September 14, 2014

Parallel Query for MySQL with Shard-Query

While Shard-Query can work over multiple nodes, this blog post focuses on using Shard-Query with a single node.  Shard-Query can add parallelism to queries which use partitioned tables.  Very large tables can often be partitioned fairly easily. Shard-Query can leverage partitioning to add paralellism, because each partition can be queried independently. Because MySQL 5.6 supports the […]

Q&A: Common (but deadly) MySQL Development Mistakes

On Wednesday I gave a presentation on “How to Avoid Common (but Deadly) MySQL Development Mistakes” for Percona MySQL Webinars. If you missed it, you can still register to view the recording and my slides. Thanks to everyone who attended, and especially to folks who asked the great questions. I answered as many as we had time […]

Increasing slow query performance with the parallel query execution

MySQL and Scaling-up (using more powerful hardware) was always a hot topic. Originally MySQL did not scale well with multiple CPUs; there were times when InnoDB performed poorer with more  CPU cores than with less CPU cores. MySQL 5.6 can scale significantly better; however there is still 1 big limitation: 1 SQL query will eventually use only […]

Shard-Query adds parallelism to queries

Preamble: On performance, workload and scalability: MySQL has always been focused on OLTP workloads. In fact, both Percona Server and MySQL 5.5.7rc have numerous performance improvements which benefit workloads that have high concurrency. Typical OLTP workloads feature numerous clients (perhaps hundreds or thousands) each reading and writing small chunks of data. The recent improvements to […]

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 […]

Why MySQL could be slow with large tables ?

If you’ve been reading enough database related forums, mailing lists or blogs you probably heard complains about MySQL being unable to handle more than 1.000.000 (or select any other number) rows by some of the users. On other hand it is well known with customers like Google, Yahoo, LiveJournal,Technocarati MySQL has installations with many billions […]

Using any general purpose computer as a special purpose SIMD computer

Often times, from a computing perspective, one must run a function on a large amount of input. Often times, the same function must be run on many pieces of input, and this is a very expensive process unless the work can be done in parallel. Shard-Query introduces set based processing, which on the surface appears […]

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: […]

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. […]

Sphinx: Going Beyond full text search

I’ve already wrote a few times about various projects using Sphinx with MySQL for scalable Full Text Search applications. For example on BoardReader we’re using this combination to build search against over 1 billion of forum posts totaling over 1.5TB of data handling hundreds of thousands of search queries per day. The count of forum […]