It has taken much longer than I anticipated to get around to writing part 3 of this mini-series on what Oracle has done about histograms in 12c.
In part 1 I gave a thumbnail sketch of the three types of histogram available in 12c
In part 2 I described in some detail the improvements in performance and accuracy for the frequency and top-frequency histograms
Or – to be more accurate – real statistics on a virtual column.
This is one of the “10 top tips” that I came up with for my session with Maria Colgan at OOW13. A method of giving more information that might improve execution plans when you can change the code. I’ll start with a small data set including a virtual column (running 126.96.36.199), and a couple of problem queries:
Here’s a little demo cut-n-pasted from a session running Oracle 188.8.131.52 (it works on 11g, too). All it does is create a table by copying from a well-known table, gather extended stats on a column group, then show you the resulting column names by querying view user_tab_cols.
Here’s a funny little problem I came across some time ago when setting up some materialized views. I have two tables, orders and order_lines, and I’ve set up materialized view logs for them that allow a join materialized view (called orders_join) to be fast refreshable. Watch what happens if I refresh this view just before gathering stats on the order_lines table.
I have a little script that start with “set echo on”, then calls two packaged procedures, one to refresh the join view, the other to collect stats on the order_lines table; here’s the output from that script:
I posted a couple of examples some time ago of oddities and boundary cases for frequency histograms on character columns. Part of the process of playing around with the 12c Beta was to re-run such cases to see if newer code made any difference. Looking at these examples, one was fixed (or improved, at least) the other wasn’t, so I’ve added a footnote to each and produced this little note to highlight the changes:
In part 2 of this mini-series I’ll be describing the new mechanism for the simple frequency histogram and the logic of the Top-N frequency histogram. In part 3 I’ll be looking at the new hybrid histogram. You need to know about the approximate NDV before you start – but there’s a thumbnail sketch at the end of the posting if you need a quick reminder.
To allow for collection of simple frequency histogram – record the first rowid for each hash value generated and count the number of times the hash value is generated. If, by the end of the table you have no more than the requested (default 254, max 2,000) distinct hash values you can look up the actual values with a query by rowid.
I’ve mentioned “linear decay” in several posts when explaining a problem that someone has seen with an execution path – but I’ve recently realised that I don’t have a post describing what it is and how it works – although it’s in Cost Based Oracle – Fundamentals, of course, if you want some detail – so here’s a brief introduction (based on simple stats with no histograms).
There are a few enhancements in 12c that might make a big difference to performance for a small investment in effort. One of the important enhancements comes from changes in histograms – which improve speed of collection with accuracy of results. The changes are so significant that I chose the topic as my presentation at OpenWorld last year.
Here’s a couple of extracts from a trace file after I’ve set optimizer_dynamic_sampling to level 3. I’ve run two, very similar, SQL statements that both require dynamic sampling according to the rules for the parameter – but take a look at the different ways that sampling has happened, and ask yourself what’s going on:
Statement 1 produced this sampling code: