We found a bug in some old code. And we fixed it. Then other stuff started failing. It turned out that there were some other code, using the same function, that worked because of the bug. That forced us to roll back the fix and thereby re-introduce the initial bug that weren’t as critical.
So – we had to find a way to find out which code-paths were working because of the bug so we could fix those.
In my previous post, I showed how you can add a fake hint to tag the origin of a duplicated statement and as a side-effect make it unique. What if you regret and can’t remember where it was. Or you want to review old hinted statements after an upgrade to a newer version of the database/optimizer.
Finding duplicate SQL statements using PL/Scope is easy. If you cannot merge them, how can you differentiate between which source is being run?
On our production system we’ve enabled the collection of PL/Scope metadata. Since this is a SmartDB/PinkDB-application (business logic and queries in the database), this makes it really easy to find, inspect and modify the source code of queries that doesn’t run efficiently. Now it’s even easier using reports in Oracle SQL Developer.
Working on a routine for dropping old partitions from a log table, I realized that I don’t have to know the name of the partition I want to drop. I can just specify a value for the partition key and Oracle resolves the partition for me. Here’s how.
I had a case where I had to match some names and needed to find a set of ways to clean and match strings. The solution I ended up with was a combination of regular expressions, the NLSSORT-function and the UTL_MATCH-package with the Jaro-Winkler algorithm.
Oracles function result cache (FRC) can in certain cases give a considerable performance boost. Application context is another useful feature. How does FRC work when the function result relies on context-settings? And how can we make them play well together?
