April 18, 2014

Setting up XFS on Hardware RAID — the simple edition

There are about a gazillion FAQs and HOWTOs out there that talk about XFS configuration, RAID IO alignment, and mount point options.  I wanted to try to put some of that information together in a condensed and simplified format that will work for the majority of use cases.  This is not meant to cover every […]

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 […]

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 […]

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: […]

Sample datasets for benchmarking and testing

Sometimes you just need some data to test and stress things. But randomly generated data is awful — it doesn’t have realistic distributions, and it isn’t easy to understand whether your results are meaningful and correct. Real or quasi-real data is best. Whether you’re looking for a couple of megabytes or many terabytes, the following […]

Conflict Avoidance with auto_increment_increment and auto_increment_offset

A lot of people are running MySQL Master-Master replication pairs in Active-Passive mode for purpose of high availabilities using MMM or other solutions. Such solutions generally have one major problem – you have to be very carefully switching writes as if you do not do it atomically (such as some scripts continue to write to […]

High availability for MySQL on Amazon EC2 – Part 2 – Setting up the initial instances

This post is the second of a series that started here. The first step to build the HA solution is to create two working instances, configure them to be EBS based and create a security group for them. A third instance, the client, will be discussed in part 7. Since this will be a proof […]

Converting Character Sets

The web is going the way of utf8. Drizzle has chosen it as the default character set, most back-ends to websites use it to store text data, and those who are still using latin1 have begun to migrate their databases to utf8. Googling for “mysql convert charset to utf8″ results in a plethora of sites, […]

JOIN Performance & Charsets

We have written before about the importance of using numeric types as keys, but maybe you’ve inherited a schema that you can’t change or have chosen string types as keys for a specific reason. Either way, the character sets used on joined columns can have a significant impact on the performance of your queries. Take […]