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MySQL: Followup on UNION for query optimization, Query profiling

Few days ago I wrote an article about using UNION to implement loose index scan. First I should mention double IN also works same way so you do not have to use the union. So changing query to:

So as you see there are really different types of ranges in MySQL. IN range allows […]

Using the new spatial functions in MySQL 5.6 for geo-enabled applications

Geo-enabled (or location enabled) applications are very common nowadays and many of them use MySQL. The common tasks for such applications are: Find all points of interests (i.e. coffee shops) around (i.e. a 10 mile radius) the given location (latitude and longitude). For example we want to show this to a user of the mobile […]

How to convert MySQL’s SHOW PROFILES into a real profile

SHOW PROFILES shows how much time MySQL spends in various phases of query execution, but it isn’t a full-featured profile. By that, I mean that it doesn’t show similar phases aggregated together, doesn’t sort them by worst-first, and doesn’t show the relative amount of time consumed. I’ll profile the “nicer_but_slower_film_list” included with the Sakila sample […]

The case for getting rid of duplicate “sets”

The most useful feature of the relational database is that it allows us to easily process data in sets, which can be much faster than processing it serially. When the relational database was first implemented, write-ahead-logging and other technologies did not exist. This made it difficult to implement the database in a way that matched […]

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: […]

Shard-Query turbo charges Infobright community edition (ICE)

Shard-Query is an open source tool kit which helps improve the performance of queries against a MySQL database by distributing the work over multiple machines and/or multiple cores. This is similar to the divide and conquer approach that Hive takes in combination with Hadoop. Shard-Query applies a clever approach to parallelism which allows it to […]

3 ways MySQL uses indexes

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.