Index maintenance is all too often overlooked and can, over time, have a serious impact on performance. Ever growing indexes account for large amounts of wasted space and failing to perform regular index rebuilds on dynamic application tables is just throwing away performance.
When APPLSYS has over a thousand indexes the OEBS application has over 60,000 indexes (version and module dependant) it often gets too hard to identify what indexes require rebuilding and they simply don’t get rebuilt. Believe it or not, most sites I visit have not rebuilt indexes on even the basic regularly purged objects such as concurrent requests and sign-on audit tables in years.
A site I recently reviewed generates approximately 35,900 fnd_concurrent _requests records per day which are being purged nightly holding 7 days history on-line. The indexes had not been rebuilt for over 4 years. Thus in this instance the base table should be holding approximately 251,000 records whereas the primary key index fnd_concurrent_requests_u1 would be holding approximately 52 million rows. 99.9% deleted rows. This is an interesting one when you calculate the space the index is holding, I estimate over 1.4 Gb for fnd_concurrent_requests_u1 alone.
In this paper we will provide a simple list of indexes to start with, and a method of identifying if any of these indexes should be rebuilt.
We also cover why you should exercise caution when using an auto index rebuild script you find on the web, some do not readily translate to an OEBS environment
The full paper can be found at http://www.piper-rx.com/pages/tips.html - Look for "Rebuilding indexes in an OEBS environment" in the tips section
About this blog
As with my website, my blogs espouse the philosophy “not all performance problems are technical” and that in most stable environments user behaviour / usage patterns are typically the source of most correctable performance problems. So if you are into bits, bytes, locks, latches etc this is not the place for you, but if you are after ways to genuinely enhance performance and work with your systems and customers to achieve better, more predictable performance, read on.