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Profiling with my Boy

We have an article online called "Can you explain Method R so even my boss could understand it?" Today I'm going to raise the stakes, because yesterday I think I explained Method R so that an eleven year-old could understand it.

Yesterday I took my 11 year-old son Alex to lunch. I talked him into eating at one of my favorite restaurants, called Mercado Juarez, over in Irving, so it was a half hour in the car together, just getting over there. It was a big day for the two of us because we were very excited about the new June 17 iPhone OS 3.0 release. I told him about some of the things I've learned about it on the Internet over the past couple of weeks. One subject in particular that we were both interested in was performance. He likes not having to wait for click results just as much as I do.

According to Apple, the new iPhone OS 3.0 software has some important code paths in it that are 3× faster. Then, upgrading to the new iPhone 3G S hardware is supposed to yield yet another 3× performance improvement for some code paths. It's what Philip Schiller talks about at 1:42:00 in the WWDC 2009 keynote video. Very exciting.

Alex of course, like many of us, wants to interpret "3× faster" as "everything I do is going to be 3× faster." As in everything that took 10 seconds yesterday will take 3 seconds tomorrow. It's a nice dream. But it's not what seeing a benchmark run 3× faster means. So we talked about it.

Latency Hiding For Fun and Profit

Yep, another post with the word ‘latency’ written all over it.

I’ve talked a lot about latency, and how it is more often than not completely immutable. So, if the latency cannot be improved upon because of some pesky law of physics, what can be done to reduce that wasted time? Just three things, actually:

  1. Don’t do it.
  2. Do it less often.
  3. Be productive with the otherwise wasted time.

The first option is constantly overlooked – do you really need to be doing this task that makes you wait around? The second option is the classic ‘do things in bigger lumps between the latency’ – making less roundtrips being the classic example. This post is about the third option, which is technically referred to as latency hiding.

Everybody knows what latency hiding is, but most don’t realise it. Here’s a classic example:

I need some salad to go with the chicken I am about to roast. Do I:

(a) go to the supermarket immediately and buy the salad, then worry about cooking the chicken?


(b) get the chicken in the oven right away, then go to the supermarket?

Unless the time required to buy the salad is much longer than the chicken’s cook-time, the answer is always going to be (b), right? That’s latency hiding, also known as Asynchronous Processing. Let’s look at the numbers:

Variable definitions:

Supermarket Trip=1800s

Chicken Cook-Time=4800s


Option (a)=1800s+4800s=6600s (oh man, nearly two hours until dinner!)

Option (b)=4800s (with 1800s supermarket time hidden within it)

Here’s another example: You have a big code compile to do, and an empty stomach to fill. In which order do you execute those tasks? Hit ‘make’, then grab a sandwich, right?

Forget I/O Bound, You’re Latency Bound, Bub

Since it’s been nearly ten years since I wrote my book, Scaling Oracle8i, I thought it was about time that I started writing again. I thought I would start with the new-fangled blogging thing, and see where it takes me. Here goes.

As some will know, I run a small consulting company called Scale Abilities, based out of the UK. We get involved in all sorts of fun projects and problems (or are they the same thing?), but one area that I seem to find myself focusing on a lot is storage. Specifically, the performance and architecture of storage in Oracle database environments. In fact I’m doing this so much that, whenever I am writing presentations for conferences these days, it always seems to be the dominant subject at the front of my mind.

One particular common thread has been the effect of latency. This isn’t just a storage issue, of course, as I endeavoured to point out in my Hotsos Symposium 2008 presentation “Latency and Skew”. Latency, as the subtitle of that particular talk said, is a silent killer. Silent, in that it often goes undetected, and the effects of it can kill performance (and still remain undetected). I’m not going to go into all the analogies about latency here, but let’s try and put a simple definition out for it:

Latency is the time taken between a request and a response.

If that’s such a simple definition, why is it so difficult to spot? Surely if a log period of time passes between a request and a response, the latency will be simple to nail? No.

