Yikes! It's more like:

Claim_id = 10,000,000 Claim_Diag_primary = 20,000 Claim_Prim_Hosp_Proc_Cd = 15,000 Claim_Bill_Type = 500

That would end up 1.5 * 10^18 combinations!

I think I'll go with the SQL.

On Thu, Feb 3, 2011 at 12:11 PM, Jordan, Lewis < Lewis.Jordan@weyerhaeuser.com> wrote:

> One way would be to subset the data. Since the class statement essentially > creates a unique classification for each "Claim_Id Claim_Diag_Primary > Claim_Prim_Hosp_Proc_Cd Claim_Bill_Type" you could create a new variable > called "my_id" then create subsets. For example, let's say you have the > following numbers of categories for each variable on the "class" statement: > > Claim_id = 5 > Claim_Diag_primary = 10 > Claim_Prim_Hosp_Proc_Cd = 3 > Claim_Bill_Type = 4 > > You would then have 5*10*3*4 = 600 unique classifications. Since you > already sorted the data, you could do the following to create your new > variable: > > /* > I'm assuming your sort was of the form: > proc sort; by Claim_Id Claim_Diag_Primary Claim_Prim_Hosp_Proc_Cd > Claim_Bill_Type > */ > > Data new;set old;by Claim_Id Claim_Diag_Primary Claim_Prim_Hosp_Proc_Cd > Claim_Bill_Type; > If (_n_=1) then my_id=1; > Else if first.Claim_Bill_Type then my_id=my_id+1; > Retain my_id; > Run; > > %macro sums(); > > %do i=1 to 600; > > proc means data=new(where=(my_id=&i)) nway noprint missing; > var Claim_Counter ClaimLine_Counter ClaimLine_Paid_Amt > ClaimLine_COB_Paid_Amt > Claim_Interest_Amt ClaimLine_Savings_Amt; > output out = WORK._BMClaims (drop = _TYPE_ _FREQ_) sum()=; > run; > > Proc append data=work._BMClaims base=all_sums; > Run; > > %end; > > %mend sums; > > > > > > ***************************** > Lewis Jordan > Weyerhaeuser: > Southern Timberlands R&D > Cell (Primary): 662-889-4514 > Office: 662-245-5227 > lewis.jordan@weyerhaeuser.com > ***************************** > > -----Original Message----- > From: SAS(r) Discussion [mailto:SAS-L@LISTSERV.UGA.EDU] On Behalf Of > Sterling Paramore > Sent: Thursday, February 03, 2011 1:55 PM > To: SAS-L@LISTSERV.UGA.EDU > Subject: Out of memory? > > Dear SAS-L, > > I assume the following is failing due to the system running out of memory > (way to go SAS - not only do you not tell me what the problem is, this > doesn't even register as a real ERROR, only a warning) because if I run it > with an OBS= statement, it completes just fine. > > To solve the problem, I've tried first sorting the dataset (6 minutes), > then doing proc means with a by (7 minutes). I also tried using proc sql > and it required only 5 minutes. > > Any other ideas? I'd prefer not to have to rewrite a bunch of my proc > means as sql. > > Thanks, > Sterling > > > > 16 > 17 proc means noprint missing nway data = WORKERR._BMClaims_Concat; > 18 var Claim_Counter ClaimLine_Counter ClaimLine_Paid_Amt > ClaimLine_COB_Paid_Amt > 19 Claim_Interest_Amt ClaimLine_Savings_Amt; > 20 class Claim_Id Claim_Diag_Primary Claim_Prim_Hosp_Proc_Cd > Claim_Bill_Type; > 21 output out = WORK._BMClaims (drop = _TYPE_ _FREQ_) sum()=; > 22 run; > > NOTE: The SAS System stopped processing this step because of errors. > NOTE: There were 70619390 observations read from the data set > WORKERR._BMCLAIMS_CONCAT. > WARNING: The data set WORK._BMCLAIMS may be incomplete. When this step was > stopped there were 0 observations and 10 variables. > NOTE: PROCEDURE MEANS used (Total process time): > real time 2:23.15 > cpu time 3:08.01 > > >