Suggest that if you have a choice, you use bzip2 compression instead of gzip as bzip2 is block-based and Pig can split reading a large bzipped file across multiple mappers while gzip can't be split that way.
On Mon, Jun 10, 2013 at 12:06 PM, William Oberman <[email protected]>wrote: > I still don't fully understand (and am still debugging), but I have a > "problem file" and a theory. > > The file has a "corrupt line" that is a huge block of null characters > followed by a "\n" (other lines are json followed by "\n"). I'm thinking > that's a problem with my cassandra -> s3 process, but is out of scope for > this thread.... I wrote scripts to examine the file directly, and if I > stop counting at the weird line, I get the "gz" count. If I count all > lines (e.g. don't fail at the corrupt line) I get the "uncompressed" count. > > I don't know how to debug hadoop/pig quite as well, though I'm trying now. > But, my working theory is that some combination of pig/hadoop aborts > processing the gz stream on a null character, but keeps chugging on a > non-gz stream. Does that sound familiar? > > will > > > On Sat, Jun 8, 2013 at 8:00 AM, William Oberman <[email protected] > >wrote: > > > They are all *.gz, I confirmed that first :-) > > > > > > On Saturday, June 8, 2013, Niels Basjes wrote: > > > >> What are the exact filenames you used? > >> The decompression of input files is based on the filename extention. > >> > >> Niels > >> On Jun 7, 2013 11:11 PM, "William Oberman" <[email protected]> > >> wrote: > >> > >> > I'm using pig 0.11.2. > >> > > >> > I had been processing ASCII files of json with schema: (key:chararray, > >> > columns:bag {column:tuple (timeUUID:chararray, value:chararray, > >> > timestamp:long)}) > >> > For what it's worth, this is cassandra data, at a fairly low level. > >> > > >> > But, this was getting big, so I compressed it all with gzip (my "ETL" > >> > process is already chunking the data into 1GB parts, making the .gz > >> files > >> > ~100MB). > >> > > >> > As a sanity check, I decided to do a quick check of pre/post, and the > >> > numbers aren't matching. Then I've done a lot of messing around > trying > >> to > >> > figure out why and I'm getting more and more puzzled. > >> > > >> > My "quick check" was to get an overall count. It looked like > (assuming > >> A > >> > is a LOAD given the schema above): > >> > ------- > >> > allGrp = GROUP A ALL; > >> > aCount = FOREACH allGrp GENERATE group, COUNT(A); > >> > DUMP aCount; > >> > ------- > >> > > >> > Basically the original data returned a number GREATER than the > >> compressed > >> > data number (not by a lot, but still...). > >> > > >> > Then I uncompressed all of the compressed files, and did a size check > of > >> > original vs. uncompressed. They were the same. Then I "quick > checked" > >> the > >> > uncompressed, and the count of that was == original! So, the way in > >> which > >> > pig processes the gzip'ed data is actually somehow different. > >> > > >> > Then I tried to see if there are nulls floating around, so I loaded > >> "orig" > >> > and "comp" and tried to catch the "missing keys" with outer joins: > >> > ----------- > >> > joined = JOIN orig by key LEFT OUTER, comp BY key; > >> > filtered = FILTER joined BY (comp::key is null); > >> > ----------- > >> > And filtered was empty! I then tried the reverse (which makes no > sense > >> I > >> > know, as this was the smaller set), and filtered is still empty! > >> > > >> > All of these loads are through a custom UDF that extends LoadFunc. > But, > >> > there isn't much to that UDF (and it's been in use for many months > now). > >> > Basically, the "raw" data is JSON (from cassandra's sstable2json > >> program). > >> > And I parse the json and turn it into the pig structure of the schema > >> > noted above. > >> > > >> > Does anything make sense here? > >> > > >> > Thanks! > >> > > >> > will > >> > > >> > > > > > > >
