Well, I know that downloading the 160 Gig uncompressed data takes
about 8 hours on the 10 Gig/sec Ethernet connection. I then bzip2
compress that to about 50 Meg. Which I binary upload back to z/OS for
safety (since it's setting on my Linux desktop) in just a few minutes.
But bzgrep can scan the compressed file fairly quickly (FSVO
"quickly"). So, if I use Perl or C to read the compressed file, expand
it on-the-fly and process the records, then recompress the data before
writing it to the proper result file (which is what I eventually want
anyway), that should greatly reduce the I/O. I need to see how easy it
is to do that in Perl vs Python vs C. Again, this is all for my
personal use so that I can answer questions more quickly about "who
did what to whom and how often? <grin/>" according to RACF.

On Wed, Jan 30, 2013 at 8:06 AM, Shane G <[email protected]> wrote:
> On Thu, Jan 31st, 2013 at 12:44 AM, John McKown wrote:
>
>> Thanks to all for the input! I _tried_ to run the script over night. I
>> added an echo to tell me which input file I was working on. I came in
>> this morning. It had been running from 14:00 to 06:30 (16 1/2 hours)
>> and was still on the first input file. That ain't gonna cut it. Time
>> to rethink. Using a Perl hash to contain an open file handle seems
>> logical. As does buffering multiple records per output file to do a
>> single I/O to write them. But I may be forced into using C or C++ for
>> speed. Too bad I'm not a very good C programmer.
>
> Interesting timing. I was about to suggest you utilize your perl skills.
> Having originally ignored it, I now use awk extensively for text
> parsing/reduction. But for *BIG* jobs, perl is it.
>
> But all that input I/O is going to be death whatever you choose.
>
> Shane ...
>
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--
Maranatha! <><
John McKown

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