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Execution plans

E-rows / A-rows

This note was prompted by an error I made at the UKOUG TechFest19 yesterday. It’s fairly well-known that when you read an execution plan that includes the rowsource execution stats – so you get the E-rows (estimated) and A-rows (Actual) reported – then a sensible check of the quality of the optimizer’s calculations is to compare the estimates and actuals allowing for the fact that the E-rows is “per start” and the A-rows is “cumulative”, so A-rows = E-rows * Starts.

The error I made yesterday was to forget that this relationship isn’t always true. In particular partitioning and parallel query introduced the need to be a little flexibility in reading the numbers – which I’ll demonstrate with a coupld of simple examples running under 12.2.0.1

IOT Hash

It’s another of my double-entendre titles. The optimizer can turn a hash join involving an index-organized table into a real performance disaster (though you may have to help it along the way by using a silly definition for your primary key columns). This post was inspired by a question posted on the Oracle Developer Community forum recently so the table and column names I’ve used in my model reflect (almost, with a few corrections) the names used in the post.

We start with a simple requirement expressed through the following SQL:

ANSI Plans

Here’s a thought that falls somewhere between philosophical and pragmatic. It came up while I was playing around with a problem from the Oracle database forum that was asking about options for rewriting a query with a certain type of predicate. This note isn’t really about that question but the OP supplied a convenient script to demonstrate their requirement and I’ve hi-jacked most of the code for my own purposes so that I can ask the question:

Should the presence of an intermediate view name generated by the optimizer in the course of cost-based query transformation cause two plans, which are otherwise identical and do exactly the same thing, to have different plan hash values ?

To demonstrate the issue let’s start with a simple script to create some data and generate an execution plan.

v$session

Here’s an odd, and unpleasant, detail about querying v$session in the “most obvious” way. (And if you were wondering what made me resurrect and complete a draft on “my session id” a couple of days ago, this posting is the reason). Specifically if you want to select some information for your own session from v$session the query you’re likely to use in any recent version of Oracle will probably be of the form:


select {list for columns} from v$session where sid = to_number(sys_context('userenv','sid'));

Unfortunately that one little statement hides two anomalies – which you can see in the execution plan. Here’s a demonstration cut from an SQL*Plus session running under 19.3.0.0:

Negative Offload

At the Trivadis Performance Days 2019 I did a presentation on using execution plans to understand what a query was doing. One of the examples I showed was a plan from an Exadata system (using 11.2.0.4) that needed to go faster. The plan was from the SQL Monitor report and all I want to show you is one line that’s reporting a tablescan. To fit the screen comfortably I’ve removed a number of columns from the output.

The report had been generated while the statement was still running (hence the “->” at the left hand edge) and the query had scanned 166 segments (with no partition elimination) of a table with 4,500 data segments (450 range partitions and 10 hash sub-partitions – note the design error, by the way, hash partitioning in Oracle should always hash for a powert of 2).

Optimizer Tricks 1

I’ve got a number of examples of clever little tricks the optimizer can do to transform your SQL before starting in on the arithmetic of optimisation. I was prompted to publish this one by a recent thread on ODC. It’s worth taking note of these tricks when you spot one as a background knowledge of what’s possible makes it much easier to interpret and trouble-shoot from execution plans. I’ve labelled this one “#1” since I may publish a few more examples in the future, and then I’ll have to catalogue them – but I’m not making any promises about that.

Here’s a table definition, and a query that’s hinted to use an index on that table.

Free Space

Several years ago I wrote a note about reporting dba_free_space and dba_extents to produce a map of the space usage in a tablespace in anticipation of messing about with moving or rebuilding objects to try and reduce the size of the files in the tablespace.  In the related page where I published the script I pointed out that a query against dba_extents would be expensive because it makes use of structure x$ktfbue which generates the information dynamically by reading segment header blocks.

opt_estimate 5

If you’ve been wondering why I resurrected my drafts on the opt_estimate() hint, a few weeks ago I received an email containing an example of a query where a couple of opt_estimate() hints were simply not working. The critical features of the example was that the basic structure of the query was of a type that I had not previously examined. That’s actually a common type of problem when trying to investigate any Oracle feature from cold – you can spend days thinking about all the possible scenarios you should model then the first time you need to do apply your knowledge to a production system the requirement falls outside every model you’ve examined.

Before you go any further reading this note, though, I should warn you that it ends in frustration because I didn’t find a solution to the problem I wanted to fix – possibly because there just isn’t a solution, possibly because I didn’t look hard enough.

opt_estimate 4

In the previous article in this series on the opt_estimate() hint I mentioned the “query_block” option for the hint. If you can identify a specify query block that becomes an “outline_leaf” in an execution plan (perhaps because you’ve deliberately given an query block name to an inline subquery and applied the no_merge() hint to it) then you can use the opt_estimate() hint to tell the optimizer how many rows will be produced by that query block (each time it starts). The syntax of the hint is very simple:

opt_estimate 3

This is just a quick note to throw out a couple of of the lesser-known options for the opt_estimate() hint – and they may be variants that are likely to be most useful since they address a problem where the optimizer can produce consistently bad cardinality estimates. The first is the “group by” option – a hint that I once would have called a “strategic” hint but which more properly ought to be called a “query block” hint. Here’s the simplest possible example (tested under 12.2, 18.3 and 19.2):