Pythian Group

Well it was unknown to me until yesterday and possibly this is new thing for no one but me, but lets blog it anyway :)

One of the most nice thing about the newer versions of Oracle is the advent of ASH and AWR as they provide awesome diagnostic information. Many customers at the Pythian use Real Application Cluster and having a cluster wide AWR report by using awrgrpt.sql script is very handy.

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Welcome ASH Masters!

I have already mentioned about the excellent work that Kyle Hailey did around Active Session History (ASH). Kyle has also created ASHMON.

The latest news — there is a new web site — ashmasters.com. This is the place where you can leave your comments and questions about ASH and ASHMON. Wondering how you can query ASH data? There are some ready to use queries. Have a cool idea how to use ASH and query ASH data? Share it there and have it added to the ASH Masters queries toolkit.

I hear, some of you say – “Right… ASH… 10g… Diagnostic Pack…” No panic, there is poor man’s ASH — ASH Simulation. This is the way to get some benefits of ASH while still running Oracle 9i or Oracle 10g without Diagnostic Pack.

Sounds exciting? It does, indeed!

For the past few months I’ve been using a query that I refer to as “ash report – recent spike”. That’s the second thing I do when I get a call of the “the system is slow” type. The first thing I do is run “top” (or whichever alternative for the OS) and check the overall CPU usage.

The script is fully RAC-aware, and although it’s not 100% perfect, I use this imperfection to see if any particular node is doing something stupid. Although it is primarily targeted for OLTP systems, it can be useful for data warehouses as well, especially if they use the parallel option.

The query is to the database what “load” (uptime) for a Linux/Unix machine is, except it has much more detail. It is basically a summarization query of the v$active_session_history table. NOTE: you need to have the performance pack license to use it. It is not designed to be aligned, or read. The best is to leave it on just a few lines and concentrate on the results.

It has two “variables” that you can adjust: how far back to look (I use two hours), and how aggressively to look for problems (having count(*) >= 2).

An explanation of how to make sense of the results follows the query.

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