Search Results for: large data insert performance

Data mart or data warehouse?

This is part two in my six part series on business intelligence, with a focus on OLAP analysis. Part 1 – Intro to OLAP Identifying the differences between a data warehouse and a data mart. (this post) Introduction to MDX and the kind of SQL which a ROLAP tool must generate to answer those queries. […]

How innodb_open_files affects performance

Recently I looked at table_cache sizing which showed larger table cache does not always provides the best performance. So I decided to look at yet another similar variable – innodb_open_files which defines how many files Innodb will keep open while working in innodb_file_per_table mode. Unlike MyISAM Innodb does not have to keep open file descriptor […]

High-Performance Click Analysis with MySQL

We have a lot of customers who do click analysis, site analytics, search engine marketing, online advertising, user behavior analysis, and many similar types of work.  The first thing these have in common is that they’re generally some kind of loggable event. The next characteristic of a lot of these systems (real or planned) is […]

Cache Performance Comparison

Jay Pipes continues cache experiements and has compared performance of MySQL Query Cache and File Cache. Jay uses Apache Benchmark to compare full full stack, cached or not which is realistic but could draw missleading picture as contribution of different components may be different depending on your unique applications. For example for application containing a […]

Tokutek now part of the Percona family

It is my pleasure to announce that Percona has acquired Tokutek and will take over development and support for TokuDB® and TokuMX™ as well as the revolutionary Fractal Tree® indexing technology that enables those products to deliver improved performance, reliability and compression for modern Big Data applications. At Percona we have been working with the […]

Yelp IT! A talk with 3 Yelp MySQL DBAs on Percona Live & more

Founded in 2004 to help people find great local businesses, Yelp has some 135 million monthly unique visitors. With those traffic volumes Yelp’s 300+ engineers are constantly working to keep things moving smoothly – and when you move that fast you learn many things. Fortunately for the global MySQL community, three Yelp DBAs will be […]