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 [...]
Last time I wrote about a few tips that can make you more efficient when using the command line on Unix. Today I want to focus more on pager. The most common usage of pager is to set it to a Unix pager such as less. It can be very useful to view the result [...]
I presented a webinar this week to give an overview of Tools and Techniques for Index Design. Even if you missed the webinar, you can register for it, and you’ll be emailed a link to the recording. I’d like to invite folks who are interested in tools for query optimization to attend the new Percona [...]
I recently worked on a customer case where at seemingly random times, inserts would fail with Innodb error 139. This is a rather simple problem, but due to it’s nature, it may only affect you after you already have a system running in production for a while.
As Calpont announced availability of InfiniDB I surely couldn’t miss a chance to compare it with previously tested databases in the same environment. See my previous posts on this topic: Analyzing air traffic performance with InfoBright and MonetDB Air traffic queries in LucidDB I could not run all queries against InfiniDB and I met some [...]
A few weeks ago I was asked to isolate some functionalities from Mark Callaghan’s MySQL patch bundle. They were extensions adding per-user and per-table accounting to the database, accessible with a new set of commands such as SHOW TABLE_STATISTICS, SHOW INDEX_STATISTICS and SHOW USER_STATISTICS. The first two can interest anyone to periodically check what data [...]
Sometimes you have the task of storing multiple of boolean values (yes/now or something similar) in the table and if you get many columns and many rows you may want to store them as efficient way as possible. For MyISAM tables you could use BIT(1) fields which get combined together for efficient storage:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | CREATE TABLE `bbool` ( `b1` bit(1) NOT NULL, `b2` bit(1) NOT NULL, `b3` bit(1) NOT NULL, `b4` bit(1) NOT NULL, `b5` bit(1) NOT NULL, `b6` bit(1) NOT NULL, `b7` bit(1) NOT NULL, `b8` bit(1) NOT NULL, `b9` bit(1) NOT NULL, `b10` bit(1) NOT NULL ) ENGINE=MyISAM mysql> show table status like 'bbool' \G *************************** 1. row *************************** Name: bbool Engine: MyISAM Version: 10 Row_format: Fixed Rows: 10 Avg_row_length: 7 Data_length: 70 Max_data_length: 1970324836974591 Index_length: 1024 Data_free: 0 Auto_increment: NULL Create_time: 2008-04-24 00:41:01 Update_time: 2008-04-24 00:45:40 Check_time: NULL Collation: latin1_swedish_ci Checksum: NULL Create_options: Comment: 1 row in set (0.00 sec) |
Finding largest tables on MySQL instance is no brainier in MySQL 5.0+ thanks to Information Schema but I still wanted to post little query I use for the purpose so I can easily find it later, plus it is quite handy in a way it presents information:
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. [...]
Last few days I had a lot of a lot of questions at MySQL Performance Forum as well as from our customers regarding query optimization… which had one thing in common – It is not query which needed to be optimized. Way too frequently people design schema first and then think how the queries they [...]
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