When the Smart Flash Cache was introduced in Exadata, it was caching reads only. So there were only read “optimization” statistics like cell flash cache read hits and physical read requests/bytes optimized in V$SESSTAT and V$SYSSTAT (the former accounted for the read IO requests that got its data from the flash cache and the latter ones accounted the disk IOs avoided both thanks to the flash cache and storage indexes). So if you wanted to measure the benefit of flash cache only, you’d have to use the cell flash cache read hits metric.
This post also applies to non-Exadata systems as hard drives work the same way in other storage arrays too – just the commands you would use for extracting the disk-level metrics would be different.
I just noticed that one of our Exadatas had a disk put into “predictive failure” mode and thought to show how to measure why the disk is in that mode (as opposed to just replacing it without really understanding the issue ;-)
In the previous post about in-memory parallel execution I described in which cases the in-mem PX can kick in for your parallel queries.
This post applies both to non-Exadata and Exadata systems.
In my previous post ( Advanced Oracle Troubleshooting Guide – Part 11: Complex Wait Chain Signature Analysis with ash_wait_chains.sql ) I introduced an experimental script for analysing performance from “top ASH wait chains” perspective.
I just learned something new yesterday when demoing large page use on Linux during my AOT seminar.
Yes, the title of this post is also a reference to the Machete Kills Again (…in Space) movie that I’m sure going to check out once it’s out ;-)
I received a question about ALTER SYSTEM in the comments section of another blog post recently.
Here’s a treat for the hard-core Oracle performance geeks out there – I’m releasing a cool, but still experimental script for ASH (or poor-man’s ASH)-based wait event analysis, which should add a whole new dimension into ASH based performance analysis. It doesn’t replace any of the existing ASH analysis techniques, but should bring the relationships between Oracle sessions in complex wait chains out to bright daylight much easier than before.
You all are familiar with the AWR/Statspack timed event summary below: