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
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:
May
31
2012
This is the third blog post in the series of blog posts leading up to the talk comparing the optimizer enhancements in MySQL 5.6 and MariaDB 5.5. This blog post is targeted at the join related optimizations introduced in the optimizer. These optimizations are available in both MySQL 5.6 and MariaDB 5.5, and MariaDB 5.5
The post Join Optimizations in MySQL 5.6 and MariaDB 5.5 appeared first on ovais.tariq.
Mar
21
2012
This is the second blog post in the series of blog posts leading up to the talk comparing the optimizer enhancements in MySQL 5.6 and MariaDB 5.5. This blog post is aimed at the optimizer enhancement Multi Range Read (MRR). Its available in both MySQL 5.6 and MariaDB 5.5
Now let’s take a look at what this optimization actually is and what benefits it brings.
Multi Range Read
With traditional secondary index lookups, if the columns that are being fetched do not belong to the secondary index definition (and hence covering index optimization is not used), then primary key lookups have to be performed for each secondary key entry fetched. This means that secondary key lookups for column values that do not belong to the secondary index definition can result in a lot of Random I/O. The …
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