Join 6100 others and follow Sean Hull on twitter @hullsean. Lots and lots of web applications need to page through information. From customer records, to the albums in your itunes collection. So as web developers and architects, it’s important that we do all this efficiently. Start by looking at how you’re fetching information from your [...]
Jun
19
2013
Jun
13
2013
Join 6100 others and follow Sean Hull on twitter @hullsean. There are two ways to speedup UNIONs in a MySQL database. First use UNION ALL if at all possible, and second try to push down your conditions. [mytweetlinks] 1. UNION ALL is much faster than UNION How does a UNION work? Imagine you have two [...]
Aug
18
2012
Calculating the standard deviation in MySQL is a no-brainer by using the build-in aggregate function STDDEV(). If you don't need the original data and only want to save aggregated values in your database, the whole matter is getting more complicated - but is worth from a space and performance point of view.
Aug
18
2012
Calculating the standard deviation in MySQL is a no-brainer by using the build-in aggregate function STDDEV(). If you don't need the original data and only want to save aggregated values in your database, the whole matter is getting more complicated - but is worth from a space and performance point of view.
Aug
14
2012
One of my colleague asked me : « Is an ALTER TABLE with many specifications is faster than 1 ALTER TABLE by specification ? »
The answers seems quite intuitive, anyway figures are better than a long speech...
Context :
MySQL Community Server 5.5.22
InnoDB table with 8 539 238 rows.
17 columns with INT, CHAR, VARCHAR, TEXT, DATETIME, … fields
Jul
16
2012
You often see databases with huge dynamic text fields, such as VARCHAR(255), TEXT, or as I recently was allowed to see the blanket use of LONGTEXT (max 4GiB) in order to be invulnerable from all contingencies. Things getting even worse when an index is used over such columns, because hey, there is an index. It makes things fast :-) Okay, jokes aside. Often you can save a lot of space and time, MySQL spends traversing the index when using a proper column type and index size.
Jul
16
2012
You often see databases with huge dynamic text fields, such as VARCHAR(255), TEXT, or as I recently was allowed to see the blanket use of LONGTEXT (max 4GiB) in order to be invulnerable from all contingencies. Things getting even worse when an index is used over such columns, because hey, there is an index. It makes things fast :-) Okay, jokes aside. Often you can save a lot of space and time, MySQL spends traversing the index when using a proper column type and index size.
Jul
12
2012
The first annual Latin America MySQL/NoSQL/Cloud Conference was held in Buenos Aires Argentina from June 26-28. Kudos to Santiago Lertora from Binlogic who had the vision for the conference in his country and made it happen. I look forward to the second annual event.
My first presentation was “Improving Performance with Better Indexes”. This presentation details the six steps to SQL performance analysis, Capture, Identify, Confirm, Analyze, Optimize and Verify. An explanation of MySQL EXPLAIN, and working examples to create indexes and better covering indexes in several examples are provided. A production example of a 13 table join is used to detail how covering indexes and partial column indexes can make a dramatic improvement in performance. …
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Jul
12
2012
Since I use MySQL for the statistical analysis on a project, I wanted to optimize the database queries and learned a lot about stuff like number theory, set theory and partial sums. I took my MySQL UDF, I've published two years ago, for this purpose and added new functions for a deeper statistical analysis. The project is around for a while, so it's time to share things with the public to start a discussion of how things could be further optimized. The source and a small documentation can be found on Github:
Jul
12
2012
Since I use MySQL for the statistical analysis on a project, I wanted to optimize the database queries and learned a lot about stuff like number theory, set theory and partial sums. I took my MySQL UDF, I've published two years ago, for this purpose and added new functions for a deeper statistical analysis. The project is around for a while, so it's time to share things with the public to start a discussion of how things could be further optimized. The source and a small documentation can be found on Github: