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Date:         Mon, 26 Apr 1999 09:34:14 -0700
Reply-To:     Zeke Torres <sas_aholic@YAHOO.COM>
Sender:       "SAS(r) Discussion" <SAS-L@UGA.CC.UGA.EDU>
From:         Zeke Torres <sas_aholic@YAHOO.COM>
Subject:      Re: How to trick Proc Freq?
Comments: To: david pider <dpider@HOTMAIL.COM>
Content-Type: text/plain; charset=us-ascii

David Pider.

I implor you. I beg you. I beseech you. PLEASE.. PLEASE.. I am on my knees crawling. PLEASE tell me where you work so I DO NOT APPLY for a JOB there. I would NOT want to waste YOUR valuable 'TECHNICAL MANAGERIAL" time and add ANY more grief to your "15 Years of experience".

Also... Do you have any printed material... IE publications? I need something to prop up my desk at home. It seams to be slanted a little to the left.

Later, Zeke Torres

Human, From: Universe, Milky Way Galaxy, Solar System, Earth, Nothern Hemisphere, United States, Mid West, Illinois, Chicago, North side ah you would know about it cause im sure your of a superior origination above us.

OR wait am i being scarcastic?

--- david pider wrote: > Alex Martchenko wrote: > > > > Hi, > > > > I have a credit policy SAS data set with almost 100 million > >observations. It has a numeric variable FLDR_ID that can be any > >integer number from -500,000 to +500,000. So on the average there > are > >about 100 observations with the same FLDR_ID on the file. The data > >set is sorted by a different variable (account number) and so it's > >unsorted by FLDR_ID. I'm trying to create a data set with > >frequencies, cumulative frequencies, percents and cumulative > percents > >for all values of FLDR_ID. I'm trying to use proc freq like that: > > > > proc freq data=folders(keep=fldr_id); > > tables fldr_id / missing out=fldr_fq; > > > >But I have 2 problems: 1) proc freq runs out of memory and abends > >the job 2) if I run it on a much smaller subset so it runs OK, it > >doesn't create cumulative variables in the OUT= file. I could live > >with problem 2 because I can read the output data set with frequency > >and then calculate cumulatives in a data step. > > Real pain is problem 1. I run it in batch on OS/390, 6.09E. A job > >can only use 50M of memory (that's all system people say we can have > >for a single SAS job). But proc freq wants more, so if I specify > >MEMSIZE=100M it doesn't matter because after 50M limit is exceeded, > >the job abends anyway. > > If you read SAS manuals you wouldn't be in trouble. About PROC FREQ, > the manual says 'the maximum number of levels allowed for any one > variable is 32,767. If you have a variable with more than 32,767 > levels, use the SUMMARY procedure'. > > >I know I can sort it by FLDR_ID and then use first. and last. > >variables to do what I need. But in our system sorting 100 million > >records is a big problem itself. Does anyone have suggestions? I > will > >greatly appreciate any input. > > Here is one: if some of self appointed 'gurus' offer you a 'datastep > algorithm' claiming it is 'more efficient' that SAS procs do yourself > a favor and use 'delete' button. Trust my 15 years in SAS, none of > thses 'solutions' run faster or 'more efficiently' than properly > applied SAS procs. I've just fired one 'expert' as soon as I saw that > he tried to get smart and summarized in datastep instead of proc > summary. If I can't ban them 'gurus' from SAS profession, at least I > can keep them away from my shop. And it's getting worse. Now this > 'datastep approach' have even sneaked into SUGI. I almost fainted at > seeing a paper by one of them 'gurus' (who I bet have no idea of real > world programing) trying to replace proc sort with his 'quick sort' > monstrosity. I wonder why he didn't call it 'blast sort' or > something? > > BTW, try SQL too. Personally, I don't like it (it shouldn't of been > in > SAS in the first place) but at least it's a SAS proc and at least > will > beat any 'datastep algorithm' hands down. > > D. Pider > Technical Manager > 15 years of SAS experience > > > > > > _______________________________________________________________ > Get Free Email and Do More On The Web. Visit >

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