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Cardinality Change

Here’s an entertaining little change across versions of Oracle, brought to my attention by Tony Hasler during UKOUG Tech 14. It’s a join cardinality estimate, so here are a couple of tables to demonstrate the issue – the only columns needed are the alpha_06 columns, but I reused some code from other demonstrations to create my test case, so there are lots of irrelevant columns in the create table script:

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It’s been a long time since I said anything interesting about transitive closure in Oracle, the mechanism by which Oracle can infer that if a = b and b = c then a = c but only (in Oracle’s case) if one of a, b, or c is a literal constant rather than a column. So with that quick reminder in place, here’s an example of optimizer mechanics to worry you. It’s not actually a demonstration of transitive closure coming into play, but I wanted to remind you of the logic to set the scene.

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I have a simple script that creates two identical tables , collects stats (with no histograms) on the pair of them, then executes a join. Here’s the SQL to create the first table:

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Lunchtime quiz

There was a question on OTN a few days ago asking the following question:

Here’s a query that ran okay on 11g, but crashed with Oracle error “ORA-01843: not a valid month” after upgrade to 12c; why ?

The generically correct answer, of course, is that the OP had been lucky (or unlucky, depending on your point of view) on 11g – and I’ll explain that answer in another blog posting.

That isn’t the point of this posting, though. This posting is a test of observation and deduction. One of the respondants in the thread had conveniently supplied a little bit of SQL that I copied and fiddled about with to demonstrate a point regarding CPU costing, but as I did so I thought I’d show you the following and ask a simple question.’

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I’m not very keen on bending the rules on production systems, I’d prefer to do things that look as if they could have happened in a completely legal fashion, but sometimes it’s necessary to abuse the system and here’s an example to demonstrate the point. I’ve got a simple SQL statement consisting of nothing more than an eight table join where the optimizer (on the various versions I’ve tested, including 12c) examines 5,040 join orders (even though _optimizer_max_permutations is set to the default of 2,000 – and that might come as a little surprise if you thought you knew what that parameter was supposed to do):

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Parallel Costs

While creating a POC of a SQL rewrite recently I received a little surprise as I switched my query from serial execution to parallel execution and saw the optimizer’s estimated cost increase dramatically. I’ll explain why in a moment, but it made me think it might be worth setting up a very simple demonstration of the anomaly. I created a table t1 by copying view all_source – which happened to give me a table with about 100,000 rows and 1117 blocks – and then ran the query ‘select max(line) from t1;’ repeating the query with a /*+ parallel(t1 2) */ hint. From here are the two execution plans I got:

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Quantum Data

That’s data that isn’t there until you look for it, sort of, from the optimizer’s perspective.

Here’s some code to create a sample data set:

create table t1
with generator as (
	select	--+ materialize
		rownum id
	from dual
	connect by
		level <= 1e4
	rownum					id,
	mod(rownum-1,200)			mod_200,
	mod(rownum-1,10000)			mod_10000,
	lpad(rownum,50)				padding
	generator	v1,
	generator	v2
	rownum <= 1e6

		ownname		 => user,
		tabname		 =>'T1',
		method_opt 	 => 'for all columns size 1'

Now derive the execution plans for a couple of queries noting, particularly, that we are using queries that are NOT CONSISTENT with the current state of the data (or more importantly the statistics about the data) – we’re querying outside the known range.

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Plan puzzle

I was in Munich a few weeks ago running a course on Designing Optimal SQL and Troubleshooting and Tuning, but just before I flew in to Munich one of the attendees emailed me with an example of a statement that behaved a little strangely and asked me if we could look at it during the course.  It displays an odd little feature, and I thought it might be interesting to write up what I did to find out what was going on. We’ll start with the problem query and execution plan:

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Cardinality Feedback

A fairly important question, and a little surprise, appeared on Oracle-L a couple of days ago. Running a query completed quickly on the first execution then ran very slowly on the second execution because Oracle had used cardinality feedback to change the plan. This shouldn’t really be entirely surprising – if you read all the notes that Oracle has published about cardinality feedback – but it’s certainly a little counter-intuitive.

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No, not the 10th posting about first_rows() this week – whatever it may seem like – just an example that happens to use the “calculate costs for fetching the first 10 rows” optimizer strategy and does it badly. I think it’s a bug, but it’s certainly a defect that is a poster case for the inherent risk of using anything other than all_rows optimisation.  Here’s some code to build a couple of sample tables:

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