On the Accuracy of Exponentials and Expositions

The following is a slightly edited version of my response to a Discussion on the Linkedin CPPE group, which is accessible to Members Only. It's written in the style of a journal reviewer. The original Discussion topic was based on a link to a blog-post. I've been asked to make my Linkedin review more widely available so, here tiz...

The blog-post Capacity Planning on a Cocktail Napkin is a really good example of a really bad explanation. There are so many things that are misleading, at best, and flat-out wrong, at worst, it's hard to know where to begin (or where to stop). Nevertheless, I'll try to keep it brief [I failed in that endeavor. — njg].

The author applies the equation:

\begin{equation} E = λ \end{equation}

Why? What is that equation? We don't know because the author does not say yet what all the symbols mean. It's all very well to impress people by slinging equations around, but it's more important to say what the equations actually mean. After all, the author might have chosen the wrong one.

Hotsos Symposium 2012

Time Bandits: How to Analyze Fractal Query Times

Tues, March 6, 2012 @ 2:15 pm

That's the title of my presentation at this year's Hotsos Symposium and no, I won't be trying to make any obscure connections between Terry Gilliam's famous movie and Oracle database products (as interesting as that exercise might be).

Instead, I'll be talking about fractals in time and how they can impact performance—especially Oracle database performance. The responsiveness of your Oracle application can be lost for longer than expected periods of time, ostensibly stolen by time bandits.

Preview Slides (2012). A more detailed explanation of the fractal technique used is now provided in the Guerrilla Data Analytics (GDAT) class: How to Get Beyond Monitoring from Linear Regression to Machine Learning.

Green Disk Sizing

I finally got around to completing item 5 on my 2011 list concerning electrical power consumed by a magnetic hard disk drive (HDD). The semi-empirical statement is:

Power ∝ N_platters × Ω^2.8 × D^4.6    . . .    (1)

where N_platters is the number of platters on the spindle, Ω is the rotational speed in revolutions per minute (RPM) and D the platter diameter in inches. The power consumed is then measured in Watts.

In principle, this makes (1) valuable for doing green HDD storage capacity planning. The bad news is, it is not in the form of an equation but a statement of proportionality, so it can't be used to calculate anything as it stands. More on that shortly. The good news is that all of the quantities in (1) can be read off from the data sheet of the respective disk vendor^†. Note that the disk capacity, e.g., GB (the usual capacity planning metric) does not appear in (1).

The outstanding question is: where do those funny non-integral exponents come from?