Something Something < >> >> mailinglist...@gmail.com> wrote: >> >> >> >> > Hello, >> >> > >> >> > One of our pig scripts creates over 500 small part files. To save on >> >> > namespace, we need to cut down the # of files, so instead of saving >> 500 >> >> > small files we need to merge them into 50. We tried the following: >> >> > >> >> > 1) When we set parallel number to 50, the Pig script takes a long >> time - >> >> > for obvious reasons. >> >> > 2) If we use Hadoop Streaming, it puts some garbage values into the >> key >> >> > field. >> >> > 3) We wrote our own Map Reducer program that reads these 500 small >> part >> >> > files & uses 50 reducers. Basically, the Mappers simply write the >> line & >> >> > reducers loop thru values & write them out. We set >> >> > job.setOutputKeyClass(NullWritable.class) so that the key is not >> written >> >> to >> >> > the output file. This is performing better than Pig. Actually >> Mappers >> >> run >> >> > very fast, but Reducers take some time to complete, but this approach >> >> seems >> >> > to be working well. >> >> > >> >> > Is there a better way to do this? What strategy can you think of to >> >> > increase speed of reducers. >> >> > >> >> > Any help in this regard will be greatly appreciated. Thanks. >> >> >> >> >>
