How To Write Efficient SAS Programs: Ten Handy Tips!

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HOW TO WRITE EFFICIENT SAS PROGRAMS:
TEN HANDY TIPS!
PRESENTATION TO THE OCKHAM SAS USERS GROUP
APRIL 16, 2013

THE BASIC RULES FOR EFFICIENT SAS PROGRAMS:
• Work with as little data as possible
• Process as few instructions as possible
• Make the programs as reusable and flexible as possible to minimize
programmer effort.
LUCKILY, THE SAS PROGRAMMING LANGUAGE OFFERS MANY WAYS TO WRITE
EFFICIENT PROGRAMS.

THE BASIC RULES FOR EFFICIENT SAS PROGRAMS:
• Work with as little data as possible
• Process as few instructions as possible
• Make the programs as reusable and flexible as possible to minimize
programmer effort.

WHEN READING A SAS DATA SET, USE THE WHERE
STATEMENT TO FILTER YOUR DATA
• Less efficient: • More efficient:
data new;
set old;
more statements here;
run;
data new;
set old;
where condition;
run;
Added efficiency: when using SAS/Access engines, SAS attempts to send the WHERE clause to
the RDBMS for evaluation rather than to SAS; with the IF statement, SAS must do the processing.

IF YOU’RE GOING TO RUN A PROCEDURE ON THE DATA,
USE THE WHERE STATEMENT IN THE PROCEDURE.
Less efficient: • More efficient:
data new;
set old;
where city=‘Raleigh';
run;
proc means data=new;
run;
proc means data=old;
where city=‘Raleigh’;
run;

CREATING AN INDEX TO USE WITH THE WHERE
STATEMENT CAN SPEED THINGS UP EVEN MORE.
• Indexes can be created in the DATA step, in PROC CONTENTS or PROC
DATASETS, or in PROC SQL
• If feasible, sort the data on the indexed field
• Indexes do take up additional space, however.

1. usually bench mark: a mark on a permanent object indicating elevation and
serving as a reference in topographic surveys and tidal observations
2. a: a point of reference from which measurements may be made
b: something that serves as a standard by which others may be measured
or judged
c: a standardized problem or test that serves as a basis for evaluation or
comparison (as of computer system performance)
bench·mark
noun ˈbench-ˌmärk

BENCHMARKS
• The programs were run on a laptop with Windows 7 Enterprise (64-bit)
• I turned on option FULLSTIMER;
• The programs were run 3x each (with SAS shut down between each run),
and I used averages for comparison

BENCHMARKS
• Results: User CPU Time (SAS processing time)
Program 1 Program 2
WHERE stmt WHERE with Index
(sorted)
.14 second .12 second
• Results: System CPU Time (peripheral activities - memory, I/O, etc.)
Program 1 Program 2
WHERE stmt WHERE with Index
(sorted)

SELECT ONLY THE COLUMNS YOU NEED WHEN WORKING
WITH SAS DATA.
data new;
set old;
run;
data new;
set old (drop=category
type value ...);
run;
Variations:
• Use the keep= option if you need to keep more variables than you need to drop!
• Use both keep= and drop= options to control variables on both the incoming and outgoing
sides!
• Keep= and drop= options can be used in PROC steps, too!

BENCHMARKS
Kept one out of eleven variables
Results: User CPU Time
Program 1 Program 2
With KEEP= option Without KEEP= option
Results: System CPU Time
Program 1 Program 2
With KEEP= option Without KEEP= option

USE IF-THEN-ELSE INSTEAD OF IF-IF-IF
Less efficient:
More efficient:
data new;
set old;
if condition then
some action;
if condition then
some other action;
if condition then
some other action;
run;
data new;
set old;
if condition then
some action;
else if condition then
some other action;
some other action;
run;
Added efficiency: rank the order in which condition takes place and order the if / else-if statements
accordingly!

MINIMIZE THE NUMBER OF TIMES YOU READ YOUR DATA.
data a;
set old;
[more code]
run;
data b;
set old;
[more code]
run;
data c;
set old;
[more code]
run;
data a b c;
set old;
if condition then
output a;
output b;
output c;
run;

BENCHMARKS
• Results: User CPU Time
Program 1 Program 2
Read data once Read data multiple times
 Results: System CPU Time
Program 1 Program 2
Read data once Read data multiple times

NO NEED TO “WAKE UP” THE DATA – JUST USE IT!
• Less inefficient: • More efficient:
data new;
set old;
run;
proc means data=new;
run;
proc means data=old;
run;

LIMIT THE NUMBER OF TIMES YOU SORT YOUR DATA
• SAS will check to see if the dataset is already sorted
• You can use the PRESORTED option to ensure the check is done.
or:

THE SAS LOG:

SOME DATA STEP AND PROCEDURE STATEMENTS
REQUIRE THE DATA TO BE SORTED; OTHERS DO NOT.
• DATA step with SET or MERGE
and BY statements
• BY statement in PROC MEANS,
PROC FREQ, etc.
• others
Requires sorting Does not require sorting
• PROC SQL joins
• CLASS statement in PROC
MEANS, PROC FREQ, etc.
• others

COMMENT YOUR PROGRAMS
• You think you’ll remember what the program does, but you won’t.
• Someone else may inherit your programs, and comments will make the
process of interpreting what they do, a lot easier.
• Method #1:
/* your comment here */
• Method #2:
* your comment here;

EXAMPLE OF A COMMENT

MAKE THINGS EASIER FOR YOURSELF: PUT ALL
“GLOBAL” STATEMENTS AT THE BEGINNING OF YOUR
CODE, AND ALL “DEFINITIONS” OUTSIDE OF YOUR CODE
• Libname statements, system options, and title statements are easier to find
(and change, if necessary) if they are all in one place.
• Macro definitions and format definitions should not be included within your
SAS programs. If they are stored as separate programs (or in macro libraries)
they will be easier to find and easier to change if necessary.

• Be “GREEN” – save code and reuse it later!
• Collaborate with your co-workers to share tips and suggestions
• Meet regularly to share ideas
• Some ways SAS code fosters reusability:
• Format library
• Macro library
• Stored processes
• User-written functions and procedures.
MAKE THINGS EASIER FOR YOURSELF: EFFICIENCY ALSO
MEANS WORKING SMARTER!

WHAT OTHER IDEAS DO YOU HAVE?

ADDITIONAL RESOURCES
• SAS Communities
• Your peers and coworkers
• Your in-house SAS User Group!

sas.com
THANK YOU FOR BEING A SAS CUSTOMER!

How To Write Efficient SAS Programs: Ten Handy Tips!

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How To Write Efficient SAS Programs: Ten Handy Tips!