Search Results for: mysql memory limit union

MySQL 5.5 and MySQL 5.6 default variable values differences

As the part of analyzing surprising MySQL 5.5 vs MySQL 5.6 performance results I’ve been looking at changes to default variable values. To do that I’ve loaded the values from MySQL 5.5.30 and MySQL 5.6.10 to the different tables and ran the query:

Lets go over to see what are the most important changes […]

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.

Possible optimization for sort_merge and UNION ORDER BY LIMIT

Every so often you need to perform sort results retrieved from MySQL when your WHERE clause goes beyound col=const values which would allow MySQL to still use second portion of the index for the order by. Ranges as well as IN lists make this optimization impossible, not even speaking about index merge optimization. Lets look […]

MySQL Query Cache

MySQL has a great feature called “Query Cache” which is quite helpful for MySQL Performance optimization tasks but there are number of things you need to know. First let me clarify what MySQL Query Cache is – I’ve seen number of people being confused, thinking MySQL Query Cache is the same as Oracle Query Cache […]

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 […]