[Forward to Part 2]
“How do you interpret statspack data ?”
If you go for a generic answer, it’s likely to be a long answer – but the first step is always the classic “Tom Kyte turnaround” … Why do you want to interpret Statspack data ?
As “a starter for ten” [Ed: a reference that may be familiar only to UK viewers of the quiz show Univeristy Challenge], I’m just going to float one thought: there are three reasons for looking at Statspack data and the reason dictates the approach, and the significance you attach to the data.
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Coming a close second to the “rebuild indexes regularly” fairy tale is the “a column with a small number of distinct values is a good candidate for a bitmap index” legend.
I’ve had to explain the error in the legend three times in the last month, so I thought I’d just point to a series of articles I wrote some time ago that might save people from wasting too much effort the next time they start to play with bitmap indexes.
All three articles were written several years ago; so when you review them, remember the advice I gave in an earlier post.
If you take a look at view user_tab_columns (or equivalent) you will find that its definition includes columns low_value and high_value, which give the currently known low and high value for the data. For example:
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