Hi,

I have a large (~300 gig) zip of images that I need to process. My
current workflow is to copy the zip to HDFS, use a custom input format
to read the zip entries, do the processing in a map, and then generate
a processing report in the reduce. I'm struggling to tune params right
now with my cluster to make everything run smoothly, but I'm also
worried that I'm missing a better way of processing.

Does anybody have suggestions for how to make the processing of a zip
more parallel? The only other idea I had was uploading the zip as a
sequence file, but that proved incredibly slow (~30 hours on my 3 node
cluster to upload).

Thanks in advance.

-Andrew

How are your splitting the zip right now?  Do you have multiple mappers and each mapper starts at the beginning of the zip and goes to the point it cares about or do you just have one mapper?  If you are doing it the first way you may want to increase your replication factor.  Alternatively you could use multiple zip files, one per mapper that you want to launch.

--Bobby Evans

On 3/19/12 7:26 PM, "Andrew McNair" <[EMAIL PROTECTED]> wrote:

Hi,

I have a large (~300 gig) zip of images that I need to process. My
current workflow is to copy the zip to HDFS, use a custom input format
to read the zip entries, do the processing in a map, and then generate
a processing report in the reduce. I'm struggling to tune params right
now with my cluster to make everything run smoothly, but I'm also
worried that I'm missing a better way of processing.

Does anybody have suggestions for how to make the processing of a zip
more parallel? The only other idea I had was uploading the zip as a
sequence file, but that proved incredibly slow (~30 hours on my 3 node
cluster to upload).

Thanks in advance.

-Andrew

As I understand it, zip isn't splittable format. You might consider using
bzip2 or another splittable compression format.

Alternatively, you could have one job that does the decompression chained
to another that does the.processing to get the parallelization.
On Mar 19, 2012 8:26 PM, "Andrew McNair" <[EMAIL PROTECTED]> wrote:

> Hi,
>
> I have a large (~300 gig) zip of images that I need to process. My
> current workflow is to copy the zip to HDFS, use a custom input format
> to read the zip entries, do the processing in a map, and then generate
> a processing report in the reduce. I'm struggling to tune params right
> now with my cluster to make everything run smoothly, but I'm also
> worried that I'm missing a better way of processing.
>
> Does anybody have suggestions for how to make the processing of a zip
> more parallel? The only other idea I had was uploading the zip as a
> sequence file, but that proved incredibly slow (~30 hours on my 3 node
> cluster to upload).
>
> Thanks in advance.
>
> -Andrew
>