October 21, 2014

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 […]

Flexviews – part 3 – improving query performance using materialized views

Combating “data drift” In my first post in this series, I described materialized views (MVs). An MV is essentially a cached result set at one point in time. The contents of the MV will become incorrect (out of sync) when the underlying data changes. This loss of synchronization is sometimes called drift. This is conceptually […]

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 […]

Slow Query Log analyzes tools

(There is an updated version of this post here). MySQL has simple but quite handy feature – slow query log, which allows you to log all queries which took over define number of seconds to execute. There is also an option to enable logging queries which do not use indexes even if they take less […]

Innodb transaction history often hides dangerous ‘debt’

In many write-intensive workloads Innodb/XtraDB storage engines you may see hidden and dangerous “debt” being accumulated – unpurged transaction “history” which if not kept in check over time will cause serve performance regression or will take all free space and cause an outage. Let’s talk about where it comes from and what can you do […]

Recover orphaned InnoDB partition tablespaces in MySQL

A few months back, Michael wrote about reconnecting orphaned *.ibd files using MySQL 5.6. I will show you the same procedure, this time for partitioned tables. An InnoDB partition is also a self-contained tablespace in itself so you can use the same method described in the previous post. To begin with, I have an example […]

MySQL compression: Compressed and Uncompressed data size

MySQL has information_schema.tables that contain information such as “data_length” or “avg_row_length.” Documentation on this table however is quite poor, making an assumption that those fields are self explanatory – they are not when it comes to tables that employ compression. And this is where inconsistency is born. Lets take a look at the same table […]