Lucky to find it…

Earlier this month I was able to bought the book “Sun Performance and Tuning: Java and the Internet (2nd Edition)” for only 190pesos at some bookstore </p />

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Fundamentals of Software Performance Quick Reference Card

I just posted "Fundamentals of Software Performance Quick Reference Card" at the Method R company website:

This two-page quick reference card written by Cary Millsap sums up computer software performance the Method R way. The first page lists definitions of the terms you need to know: efficiency, knee, load, response time, and so on. The second page lists ten principles that are vital to your ability to think clearly about software performance. This document contains meaningful insight in a format that's compact enough to hang on your wall.

It's free, and there's no sign-up required. I hope you will enjoy it.

Diagnosing and Resolving “gc block lost”

Last week, one of our clients had a sudden slow down on all of their applications which is running on two node RAC environment

Below is the summary of the setup:
– Server and Storage: SunFire X4200 with LUNs on EMC CX300
– OS: RHEL 4.3 ES
– Oracle (database and clusterware)
– Database Files, Flash Recovery Area, OCR, and Voting disk are located on OCFS2 filesystems
– Application: Forms and Reports (6i and also lower)

As per the DBA, the workload on the database was normal and there were no changes on the RAC nodes and on the applications. Hmm, I can’t really tell because I haven’t really looked into their workload so I don’t have past data to compare.

The Most Common Performance Problem I See

At the Percona Performance Conference in Santa Clara this week, the first question an audience member asked our panel was, "What is the most common performance problem you see in the field?"

I figured, being an Oracle guy at a MySQL conference, this might be my only chance to answer something, so I went for the mic. Here is my answer.

The most common performance problem I see is people who think there's a most-common performance problem that they should be looking for, instead of measuring to find out what their actual performance problem actually is.

It's a meta answer, but it's a meta problem. The biggest performance problems I see, and the ones I see most often, are not problems with machines or software. They're problems with people who don't have a reliable process of identifying the right thing to work on in the first place.

That's why the definition of Method R doesn't mention Oracle, or databases, or even computers. It's why Optimizing Oracle Performance spends the first 69 pages talking about red rocks and informed consent and Eli Goldratt instead of Oracle, or databases, or even computers.

Advanced Oracle Troubleshooting by Tanel Poder in Singapore

When I first saw that Tanel will conduct his seminar in Singapore, I told myself that I would even spend my own money just to be on that training! I’ve already read performance books like Optimizing Oracle Performance, Oracle 8i Internal Services, Forecasting Oracle Performance… And after that I still want more, and I still have questions that need to be answered. Well, if you’re on a tight budget you just opt to download some more docs/books to do multiple reads coupled with research/test cases and also reading through others blog…
But thanks to my boss for the funding, I was there!</p />

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What would you do with 8 disks?

Yesterday, David Best posted this question at Oracle-L:

If you had 8 disks in a server what would you do? From watching this list I can see alot of people using RAID 5 but i'm wary of the performance implicatons. (

I was thinking maybe RAID 5 (3 disks) for the OS, software and
backups. RAID 10 (4 disks + 1 hot spare) for the database files.

Any thoughts?

I do have some thoughts about it.

There are four dimensions in which I have to make considerations as I answer this question:

  1. Volume
  2. Flow
  3. Availability
  4. Change

Just about everybody understands at least a little bit about #1: the reason you bought 8 disks instead of 4 or 16 has something to do with how many bytes of data you're going to store. Most people are clever enough to figure out that if you need to store N bytes of data, then you need to buy N + M bytes of capacity, for some M > 0 (grin).

OS Thread Startup

Recently I encountered a performance problem scenario where a simple sqlplus “/ as sysdba” took about 2minutes to finish, this is critical to the client’s business because they have a local C program that loads Call Detail Reports on the database making use of local authentication for most of its operations and Sql*Loader to load the data, so this “2minutes of waiting” when accumulated greatly consumes significant time on their operations and greatly impacts the business.

When I arrived on the client I first checked the alert logs of both ASM (they have a separate home for ASM) and RDBMS, there were no errors…

Then I checked on the server to see if there were any CPU, IO, memory, swap, and network bottlenecks going on

The CPU run queue was zero and most of the time 90% idle

The disks were also most of the time idle

The memory utilization was low with 430MB free