April 23, 2014

Designing one to many relations – MongoDB vs MySQL

We already discussed one to one relations in MongoDB, and the main conclusion was that you should design your collections according to the most frequent access pattern. With one to many relations, this is still valid, but other factors may come into play. Let’s look at a simple problem: we are a shop and we […]

Galera Flow Control in Percona XtraDB Cluster for MySQL

Last week at Percona Live, I delivered a six-hour tutorial about Percona XtraDB Cluster (PXC) for MySQL.  I actually had more material than I covered (by design), but one thing I regret we didn’t cover was Flow control.  So, I thought I’d write a post covering flow control because it is important to understand. What […]

A case for MariaDB’s Hash Joins

MariaDB 5.3/5.5 has introduced a new join type “Hash Joins” which is an implementation of a Classic Block-based Hash Join Algorithm. In this post we will see what the Hash Join is, how it works and for what types of queries would it be the right choice. I will show the results of executing benchmarks […]

How FLUSH TABLES WITH READ LOCK works with Innodb Tables

Many backup tools including Percona Xtrabackup, MyLVMBackup and others use FLUSH TABLES WITH READ LOCK to temporary make MySQL read only. In many cases the period for which server has to be made read only is very short, just few seconds, yet the impact of FLUSH TABLES WITH READ LOCK can be quite large because […]

Optimizing InnoDB for creating 30,000 tables (and nothing else)

Once upon a time, it would have been considered madness to even attempt to create 30,000 tables in InnoDB. That time is now a memory. We have customers with a lot more tables than a mere 30,000. There have historically been no tests for anything near this many tables in the MySQL test suite. So, […]

Is VoltDB really as scalable as they claim?

Before I begin, a disclaimer. VoltDB is not a customer, and did not pay Percona or me to investigate VoltDB’s scalability or publish this blog post. More disclaimers at the end. Short version: VoltDB is very scalable; it should scale to 120 partitions, 39 servers, and 1.6 million complex transactions per second at over 300 […]

Performance problem with Innodb and DROP TABLE

I’ve been working with an application which does a lot of CREATE and DROP table for Innodb tables and we’ve discovered DROP TABLE can take a lot of time and when it happens a lot of other threads stall in “Opening Tables” State. Also contrary to my initial suspect benchmarking create/drop table was CPU bound […]

MongoDB Approach to Availability

Another thing I find interesting about MongoDB is its approach to Durability, Data Consistency and Availability. It is very relaxed and will not work for some applications but for others it can be usable in current form. Let me explain some concepts and compare it to technologies in MySQL space. First I think MongoDB is […]

Adjusting Innodb for Memory resident workload

As larger and larger amount of memory become common (512GB is something you can fit into relatively commodity server this day) many customers select to build their application so all or most of their database (frequently Innodb) fits into memory. If all tables fit in Innodb buffer pool the performance for reads will be quite […]

Heikki Tuuri Innodb answers – Part I

Its almost a month since I promised Heikki Tuuri to answer Innodb Questions. Heikki is a busy man so I got answers to only some of the questions but as people still poking me about this I decided to publish the answers I have so far. Plus we may get some interesting follow up questions […]