Operating Environment Information
See the documentation for your operating environment for information about how
STIMER differs from FULLSTIMER in your operating environment. The
information that these options display varies depending on your operating
environment, so statistics that you see might differ from the ones shown.
Interpreting FULLSTIMER and STIMER Statistics
Several types of resource usage statistics are reported by the STIMER and
FULLSTIMER options, including real time (elapsed time) and CPU time. Real time
represents the clock time it took to execute a job or step; it is heavily dependent on the
capacity of the system and the current load. As more users share a particular resource,
less of that resource is available to you. CPU time represents the actual processing time
required by the CPU to execute the job, exclusive of capacity and load factors. If you
must wait longer for a resource, your CPU time does not increase, but your real-time
increases. It is not advisable to use real time as the only criterion for the efficiency of
your program. The reason is that you cannot always control the capacity and load
demands on your system. A more accurate assessment of system performance is CPU
time, which decreases more predictably as you modify your program to become more
The statistics reported by FULLSTIMER relate to the three critical computer resources:
I/O, memory, and CPU time. Under many circumstances, reducing the use of any of
these three resources usually results in better throughput of a particular job and a
reduction of real time used. However, there are exceptions, as described in the following
Techniques for Optimizing I/O
Overview of Techniques for Optimizing I/O
I/O is one of the most important factors for optimizing performance. Most SAS jobs
consist of repeated cycles of reading a particular set of data to perform various data
analysis and data manipulation tasks. To improve the performance of a SAS job, you
must reduce the number of times SAS accesses disk or tape devices.
To do this, you can modify your SAS programs to process only the necessary variables
and observations by:
using WHERE processing
using DROP and KEEP statements
using LENGTH statements
using the OBS= and FIRSTOBS= data set options
You can also modify your programs to reduce the number of times it processes the data
internally by:
creating SAS data sets
using indexes
accessing data through SAS views
using engines efficiently
Techniques for Optimizing I/O 197

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