Hello, I am a SAS novice and learning SAS on my own. Here is what I'm trying to do:
I have SAS installed on UNIX. I use MS ACCESS to produce GUI based reports. I have few large files in SAS/UNIX. Is it possible to run query in SAS/UNIX files and produce report in MS ACCESS? I don’t want to import huge files from SAS/UNIX to MS ACCESS.
If you have a SAS/SHARE server set up, you can use the SAS ODBC driver:
http://support.sas.com/software/products/odbc/
If you have SAS Integration Technologies (for use with SAS Enterprise Guide, for example), you can use the SAS IOM OLE DB provider. You'll have to specify a connection string that includes your SAS Workspace host, port, and credentials.
Be sure to apply proper filters when you access (SQL or WHERE clause) so that you don't pull that huge data into your MS Access session.
Is it possible to run query against SAS files stored on UNIX without importing files to MS Access?
One approach might be to do all of your big volume data processing in SAS, producing summary SAS tables that you then export to Access. If you have SAS/ACCESS Interface to PC Files you can export to MS Access instead of importing from it.
You should be able to do this with the IML interface to R
You will need a prebult access database to write into.
Microsoft changes the structure of access so R works better
if you supply the access database.
You can find a sample access databases at
C:\Program Files\sashome\SASFoundation\9.4\access\sasmisc
* I have 64bit SAS 9.4M2 on Windows and 64 bit Office
* there are options for all combinations of 32 and 64bit R or/and Office
* Should work almost everywhere (Windows/Unicies/Mac OS but not Z/OS or VMS)
HAVE Subset of SASHEL.CLASS
============================
SASHELP.CLASS
Up to 40 obs SD1.CLASS total obs=19
Obs NAME AGE HEIGHT WEIGHT
1 Alfred 14 69.0 112.5
2 Alice 13 56.5 84.0
3 Barbara 13 65.3 98.0
4 Carol 14 62.8 102.5
5 Henry 14 63.5 102.5
6 James 12 57.3 83.0
7 Jane 12 59.8 84.5
WANT ( Coefficient and residual reports in MS Access)
===============================================
COEFFICIENTS
names.cof. cof
(Intercept) (Intercept) -141.223763
AGE AGE 1.278393
HEIGHT HEIGHT 3.597027
RESIDUALS
NAME SEX AGE HEIGHT WEIGHT RESID FIT
1 Alfred M 14 69.0 112.5 -12.36856100 124.86856
2 Alice F 13 56.5 84.0 5.37266290 78.62734
3 Barbara F 13 65.3 98.0 -12.28117040 110.28117
4 Carol F 14 62.8 102.5 -0.06699663 102.56700
5 Henry M 14 63.5 102.5 -2.58491519 105.08492
6 James M 12 57.3 83.0 2.77343421 80.22657
7 Jane F 12 59.8 84.5 -4.71913207 89.21913
8 Janet F 15 62.5 112.5 9.73371881 102.76628
9 Jeffrey M 13 62.5 84.0 -16.20949616 100.20950
10 John M 12 59.0 99.5 13.15848914 86.34151
11 Joyce F 11 51.3 50.5 -6.86601421 57.36601
12 Judy F 14 64.3 90.0 -17.96253640 107.96254
13 Louise F 12 56.3 77.0 0.37046072 76.62954
14 Mary F 15 66.5 112.0 -5.15438724 117.15439
15 Philip M 16 72.0 150.0 11.78357444 138.21643
16 Robert M 12 64.8 128.0 20.79573537 107.20426
17 Ronald M 15 67.0 133.0 14.04709951 118.95290
18 Thomas M 11 57.5 85.0 5.33242142 79.66758
19 William M 15 66.5 112.0 -5.15438724 117.15439
SOLUTION
options validvarname=upcase;
libname sd1 "d:/sd1";
data sd1.class;
set sashelp.class(keep=name age weight height);
run;quit;
%utl_submit_r64('
library(haven);
library(RODBC);
library(Zelig);
myDB<-odbcDriverConnect("Driver={Microsoft Access Driver (*.mdb, *.accdb)};DBQ=d:/mdb/demo.accdb");
class<-read_sas("d:/sd1/class.sas7bdat");
z.o1 <- aov(WEIGHT ~ AGE + HEIGHT,data=class);
cof<-z.o1$coefficients;
coef=data.frame(names(cof),cof);
coef;
RESID<-z.o1$residuals;
FIT<-z.o1$fitted.values;
residual<-cbind(class,RESID,FIT);
residual;
sqlSave(myDB,residual,rownames=FALSE);
sqlSave(myDB,coef,rownames=FALSE);
close(myDB);
');
You can apply a filter as a query on the "command" you send via OLE DB. This SAS Note has some VB Script examples. These might be overkill for what you're looking for.
It sounds like you need to access SAS as a database via MS Access. ODBC and OLE DB are standard approaches from MS Access, if you have a running SAS instance (like SAS/Share or a SAS Workspace) that you can connect to.
Join us for SAS Innovate 2025, our biggest and most exciting global event of the year, in Orlando, FL, from May 6-9.
Lock in the best rate now before the price increases on April 1.
Learn the difference between classical and Bayesian statistical approaches and see a few PROC examples to perform Bayesian analysis in this video.
Find more tutorials on the SAS Users YouTube channel.
Ready to level-up your skills? Choose your own adventure.