Oracle

Followers of the blog will know I dig virtualization. I first ran Oracle in virtualized environments over a decade ago.

In my current company there is a strong virtualization presence in the Windows space. Pretty much all Windows servers, including those running MS SQL Server, are actually VMs running on a VMware farm. The UNIX/Linux side is a little different. Most stuff is still done on physical boxes and what little virtualization is done, uses CentOS and KVM for freebie open source solutions.

There are a lot of architectural changes going on at the moment and I’ve been pushing *very hard* for a switch to the virtual infrastructure (VI) for all our middle tier servers and a few of our databases. It is looking very likely (but not guaranteed) that this will happen.

It’s very easy to get a lot of information from an AWR (or Statspack) report – provided you remember what all the numbers represent. From time to time I find that someone asks me a question about some statistic and my mind goes completely blank about the exact interpretation; but fortunately it’s always possible to cross check because so many of the statistics are cross-linked. Here’s an example of a brief mental block I ran into a few days ago – I thought I knew the answer, but realised that I wasn’t 100% sure that my memory was correct:

In this Load Profile (for an AWR report of 60.25 minutes), what does that Transactions figure actually represent ?

The promised hacking session about Exadata performance troubleshooting will happen on Thursday 21st February 9am-11am PST (2 hours). I will show a number of examples and demos where the Exadata Snapper shows what was going on in storage cells when running Smart Scans or just doing IO.

Register here (free stuff!):

• https://www1.gotomeeting.com/register/270528161

Slides:

• http://blog.tanelpoder.com/files/Tanel_Poder_Drilling_Deep_Into_Exadata_Performance.pdf

I will post the scripts on the day of this session.

Here’s an example of a quick’n'dirty way of profiling stack traces on your command line. This is an example from Solaris (but the script should work on Linux too plus other Unixes with minor modifications).

I created a problem case below, based on a case I once troubleshooted at a client site. Note that they had set optimizer_mode = FIRST_ROWS in their database and the optimized came up with a very inefficient execution plan for the select from DBA_LOCK_INTERNAL view below:

SQL> ALTER SESSION SET optimizer_mode = FIRST_ROWS;

Session altered.

SQL> SET TIMING ON

SQL> SELECT * FROM dba_lock_internal;
...
... the output data stripped ...
...

927 rows selected.

Elapsed: 00:23:27.14

It took over 23 minutes to return 927 rows from DBA_LOCK_INTERNAL!

I ran Snapper to see where the time is spent then:

I’m working out my 2013 high-level plans and something dawned on me. I’m not sure I know what the term knowledge-sharing means any more.

That’s SQL Tuning Sets, optimizer_features_enable, and SQL Plan Management.

There’s a recent post on OTN describing an issue when using SQL Tuning Sets to enforce plan stability when upgrading from 10.2.0.3 to 11.2.0.3 – it doesn’t always work. Here’s a very simple model to demonstrate the type of thing that can happen (the tables are cloned from a completely different demo, so don’t ask why I picked the data they hold):

I was at a client site recently where one of the end-users seemed to have discovered a cunning strategy for optimising a critical SQL statement. His problem was that his query screen times out after 2 minutes, so any query he runs has to complete in less than two minutes or he doesn’t see the results. Unfortunately he had a particular query which took nearly 32 minutes from cold to complete – partly because it’s a seven-table join using ANSI OUTER joins, against tables ranging through the 10s of millions of rows and gigabytes of data – the (necessary) tablescan of the table that had to be first in the join order took 70 seconds alone.