May 21, 2013

Webinar: Building a highly scaleable distributed row, document or column store with MySQL and Shard-Query

On Friday, February 15, 2013 10:00am Pacific Standard Time, I will be delivering a webinar entitled “Building a highly scaleable distributed row, document or column store with MySQL and Shard-Query” The first part of this webinar will focus on why distributed databases are needed, and on the techniques employed by Shard-Query to implement a distributed [...]

Is your MySQL Application having Busy IO by Oracle Measures ?

Preparing Choosing Storage Systems for MySQL talk for Percona Live in Washington,DC I ran into great paper called Sane SAN 2010 by James Morle from Scale Abilities – and Oracle consulting company. It is worth to read for variety of reason yet for this post I wanted to mention what James calls “Busy” Oracle database [...]

An update on Percona Live MySQL Conference & Expo 2012

We announced a while back that we were going to continue the traditional MySQL conference in Santa Clara, because O’Reilly wasn’t doing it anymore. But we haven’t given an update in a while. Here’s the current status: We created a conference committee. We created a conference website that allows people to create an account and [...]

Aligning IO on a hard disk RAID – the Benchmarks

In the first part of this article I have showed how I align IO, now I want to share results of the benchmark that I have been running to see how much benefit can we get from a proper IO alignment on a 4-disk RAID1+0 with 64k stripe element. I haven’t been running any benchmarks [...]

Checking the subset sum set problem with set processing

Hi, Here is an easy way to run the subset sum check from SQL, which you can then distribute with Shard-Query:

Notice there is no 16 in the list. We did not pass the check. There are enough 15s though. The distinct value count for each item in the output set, must at least [...]

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 performance analysis with ICE 3.5.2pl1 at 20 nodes.

Demonstrating distributed set processing performance Shard-Query + ICE scales very well up to at least 20 nodes This post is a detailed performance analysis of what I’ve coined “distributed set processing”. Please also read this post’s “sister post” which describes the distributed set processing technique. Also, remember that Percona can help you get up and [...]

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 EC2 images available

Infobright and InnoDB AMI images are now available There are now demonstration AMI images for Shard-Query. Each image comes pre-loaded with the data used in the previous Shard-Query blog post. The data in the each image is split into 20 “shards”. This blog post will refer to an EC2 instances as a node from here [...]

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 [...]