SQL

I suppose it had to happen eventually but one of my presentations has ended up on YouTube. It’s a recent presentation I did for the Oracle Midlands user group in September.

The topic is (as the title of this blog post hints at!)Boosting select performance by clustering data. The video consists of the slides I presented, changing as the presentation progresses, with my audio over the top. It goes on for a bit, close to an hour, but you could watch a section and then go and do something else before watching a bit more.

I have to say, it is very odd hearing my voice (and the slight touch of the “brummie” {Birmingham} accent coming through) and I do wince at the places where I blather or say something slightly wrong or make a joke that involved a visual element that is lost. Oh well, at least you don’t see me wandering around and jumping up,literally, to point out bits on the slides.

What is the date if you only specify the time when you populate an Oracle date column (or variable)?

That was the question that came up a few days ago in the little DBA team I am currently working in. Of course, the question was posed by the “junior” (who is damned smart at this stuff as he keeps asking questions like that) and the answer from us two old hands was… “Ohh!… hang on… errr….”

A little discussion then occurred. One of us suggested it would be “today”. One of us suggested it would be the Julian 1 date (4712BC). Both of us then stated it was an easy thing to test and the PROPER answer was “just try it and then you will know for sure”. We were right {and, of course, wrong} – as in with a simple question like this you don’t need to google the question (so “hello” to anyone googling the question and finding this page!) you just try it:

The junior tried it and…

I’ve spent the last couple of evenings playing with the new SQL pattern matching feature in Oracle 12c.

• Pattern Matching (MATCH_RECOGNIZE) in Oracle Database 12c Release 1 (12.1)

I’m doing some sessions on analytic functions in some upcoming conferences and I thought I should look at this stuff. I’m not really going to include much, if anything, about it as my sessions are focussed on beginners and I don’t really want to scare people off. The idea is to ease people in gently, then let them scare themselves once they are hooked on analytics. I’m thinking about Hooked on Monkey Fonics now…

#555555;">Every so often a DSS query that usually takes 10 minutes ends up taking over an hour.  (or one that takes an hour never seems to finish)

#555555;">Why would this happen?

#555555;">When investigating the DSS query, perhaps with wait event tracing,  one finds that the query which is doing full table scans and should be doing large multi-block reads and waiting for “db file scattered read” is instead waiting for single block reads, ie “db file sequential read”.  What the heck is going on?

#555555;">Sequential reads during a  full table scan scattered read query is a classic sign of reading rollback and reading rollback can make that minute(s) full table scan take hours.

#555555;">What is right deep verses left deep? Good question. In join trees (not VST) the object on the left is acted upon first then the object on the right.  Below are left deep and right deep examples of the same query, showing

#555555;">
• query text
• join tree
• join tree  modified to more clearly show actions
• VST showing the same actions

#555555;">

Just a quick code snippit. I do a lot of data pumps to move schemas between different databases; for example taking a copy of a schema to an internal database to try to reproduce a problem. Some of these schemas have some very large tables. The large tables aren’t always needed to research a particular problem.

Here’s a quick bit of SQL to list the 20 largest tables by total size – including space used by indexes and LOBs. A quick search on google didn’t reveal anything similar so I just wrote something up myself. I’m pretty sure this is somewhat efficient; if there’s a better way to do it then let me know! I’m posting here so I can reference it in the future. :)

Just a quick code snippit. I do a lot of data pumps to move schemas between different databases; for example taking a copy of a schema to an internal database to try to reproduce a problem. Some of these schemas have some very large tables. The large tables aren’t always needed to research a particular problem.

Here’s a quick bit of SQL to list the 20 largest tables by total size – including space used by indexes and LOBs. A quick search on google didn’t reveal anything similar so I just wrote something up myself. I’m pretty sure this is somewhat efficient; if there’s a better way to do it then let me know! I’m posting here so I can reference it in the future. :)

Just a quick code snippit. I do a lot of data pumps to move schemas between different databases; for example taking a copy of a schema to an internal database to try to reproduce a problem. Some of these schemas have some very large tables. The large tables aren’t always needed to research a particular problem.

Here’s a quick bit of SQL to list the 20 largest tables by total size – including space used by indexes and LOBs. A quick search on google didn’t reveal anything similar so I just wrote something up myself. I’m pretty sure this is somewhat efficient; if there’s a better way to do it then let me know! I’m posting here so I can reference it in the future. :)

Thank you all who attended my sessions at NYOUG Fall Conference this morning. I appreciate spending you most precious commodity - your time - with me. I sincerely hope you found both the presentations enlightening as well as entertaining.

Please see the details of the sessions below along with the download links.

Keynote: Oracle 12c Gee Whiz Features

Yet another Oracle version is out and so are about 1500 new features in a variety of areas. Some are well marketed (e.g. pluggable database or the multitenant option) and some shine by their sheer usefulness. And there are some that do not get a whole lot of coverage but are are hidden gems. In this session you learned 12 broad areas of Oracle Database 12c I feel are worth learning about to make your job as a DBA or developer better, easier, smoother and, in some cases, even make it possible what was hitherto impossible or impractical.

Anyone who has been around Oracle performance over the years knows the grief that hard parsing SQL queries can cause on highly concurrent applications. The number one reason for hard parsing has been applications that don’t use bind variables. Without bind variables queries that would otherwise be shared get recompiled because their text is different and Oracle treats them as different queries. Oracle addressed this issue with a parameter called cursor_sharing. The parameter cursor_sharing has three values

1. exact – the default
2. similar – replace literals with bind variables, if a histogram keep literal in place
3. force – replace literals with bind variables and use existing plan if it exists

Here is what the load looks like going from the default, exact, to the value force on a load of the same query but a query that doesn’t use bind variables: