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Function Based Indexes

Index Usage – 4

Here’s a thought that came to me while I was writing up a note about identifying redundant indexes a few minutes ago. Sometimes you end up supporting applications with unexpected duplication of data and indexes and need to find ways to reduce overheads. Here’s some code modelling a scenario that I’ve seen more often than I like (actually, just once would be more often than I’d like):

Index Usage – 2

I’ve been a little slow in the follow-up to my previous posting on possibly redundant indexes. Before going into the slightly more complex stuff, there’s another peripheral point (but a very important one) that’s worth raising about how clever the optimizer can be. Here’s some code for 11.2.0.4 to demonstrate the point:

Easy – Oops.

A question came up on OTN today asking for suggestions on how to enforce uniqueness on a pair of columns only when the second column was not null. There’s an easy and obvious solution – but I decided to clone the OP’s example and check that I’d typed my definition up before posting it; and the result came as a bit of a surprise. Here’s a demo script (not using the OP’s table):

Easy – Oops.

A question came up on OTN today asking for suggestions on how to enforce uniqueness on a pair of columns only when the second column was not null. There’s an easy and obvious solution – but I decided to clone the OP’s example and check that I’d typed my definition up before posting it; and the result came as a bit of a surprise. Here’s a demo script (not using the OP’s table):

Tweaking

The following question came up on OTN recently:

Which one gives better performance? Could please explain.

1) nvl( my_column, ‘N’) <> ‘Y’

2) nvl( my_column, ‘N’) = ‘N’

It’s a question that can lead to a good 20 minute discussion – if you were in some sort of development environment and had a fairly free hand to do whatever you wanted.

The most direct answer is that you could expect the performance to be the same whichever option you chose – but the results might be different, of course, unless you had a constraint on my_column that ensured that it would hold only null, ‘Y’, or ‘N’.  (Reminder:  the constraint check (my_column in (‘Y’,’N’) will allow nulls in the column).

Tweaking

The following question came up on OTN recently:

Which one gives better performance? Could please explain.

1) nvl( my_column, ‘N’) <> ‘Y’

2) nvl( my_column, ‘N’) = ‘N’

It’s a question that can lead to a good 20 minute discussion – if you were in some sort of development environment and had a fairly free hand to do whatever you wanted.

The most direct answer is that you could expect the performance to be the same whichever option you chose – but the results might be different, of course, unless you had a constraint on my_column that ensured that it would hold only null, ‘Y’, or ‘N’.  (Reminder:  the constraint check (my_column in (‘Y’,’N’) will allow nulls in the column).

Min/Max

One of my most-repeated observations about trouble-shooting Oracle is that things break when you start combining features. Here’s an example that demonstrates the point.

It’s possible to create “descending” indexes – or indexes with descending columns, as I prefer to call them, and there’s a special “min/max range scan” optimizer operation for a particular kind of index usage – demonstrated in the following code fragment (running under 11.2.0.4, and reporting the rowsource execution statistics):

Min/Max

One of my most-repeated observations about trouble-shooting Oracle is that things break when you start combining features. Here’s an example that demonstrates the point.

It’s possible to create “descending” indexes – or indexes with descending columns, as I prefer to call them, and there’s a special “min/max range scan” optimizer operation for a particular kind of index usage – demonstrated in the following code fragment (running under 11.2.0.4, and reporting the rowsource execution statistics):

Auto Sample Size

In the past I have enthused mightily about the benefits of the approximate NDV mechanism and the benefit of using auto_sample_size to collect statistics in 11g; however, as so often happens with Oracle features, there’s a down-side or boundary condition, or edge case. I’ve already picked this up once as an addendum to an earlier blog note on virtual stats, which linked to an article on OTN describing how the time taken to collect stats on a table increased dramatically after the addition of an index – where the index had this definition:

FBI Skip Scan

A recent posting on the OTN database forum highlighted a bug (or defect, or limitation) in the way that the optimizer handles index skip scans with “function-based” indexes – it doesn’t do them. The defect has probably been around for a long time and demonstrates a common problem with testing Oracle – it’s very easy for errors in the slightly unusual cases to be missed; it also demonstrates a general principle that it can take some time for a (small) new feature to be applied consistently across the board.

The index definitions in the original posting included expressions like substr(nls_lower(colX), 1, 25), and it’s possible for all sorts of unexpected effects to appear when your code starts running into NLS  settings, so I’ve created a much simpler example. Here’s my table definition, with three index definitions: