Percona's MySQL & InnoDB performance and scalability blog
This is part 2 in a 3 part series. In part 1, we took a quick look at some initial configuration of InnoDB full-text search and discovered a little bit of quirky behavior; here, we are going to run some queries and compare the result sets. Our hope is that the one of two things [...]
One of the most common causes of a poor Sphinx search performance I find our customers face is misuse of search filters. In this article I will cover how Sphinx attributes (which are normally used for filtering) work, when they are a good idea to use and what to do when they are not, but [...]
Inspiration for this post is courtesy of a friend and former colleague of mine, Greg Youngblood, who pinged me last week with an interesting MySQL puzzle. He was running Percona Server 5.5.21 with a table structure that looks something like this:
1 2 3 4 5 6 7 8 9 | CREATE TABLE foo ( id INT UNSIGNED NOT NULL AUTO_INCREMENT PRIMARY KEY, uid INT UNSIGNED NOT NULL, update_time DATETIME NOT NULL, .... INDEX `uid` (uid, update_time), INDEX `bar` (some_other_columns) .... ) ENGINE=InnoDB; |
When he ran this query:
1 | SELECT MIN(update_time) FROM foo WHERE update_time IS NOT NULL AND update_time <> '0000-00-00 00:00:00'; |
The result came back as 2012-06-22 10:28:16. [...]
Overview Profiling, analyzing and then fixing queries is likely the most oft-repeated part of a job of a DBA and one that keeps evolving, as new features are added to the application new queries pop up that need to be analyzed and fixed. And there are not too many tools out there that can make [...]
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 [...]
A few weeks ago, we had a query optimization request from one of our customer. The query was very simple like:
1 | SELECT * FROM `table` WHERE (col1='A'||col1='B') ORDER BY id DESC LIMIT 20 OFFSET 0 |
This column in the table is looks like this:
1 | `col1` enum('A','B','C','CD','DE','F','G','HI') default NULL |
The table have 549252 rows and of course, there is an index on the col1. MySQL estimated the cardinality of that index as [...]
I often see people confuse different ways MySQL can use indexing, getting wrong ideas on what query performance they should expect. There are 3 main ways how MySQL can use the indexes for query execution, which are not mutually exclusive, in fact some queries will use indexes for all 3 purposes listed here.
I wanted to share a little rule of thumb I sometimes use to decide which columns should come first in an index. This is not specific to MySQL, it’s generally applicable to any database server with b-tree indexes. And there are a bunch of subtleties, but I will also ignore those for the sake of [...]
When doing performance analyzes you often would want to see 95 percentile, 99 percentile and similar values. The “average” is the evil of performance optimization and often as helpful as “average patient temperature in the hospital”. Lets set you have 10000 page views or queries and have average response time of 1 second. What does [...]
Quite typical query for reporting applications is to find top X values. If you analyze Web Site logs you would look at most popular web pages or search engine keywords which bring you most of the traffic. If you’re looking at ecommerce reporting you may be interested in best selling product or top sales people. [...]
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