In my last note on index usage I introduced the idea of looking at v$segstat (or v$segment_statistics) and comparing the “logical reads” statistic with the “db block changes” statistic as an indicator of whether or not the index was used in execution plans. This week I’ll explain the idea and show you some results – with a little commentary – from a production system that was reported on the OTN database forum.
The question of how to identify indexes that could be dropped re-appeared (yet again) on the OTN database forum last week. It’s not really surprising that it recurs so regularly – the problem isn’t an easy one to solve but new (and even less new) users keep hoping that there’s a quick and easy solution.
There are, however, strategies and pointers that can help you to optimise the trade-off between effort, risk, and reward. Broadly the idea is to spend a small amount of effort finding a relatively small number of “expensive” indexes that might be safe to drop, so that when you do the detailed analysis you have a good chance that the time spent will be rewarded by a positive result.
Before we get to some results posted on OTN, it’s worth thinking about the global impact and what we’re trying to achieve, and the threats that go with our attempt to achieve it.
I need to check if at least one record present in table before processing rest of the statements in my PL/SQL procedure. Is there an efficient way to achieve that considering that the table is having huge number of records like 10K.
I don’t think many readers of the forum would consider 10K to be a huge number of records; nevertheless it is a question that could reasonably be asked, and should prompt a little discssion.
First question to ask, of course is: how often do you do this and how important is it to be as efficient as possible. We don’t want to waste a couple of days of coding and testing to save five seconds every 24 hours. Some context is needed before charging into high-tech geek solution mode.
Several years go (eight to be precise) I wrote a note suggesting that Oracle will not materialize a factored subquery unless it is used at least twice in the main query. I based this conclusion on a logical argument about the cost of creating and using a factored subquery and, at the time, I left it at that. A couple of years ago I came across an example where even with two uses of a factored subquery Oracle still didn’t materialize even though the cost of doing so would reduce the cost of the query – but I never got around to writing up the example, so here it is:
This whole thing about “not exists” subqueries can run and run. In the previous episode I walked through some ideas of how the following query might perform depending on the data, the indexes, and the transformation that the optimizer might apply:
Some time ago I pulled off the apocryphal “from 2 hours to 10 seconds” trick for a client using a technique that is conceptually very simple but, like my example from last week, falls outside the pattern of generic SQL. The problem (with some camouflage) is as follows: we have a data set with 8 “type” attributes which are all mandatory columns. We have a “types” table with the same 8 columns together with two more columns that are used to translate a combination of attributes into a specific category and “level of relevance”. The “type” columns in the types table are, however, allowed to be null although each row must have at least one column that is not null – i.e. there is no row where every “type” column is null.
I think the “mini-series” is a really nice blogging concept – it can pull together a number of short articles to offer a much better learning experience for the reader than they could get from the random collection of sound-bites that so often typifies an internet search; so here’s my recommendation for this week’s mini-series: a set of articles by Sayan Malakshinov a couple of years ago comparing the behaviour of Deterministic Functions and Scalar Subquery Caching.
Because you can never have enough of a good thing.
Here’s a thought – The optimizer doesn’t treat all constants equally. No explanations, just read the code – execution plans at the end:
This is the second part of a series of blogpost on Oracle database PGA usage. See the first part here. The first part described SGA and PGA usage, their distinction (SGA being static, PGA being variable), the problem (no limitation for PGA allocations outside of sort, hash and bitmap memory), a resolution for Oracle 12 (PGA_AGGREGATE_LIMIT), and some specifics about that (it doesn’t look like a very hard limit).
But this leaves out Oracle version 11.2. In reality, the vast majority of the database that I deal with at the time of writing is at version 11.2, and my guess is that this is not just the databases I deal with, but a general tendency. This could change in the coming time with the desupport of Oracle 11.2, however I suspect the installed base of Oracle version 12 to increase gradually and smoothly instead of in a big bang.
It’s been about 8 months since I posted a little note about a “notable change in behaviour” of the optimizer when dealing with subqueries in the where clause that could be used to return a constant, e.g.:
select * from t1 where id between (select 10001 from dual) and (select 90000 from dual) ;
There’s been a note at the start of the script ever since saying: Check if this is also true for any table with ‘select fixed_value from table where primary = constant’ I finally had a few minutes this morning (San Francisco time) to check – and it does, in both 184.108.40.206 and 220.127.116.11. With the t1 table from the previous article run the following: