I remember wanting to create MySQL Cluster sandboxes several years ago. By then, however, MySQL-Sandbox technology was not flexible enough to allow an easy inclusion, and the cluster software itself was not as easy to install as it is today. Thus, I kept postponing the implementation, until I started working with dbdeployer.

I included the skeleton of support for MySQL Cluster since the beginning (by keeping a range of ports dedicated for this technology, but I didn’t do anything until June 2018, when I made public my intentions to add support for NDB in dbdeployer with issue #20 (Add support for MySQL Cluster)). The issue had just a bare idea, but I needed help from someone, as my expertise with …

MySQL NDB Cluster uses row level locks instead of a single shared commit lock in order to prevent inconsistency in simultaneous distributed transactions. This gives NDB a great advantage over all other MySQL clustering solutions and is one reason behind cluster’s unmatched ability to scale both reads and writes. 
NDB is a transactional data store. The lowest and only isolation level available in NDB is Read Committed. There are no dirty reads in NDB and only committed rows can be read by other transactions. 
All write transactions in NDB will result in exclusive row locks of all individual rows changed during the transaction. Any other transaction is allowed to read any committed row independent of their lock status. Reads are lock-free reads.
The great advantage is that committed reads in NDB never block during writes to the same data and always the latest committed changes are read. A select doesn't block concurrent …

Last time I mentioned four great MySQL books for 2018.  I was tactfully reminded of two books I overlooked. First is Dr. Charles Bell's Introducing InnoDB Cluster which I have not read (but it is on order).

And last, but not least, is Mikael Ronstrum's MySQL Cluster 7.5 Inside and Out.  This is another book on NDB cluster and is a 'msut have' for those running NDB clusters.

Someone once told me you can tell how healthy a software project is by the number of new books each year.  For the past few years the MySQL community has been blessed with one or two books each year. Part of that was the major shift with MySQL 8 changes but part of it was that the vast majority of the changes were fairly minor and did not need detailed explanations. But this year we have been blessed with four new books.  Four very good books on new facets of MySQL.

Introducing the MySQL 8 Document Store is the latest book from Dr. Charles Bell on MySQL.  If you have read any other of Dr. Chuck's book you know they are well written with lots of examples.  This is more than a simple introduction with many intermediate and advanced concepts covered in detail.

In the old days, when we wanted to strengthen our skills the only option was to buy a good book. Nowadays one can find a lot of resources on the Internet, however quality is often poor. Fortunately there are still some great people who are brave enough to write new books that will help a new generation of women and men to build modern applications with MySQL the world's most popular open source database. Let me introduce you 3 MySQL books : Introducing the MySQL 8 Document Store / MySQL and JSON: A Practical Programming Guide / Pro MySQL NDB Cluster

In this blog, I will provide answers to the Q & A for the Troubleshooting MySQL Concurrency Issues with Load Testing Tools webinar.

First, I want to thank everybody for attending my May 23, 2018, webinar on troubleshooting tools for MySQL. The recording and slides for the webinar are available here. Below is the list of your questions that I was unable to answer fully during the webinar.

Q: What do you recommend for benchmarking NDB cluster? Which should be used and how?

A: The issue with benchmarking NDB cluster is not the tool choice, …

In this series of blogs I will do my best to demonstrate how to set up and run Cluster in Cloud environment by hand and by utilizing MCC. For detailed configuration, I will use MCC (Auto-installer). Some of the information regarding this setup is provided in post by Mikael. Information regarding Auto-installer is available in our documentation, HTML help files in share/MCC distribution directory and in my blog post.

Cloud setupIt might come as surprise but for initial testing any instance should do. I started with 1CPU/1GB RAM ones. The target topology was:

• Host #1: Management node and Cluster client tools.
• Host #2: Multi-threaded DATA node. …

After dealing with Windows performance, I switched to MySQL Cluster Configurator (MCC for short) project. This was quite a change for me having to deal with Python back-end and JavaScript front-end, languages I was not so familiar with.

For the history of the project, please refer to Andrew's blog post for I will concentrate on changes made in new version.

There are many exciting new features in MySQL Cluster 7.6.4DMR including new MCC. To download MySQL Cluster 7.6.4DMR, please go to Development Releases tab. To see what's new in 7.6.4DMR, please follow this link.

MySQL Cluster Configurator in shortWith a single …

This blog gives some background to the decisions made when designing the
storage engine NDB Cluster used in MySQL Cluster around how to support
real-time requirements (or as I sometime refer to it, predictable response
time requirements).

Requirement analysisWhen analysing the requirements for NDB Cluster based on its usage in telecom
databases two things were important. The first requirement is that we need to
be able to respond to queries within a few milliseconds (today even down to
tens of microseconds). The second requirement is that we need to do this while
at the same time supporting a mix of simple traffic queries combined with a
number of more complex queries running at the same time.

The first requirement was the main requirement that led to NDB Cluster using a
main memory storage model with durability on disk using a REDO log and
various …

The swedish research institute, SICS, have worked hard for a few years on
developing a scalable and a highly available Hadoop implementation using
MySQL Cluster to store the metadata. In particular they have focused on the
Hadoop file system (HDFS) and the YARN. Using features of MySQL
Cluster 7.5 they were able to achieve linear scaling in number of name
nodes as well as in number of NDB data nodes to the number of nodes
available for the experiment (72 machines). Read the press release from
SICS here

The existing metadata layer of HDFS is based on a single Java server
that acts as name node in HDFS. There are implementations to ensure
that this metadata layer have HA by using a backup name node and to
use ZooKeeper for heartbeats and a number of …