statistics

No-one should be using exp/imp to export and import data any more, they should be using the datapump equivalents expdp/impdp – but if you’re on an older (pre-12c) version of Oracle and still using exp/imp to do things like moving tables with their production statistics over to test systems then be careful that you don’t fall into an obsolescence trap when you finally upgrade to 12c (or Oracle 18).

exp/imp will mess up some of your histograms if you’re still using them to move tables/statistics in 12c.

There’s a question on the ODC database forum about column groups that throws up an interesting side point. The OP is looking at a query like the following and asking about which column groups might help the optimizer get the best plan:

Here is a little script I use from time to time to look at V$MYSTAT values and displaying on one line a set of statistics with their delta value between two calls.

The first script, _mystat_init.sql, initializes the variables. The second one displays the values, such as:

SQL> @ _mystat_diff.sql
 
db block changes redo size undo change vector size redo entries
---------------- ---------------- ----------------------- ----------------
57,371 15,445,852 6,111,608 37,709


Have you ever seen a result like this:

SQL> select sql_id, count(*) from V$sql group by sql_id having count(*) > 1000;

SQL_ID		COUNT(*)
------------- ----------
1dbzmt8gpg8x7	   30516

A client of mine who had recently upgraded to 12.2.0.1 RAC, using DRCP (database resident connection pooling) for an application using PHP was seeing exactly this type of behaviour for a small number of very simple SQL statements and wanted to find out what was going on because they were also seeing an undesirable level of contention in the library cache when the system load increased.

In this note I just want to highlight a particular detail of their problem – with an example – showing how easily histograms can introduce problems if you don’t keep an eye out for the dangers.

One of their queries really was as simple as this:

I had a sudden urge to go a bit meta – so here’s a relative frequency histogram of my observations of the general use of histograms in Oracle:

I’ve made several comments in the past about the need for being selective when gathering objects statistics with particular reference to the trade-offs when creating histograms. With Oracle 12c it’s now reasonably safe (as far as I’m concerned) to set a method_opt as a table preference that identifies columns where you expect to see Frequency or (pace the buggy behaviour described in a recent post) a Top-N histograms. The biggest problem I have is that I keep forgetting the exact syntax I need – so I’ve written this note more as a reminder to myself than anything else.

I came across a simple performance problem recently that ended up highlighting a problem with the 12c hybrid histogram algorithm. It was a problem that I had mentioned in passing a few years ago, but only in the context of Top-N histograms and without paying attention to the consequences. In fact I should have noticed the same threat in a recent article by Maria Colgan that mentioned the problems introduced in 12c by the option “for all columns size repeat”.

So here’s the context (note – all numbers used in this example are approximations to make the arithmetic obvious).  The client had a query with a predicate like the follwing:

This blog post is part of a series that discusses how to get optimal performance from PeopleSoft nVision reporting as used in General Ledger.

If you do not partition your selector tables, and if you predominantly use static selectors then you can maintain the statistics on the selector table as the new static selectors are created or updated.  PeopleTools table PSTREESELCTL is used to track static selectors.  It is keyed by selector number.  A row is inserted when a new selector is created, and the version number is updated when an existing selector is re-extracted.  Therefore, a trigger on this table can be used to submit a job to refresh the statistics on the tree selector.

This blog post is part of a series that discusses how to get optimal performance from PeopleSoft nVision reporting as used in General Ledger.

The decision to use interval partitioning on the tree selector tables came from the need to have accurate statistics for the optimizer when parsing nVision queries.  It is not possible to introduce hints into nVision SQL. The dynamic nature of the code means it is not viable to consider any of the forms of database plan stability across the whole application, (although it may be possible to use SQL Profiles in limited cases). Therefore, as far as possible the optimizer has to choose the best plan on its own. Without accurate optimizer statistics, I have found that the optimizer will usually not choose to use a Bloom filter.

In my UKOUG OracleScene article on 12c online statistics and GTT I mentioned the following:

A final note about those 12c changes in statistics gathering on GTT. In 11g the dbms_stats did a commit at the start. So if you did gather stats after the load, you had to set the GTT as ON COMMIT PRESERVE ROWS. Or you just vacuum what you’ve loaded. That has changed in 12c. If you now choose to do a conventional insert followed by dbms_stats (having set private stats of course) then you don’t need to set on commit preserve rows anymore.

Today, I realized that I’ve never explained exactly when dbms_stats.gather_table_stats commits the transaction or not. Because, of course, it depends. In summary: 12c non-SYS owner GTT with private statistics.