In a previous article, The Node Less Traveled: Improving Job Performance with Node Profile Logs, I described the use of node profile logging to help pinpoint underperforming areas of SAS Data Management Platform jobs. In that article, however, I only hinted at corrections that could be made to eliminate inefficient code and incorrect settings that might be contributing to the problem.
Since I don’t want to leave you stranded in your attempts to optimize Data Management Platform jobs, I’ve compiled a “top 10 list” of process-tuning techniques. With these tips, you’ll have your data management jobs performing at top speed in no time.
There you have it—a list of some of the most effective ways to speed up data management job performance. Many of these techniques don’t even require reworking of you job logic; you only have to change a few node options. Some of these tips do however require a rethinking of the job data flow. Understanding that “forewarned is forearmed,” review these suggestions before the design phase of your next project and you will be running at top speed from the very beginning.
Do you have any additional tips? Have you used any pointers mentioned here and seen improvements? Share your thoughts below.