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Band Join 12c

One of the optimizer enhancements that appeared in 12.2 for SQL is the “band join”. that makes certain types of merge join much more  efficient.  Consider the following query (I’ll supply the SQL to create the demonstration at the end of the posting) which joins two tables of 10,000 rows each using a “between” predicate on a column which (just to make it easy to understand the size of the result set)  happens to be unique with sequential values though there’s no index or constraint in place:

Uniquely parallel

Here’s a surprising (to me) execution plan from – parallel execution to find one row in a table using a unique scan of a unique index – produced by running the following script (data creation SQL to follow):

Accelerating Oracle E-Business Suites upgrades

Taking backups during development, testing, or upgrades

The process of upgrading an Oracle E-Business Suites (EBS) system is one requiring dozens or hundreds of steps. Think of it like rock climbing. Each handhold or foothold is analogous to one of the steps in the upgrade.

What happens if you miss a handhold or foothold?

If you are close to the ground, then the fall isn’t dangerous. You dust yourself off, take a deep breath, and then you just start climbing again.

But what happens if you’re 25 or 35 feet off the ground? Or higher?


A posting on the OTN database forum a few days ago demonstrated an important problem with hinting – especially (though it didn’t come up in the thread)  in the face of upgrades. A simple query needed a couple of hints to produce the correct plan, but a slight change to the query seemed to result in Oracle ignoring the hints. The optimizer doesn’t ignore hints, of course, but there are many reasons why it might have appeared to so I created a little demonstration of the problem – starting with the following data set:


One of the questions that came up at the Optimizer Round Table this year was about minimizing the performance-related** hassle of upgrading from 11g to 12c. Dealing with changes in the optimizer is always an an interesting problem but in 12c this is made more challenging because of the automatic dynamic sampling that can introduce a significant amount of extra work at (hard) parse time, then generate SQL Directives, and finally generate extended (column group) statistics the next time you (or the automatic job) collect stats.


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.


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:


One of the worst problems with upgrades is that things sometimes stop working. A particular nuisance is the execution plan that suddenly stops appearing, to be replaced by an alternative plan that is much less efficient.

Apart from the nuisance of the time spent trying to force the old plan to re-appear, plus the time spent working out a way of rewriting the query when you finally decide the old plan simply isn’t going to re-appear, there’s also the worry about WHY the old plan won’t appear. Is it some sort of bug, is it that some new optimizer feature has disabled some older optimizer feature, or is it that someone in the optimizer group realised that the old plan was capable of producing the wrong results in some circumstances … it’s that last possibility that I find most worrying.

MySQL Upgrades

I read Wim Coekaerts post about the MySQL 5.6.20-4 this morning. I logged on to my server and did the following command as root.

# yum update -y

That’ll be the upgrade done then… :)

If you are using MySQL on Linux you can use the MySQL Repository for your distribution, rather than using the bundled MySQL version, to make sure you stay up to date with the latest and greatest. As long as you stay within a point release (5.6, 5.7 etc.) of the latest version, upgrades should really be as simple as a “yum update”.

NVL() change

One of the problems of functions is that the optimizer generally doesn’t have any idea on how a predicate based on function(col) might affect the cardinality. However,  the optimizer group are constantly refining the algorithms to cover an increasing number of special cases more accurately. This is a good thing, of course – but it does mean that you might be unlucky on an upgrade where a better cardinality estimate leads to a less efficient execution plan. Consider for example the simple query (where d1 is column of type date):

select	*
from	t1
where	nvl(d1,to_date('01-01-1900','dd-mm-yyyy')) < sysdate

Now, there are many cases in many versions of Oracle, where the optimizer will appear to calculate the cardinality of

nvl(columnX,{constant}) operator {constant}

as if it were: