August 1, 2014

MySQL Indexing Best Practices: Webinar Questions Followup

I had a lot of questions on my MySQL Indexing: Best Practices Webinar (both recording and slides are available now) We had lots of questions. I did not have time to answer some and others are better answered in writing anyway. Q: One developer on our team wants to replace longish (25-30) indexed varchars with […]

Distributed Set Processing with Shard-Query

Can Shard-Query scale to 20 nodes? Peter asked this question in comments to to my previous Shard-Query benchmark. Actually he asked if it could scale to 50, but testing 20 was all I could due to to EC2 and time limits. I think the results at 20 nodes are very useful to understand the performance: […]

The two even more fundamental performance metrics

In a recent blog post, I wrote about four fundamental metrics for system performance analysis. These are throughput, residence time, “weighted time” (the sum of all residence times in the observation period — the terminology is mine for lack of a better name), and concurrency. I derived all of these metrics from two “even more […]

The four fundamental performance metrics

There are many ways to slice and aggregate metrics of activity on a system such as MySQL. In the best case, we want to know everything about the system’s activity: we want to know how many things happened, how big they were, and how long they took. We want to know precisely when they happened. […]

Optimizing slow web pages with mk-query-digest

I don’t use many tools in my consulting practice but for the ones I do, I try to know them as best as I can. I’ve been using mk-query-digest for almost as long as it exists but it continues to surprise me in ways I couldn’t imagine it would. This time I’d like to share […]

Percona’s Sessions at the O’Reilly MySQL Conference and Expo

I just realized that we haven’t blogged a list of our sessions at the O’Reilly MySQL Conference and Expo (#mysqlconf) yet. Here is a hopefully complete list.

MySQL caching methods and tips

“The least expensive query is the query you never run.” Data access is expensive for your application. It often requires CPU, network and disk access, all of which can take a lot of time. Using less computing resources, particularly in the cloud, results in decreased overall operational costs, so caches provide real value by avoiding […]

Flexviews – part 3 – improving query performance using materialized views

Combating “data drift” In my first post in this series, I described materialized views (MVs). An MV is essentially a cached result set at one point in time. The contents of the MV will become incorrect (out of sync) when the underlying data changes. This loss of synchronization is sometimes called drift. This is conceptually […]

Maatkit’s mk-query-digest filters

Have you ever seen BIG weird numbers in mk-query-digest report that just seem wrong? I have! Here’s one report I got today:

Using Flexviews – part two, change data capture

In my previous post I introduced materialized view concepts. This post begins with an introduction to change data capture technology and describes some of the ways in which it can be leveraged for your benefit. This is followed by a description of FlexCDC, the change data capture tool included with Flexviews. It continues with an […]