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Make It Fast: The Underrated Rewards of Performance Tuning

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Make It Fast: The Underrated Rewards of Performance Tuning

Get tips on performance tuning your applications, where to find the low-hanging fruit, as well as unexpected benefits to your team.

· Performance Zone ·
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Many will be familiar with "Make it work; make it right; make it fast," generally attributed to Kent Beck. The "fast" bit trails like something of an afterthought; unlike its siblings it feels kind of optional, in practice, anyway, if not in the perfect world in which such advice lives.

Let's face it: for those of us in the commercial world time to market is often crucial, and "Add feature 2" tends to beat "Improve feature 1" in prioritization decisions.

But right now I'm not looking to consider pragmatism vs purism, or gold-plating vs turd-polishing (!) — we all know the trade-offs that happen in real life: decisions are made; stuff gets done in way too much of a hurry; junior devs don't get the support they need; new and unproven tech stacks are inflicted — how hard can it be?

I'm writing today instead to celebrate the sheer unalloyed glory of a successful performance deep-dive and fix — to revel in the purity of such a task, and exult in the unqualified satisfaction that comes from cutting tens, hundreds or even thousands of milliseconds off an operation! What triumph! I've been doing quite a bit of this in recent client engagements and as well as having the stubbornness and tenacity to be pretty damn good at it I've found it rather an enjoyable way to "add business value."

So what's so good about it, exactly?

First, some caveats:

  • Caveat 1 — any boss type, pointy-haired or otherwise, wandering over at 11am and demanding a fix by 4pm isn't conducive to an enjoyable session; this kind of pressure takes all the fun out of what is clearly an artistic and creative process. Avoid such people.
  • Caveat 2 — try to fix problems in code which other people wrote. We're not looking to blame-storm, but if your work's all in Component X while all the issues are in Component Y, there's zero downside: you are not at risk of uncovering your own dirty little secrets. And if you don't really find anything, well, that's sort of OK, it wasn't your fault in the first place... (ahem).

So, groundwork done — you have unlimited time to find someone else's mistake. Happy days. Let's proceed.

Main reasons this kind of task can be deeply rewarding, then:

  • It's a great chance to make your team's product unambiguously — and measurably — better, most likely in an area of enough importance to justify its priority being higher than adding new features or fixing other known bugs in the first place.
  • There are no politics or negotiations to consider (if there is, your organization may be a bit broken) - but there is the tremendous credit to be gained by announcing the "wins" (be wary of announcing the non-wins!).
  • It's an easy sort of task to become deeply immersed in; hours can pass while you sit sifting logs, correlating timings and frequencies against code, trying to build a narrative of what's really happening; this sort of state is known as Flow and well worth reading about — jobs and tasks where you achieve this state tend to be ones you enjoy more.
  • It's a very pure challenge: you have one goal to work towards, and you can channel all your skills towards it - and build new ones too if you're lucky!
  • By definition, if you're investigating an area then it's not well understood (by you, anyway — yet) so you'll inevitably end up learning a lot more about that area - and that's never a bad thing.
  • You know when you're done, much like a sudoku or a crossword puzzle; getting an operation down from 1,500ms to 30ms may or may not be carved in stone as "the requirement" but once you're there you know you've nailed it.
  • Perhaps most significantly of all, it's like a detective story: often there's a single root cause for any given misbehaving area, and hours, days and even weeks of painstaking forensic analysis, experimentation and evidence-gathering reveals exactly 'whodunnit'! It's no exaggeration to say some of these "eureka" moments have been the most satisfying of my career!

Where Should We Look?

Experience suggests the following candidates, in severity order:

#1 — The Database

There we go; done. Look in your database and/or how your application or services are using it. That's where your problem is. You're welcome.

The Tools for the Job

There are sophisticated tools in the monitoring world, but honestly, the basics are all you need:

  • Access to complete log files and the ability to add new log entries.
  • The codebase and the ability to make diagnostics changes — a cheeky log.info("Got here 123!") can work wonders in the right place! (always remove it afterward, though; we're not savages...).
  • The ability to conduct runs and experiments — either locally with zero friction, or even by deploying — safely — to production to get extra log instrumentation into play.

With the above, you have all you need to conduct your experiments: add logging till you know exactly what is happening, write scripts to extract meaningful patterns if your volumes prohibit intuition alone from gleaning the key facts, and really just keep iterating until you know what's taking place.

Macro vs. Micro Issues

Sometimes your issue is a tiny but Very Bad SQL query running in a component. Sometimes it's a perfectly good SQL query but it's being run by 40 threads in 30 parallel application instances. Be mindful of this difference: look at the code but be aware of the wider architecture. (Like I said, it's still always the database...)

Low-Hanging Fruit — A Case Study

Don't make the mistake of assuming any issue is going to take weeks of micro-analysis: sometimes there are huge wins just waiting to be found. "Packs of watermelons hanging off the leaves" levels of low hanging fruits. Don't count on this of course but do yourself a favor and look out for them before you look for the harder gains.

Here's an example: 15 years or so ago, the firm I worked with was basically "gifted" a government client from another development shop. The original developers had built a form of contact management system for a small number of high-value contacts: it worked, it was correct, but sweet chocolate teapots, was it slow — it barely functioned at all.

One page — "view contacts" — showing names and email addresses, for example, would take 10 minutes to load. There were a couple of thousand contacts: it probably worked great for the 5 "test" entries, maybe the next 50 real contacts. But very quickly (ha) it then went wrong. And the original developers couldn't fix it. They tried, they couldn't find the problem, and, to their credit, they helped their client find someone else who could.

Long story short: yeah, it was the database. A dumb ORM interaction with the database to be precise. Each Contact had one or more Company objects, and those had Location objects, and the ORM was doing what dumb ORMs do unless you advise them otherwise and fetching the child objects one by one by ID. We quickly measured something like:

  • 1 query to find the 2000 Contact entries
  • 2000 queries to find the Company entries one by one
  • 2000 queries to find the Location entries one by one

The irony was that the page didn't even use the results from those other 4000 queries: the code loaded the entire object graph, ignored most of it, and spent many minutes doing so. We replaced it with a simple hand-crafted SQL query and a simple result handler and the "view contacts" page loaded pretty much instantaneously.

The moral of the story here isn't about ORMs (but, wow, therein lies a topic) or even Knowing One's Tools — it's about looking for the simple stuff first because sometimes even in the incredibly sophisticated world of software, optimisation isn't always about squeezing the last few ounces of horsepower from the red-lining engine, it's just about releasing the handbrake before putting your foot down!

Some Further Reading

It's maybe not super relevant, but the novel Zen and the Art of Motorcycle Maintenance has some interesting parallels to performance tuning and debugging in general: the focus one finds in trying to determine root causes, the systematic and methodical approach, the need to know one's tools and to develop a wider understanding of the overall system/engine in order to effect a correct repair.

It's an acknowledged classic and well worth a read for anyone with even a slightly philosophical bent; it's not an auto-repair manual, I should repeat, it's a novel...

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Topics:
performance ,performance tuning ,database ,optimization

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