The files decompress remarkably fast, too. I seem to recall about 8 minutes on our hardware.
I could not get map/reduce to split on blocks in bzip'd files. That gave me a long tail since the English file is so much bigger. Uncompressing the files is the way to go. -Eric On Tue, May 21, 2013 at 2:58 PM, Josh Elser <[email protected]> wrote: > You should see much better ingest performance having decompressed input. > Hadoop will also 'naturally' handle the splits for you based on the HDFS > block size. > > > On 5/21/13 2:35 PM, Patrick Lynch wrote: > >> I think your description is accurate, except that I split the single >> archive into a much greater number of pieces than the number of >> different archives I ingested. Specifically, I set numGroups to a higher >> number, I didn't split the archive my hand in hdfs. The archives are >> bzip2-ed, not gzip-ed. Will decompressing still have the same benefit? >> >> >> -----Original Message----- >> From: Josh Elser <[email protected]> >> To: user <[email protected]> >> Sent: Tue, May 21, 2013 2:16 pm >> Subject: Re: Wikisearch Performance Question >> >> Let me see if I understand what you're asking: you took one mediawiki >> archive and split it into n archives of size 1/n the original. You then >> took many n _different_ mediawiki archives and ingested those. You tried >> to get the speed of ingesting many different archives be as fast as >> splitting an original single archive? >> >> Are you using gzip'ed input files? Have you tried just decompressing the >> gzip into plaintext? Hadoop will naturally split uncompressed text and >> and give you nice balancing. >> >> I haven't looked at the ingest code in a long time. Not sure if it ever >> received much love. >> >> On 5/21/13 1:30 PM, Patrick Lynch wrote: >> >>> user@accumulo, >>> >>> I was working with the Wikipedia Accumulo ingest examples, and I was >>> trying to get the ingest of a single archive file to be as fast as >>> ingesting multiple archives through parallelization. I increased the >>> number of ways the job split the single archive so that all the servers >>> could work on ingesting at the same time. What I noticed, however, was >>> that having all the servers work on ingesting the same file was still >>> not nearly as fast as using multiple ingest files. I was wondering if I >>> could have some insight into the design of the Wikipedia ingest that >>> could explain this phenomenon. >>> >>> Thank you for your time, >>> Patrick Lynch >>> >> >>
