In a previous post, A Horizontal Scalability Mindset for MySQL, I discussed the concerns around growing individual MySQL instances too large and some basic strategies:

• Optimizing/minimizing size with proper data types
• Removing unused/duplicate indexes
• Keeping your Primary Keys small
• Pruning data

Finally, if those methods have been exhausted, I touched on horizontal sharding as the approach to keep individual instances at a reasonable size. When discussing my thoughts across our internal teams, there was lots of feedback that we needed to dive into the sharding topic in more detail. This post aims to give more theory and considerations around sharding along with a lightweight ProxySQL sample implementation.

What is Sharding?

Sharding is a word that is frequently used but …

On behalf of the Vitess maintainers, I am pleased to announce the general availability of Vitess 11. Major Themes # In this release, Vitess Maintainers have made significant progress in several areas, including Benchmarking, VTAdmin, Schema Tracking, Online DDL, and Performance improvements. While Schema Tracking is experimental, we’re very excited to have Gen4 planner evolving as well. Please take a moment to review the Release Notes. Please read them carefully and report any issues via GitHub.

On behalf of the Vitess maintainers, I am pleased to announce the general availability of Vitess 10. Major Themes # In this release, Vitess Maintainers have continued to focus on compatibility. It is still the most critical component of Vitess being part of the MySQL ecosystem. We have also started working on benchmarking and performance optimizations. These improvements have given us a clear vision of which areas of Vitess can be improved in terms of performance.

On behalf of the Vitess maintainers team, I am pleased to announce the general availability of Vitess 9. Major Themes # In this release, we have focused on making Vitess more stable after the successful release of Version 8. There have been no major issues reported. So there were no patches released for Version 8. This has allowed us to push further on compatibility and adoption of common frameworks as priorities.

Django is a popular framework for Python application developers. It includes packages which make tasks like authorization and content administration easier. Django supports a number of databases including MySQL which makes it possible to run a Django application over Vitess without having to change the application code. Let’s take a look at how to combine the strengths of these two open source frameworks. We built this example using Vitess operator. You can see the details of the implementation in the blog post Vitess Operator for Kubernetes.

Introduction # In this blog, I would like to explore Vitess Operator for Kubernetes. This post demonstrates the sample implementation of Vitess in Kubernetes topology. I also explore common DBA tasks by demonstrating how they are handled in the Vitess ecosystem. Vitess, out of the box, comes with a lot of tools and utilities that one has to either incorporate or develop to manage MySQL topology. Let’s take a look at the capabilities of Vitess in these areas and demonstrate how they are performed under the operator realm.

Welcome to another post in the series of Percona Live featured tutorial speakers blogs! In these blogs, we’ll highlight some of the tutorial speakers that will be at this year’s Percona Live conference. We’ll also discuss how these tutorials can help you improve your database environment. Make sure to read to the end to get a special Percona Live 2017 registration bonus!

In this Percona Live featured tutorial, we’ll meet Derek Downey (OSDB Practice Advocate, Pythian), David Turner (Storage SRE, Uber) and René Cannaò (MySQL SRE, Dropbox / ProxySQL). Their session is ProxySQL Tutorial. There is a stigma attached to database proxies when it comes to MySQL. This tutorial hopes to blow away that stigma by showing you what can be done with a proxy designed from the …

In this blog post, I’ll discuss MySQL sharding models, and how they apply to SaaS application environments.

MySQL is one of the most popular database technologies used to build many modern SaaS applications, ranging from simple productivity tools to business-critical applications for the financial and healthcare industries.

Pretty much any large scale SaaS application powered by MySQL uses sharding to scale. In this blog post, we will discuss sharding choices as they apply to these kinds of applications.

In MySQL, unlike in some more modern technologies such as MongoDB, there is no standard sharding implementation that the vast majority of applications …

MySQL Cluster does an automatic sharding/partitioning to the tables across data nodes, enabling databases to scale horizontally to serve read and write-intensive workloads, but what is the default sharding key used in partitioning the data?
According to the recent update (Oct, 2016) of the MySQL Cluster white paper, primary key is the default sharding key:

By default, sharding is based on hashing of the primary key, which generally leads to a more even distribution of data and queries across the cluster than alternative approaches such as range partitioning.

However, that is not the case in all MySQL Cluster versions so far!
In this post, I’ll do some test cases on MySQL Cluster (of 4 datanodes) to confirm the default sharding key.

Testing on MySQL Cluster 7.2.26 …

As stated in the MySQL Cluster documentation:

Partition.  This is a portion of the data stored by the cluster. There are as many cluster partitions as nodes participating in the cluster. Each node is responsible for keeping at least one copy of any partitions assigned to it (that is, at least one replica) available to the cluster.

According to my understanding for the previous paragraph, if we have a cluster of 6 datanodes we should have 6 partitions for each NDB table. I claim that this is not true for all cases – at least, after the introduction of ndbmtd (Multi-Threaded Daemon) in MySQL Cluster 7.2 .
In this post, I’ll do some …