It's Saturday night. I have a week of vacation ahead that I am going to spend at home, working on things I usually do not have time for. I already did something useful (created a couple of test cases for MariaDB bugs here and there, among other things), so why not to get some fun and continue my previous review of recent interesting MySQL bug report...

So, here is the list of 15 more MySQL community bug reports that I've subscribed to back in May and June 2019:

• Bug #95491 - "The unused wake up in simulator AIO of function reserve_slot". I am impressed by …

After a 3 months long break I'd like to continue reviewing MySQL bug reports that I am subscribed to. This issue is devoted to bug reports I've considered interesting to follow in May, 2019:

• Bug #95215 - "Memory lifetime of variables between check and update incorrectly managed". As demonstrated by Manuel Ung, there is a problem with all InnoDB MYSQL_SYSVAR_STR variables that can be dynamically updated. Valgrind allows to highlight it.
• Bug #95218 - "Virtual generated column altered …

We were pleased to sponsor the Percona Live Conference in Austin this year: many thanks to the Percona Team for organising a smooth conference yet again!

This is the recap of our week in Texas!

At The Conference

This year’s conference was the first one not taking place in Santa Clara, CA, but rather in Austin, TX. This turned out to be a nice choice by Percona, as it meant that open source database users who may not have travelled to California in the past, were attracted to the new location; and Austin being the new hot spot for (tech) companies at the moment, a lot of “locals” seemed to have made the choice to attend the conference. It was great to meet many new faces as a result.

As Diamond Sponsors of the conference we were of course present with a booth in the exhibition hall, as well as with three talks.

And while the hotel looked slightly dystopian at night, it was in fact a nice and …

(In the previous post, Part 6, we covered Replication.)

In this final blog post, we conclude our series of exploring MyRocks by taking a look at use case considerations. After all, having knowledge of how an engine works is really only applicable if you feel like you’re in a good position to use it.

Advantages of MyRocks

Let’s start by talking about some of the advantages of MyRocks.

Compression

MyRocks will typically do a good job of reducing the physical footprint of your data. As I mentioned in my previous post in this series about compression, you have the ability to configure compression down to the individual compaction layers for each column family. You also get the advantage of the fact that data isn’t updated once it’s written to disk. Compaction, which was …

Discover Tungsten Replicator (AMI) – the replication engine for MySQL, MariaDB & Percona Server, including Amazon RDS MySQL and Amazon Aurora We’re excited to announce the availability on the Amazon Marketplace of the new Tungsten Replicator (AMI). Tungsten Replicator (AMI) is a replication engine that provides high-performance and improved replication functionality over the native MySQL replication solution and provides an ability to apply real-time MySQL data feed into a range of analytics and big data databases. Tungsten Replicator (AMI) builds on the well-established, commercial stand-alone product Tungsten Replicator and offers the exact same functionality, but with the convenience that comes with an ad-hoc online service: cost-effective and rapid, automated deployment. Target Databases Available as of Today

…

Today we’re happy to announce that we’ll be partnering with Datavail to provide solutions for continuous & highly available MySQL, Percona Server & MariaDB database operations based on Tungsten Clustering & Datavail Database Services.

Datavail is a renowned, tech-enabled data management, applications, business intelligence, and software solutions provider with a team of 700+ DBAs that look after customers’ database environments.

What are we aiming for?

Together we’re looking to continue to drive momentum in supporting rapid MySQL & MariaDB based application deployments as well as highly available and scalable database implementations for existing and future customers.

This new …

(In the previous post, Part 5, we covered Data Reads.)

In this blog post, we continue our series of exploring MyRocks mechanics by looking at the configurable server variables and column family options. In our last post, I explained at a high level how reads occur in MyRocks, concluding the arc of covering how data moves into and out of MyRocks. In this post, we’re going to explore replication with MyRocks, more specifically read-free replication.

Some of you may already be familiar with the concepts of read-free replication as it was a key feature of the TokuDB engine, which leveraged fractal tree indexing. TokuDB was similar to MyRocks in the sense that it had a pseudo log-based storage …

As promised, I am trying to write one blog post in this series per week. So, even though writing about InnoDB row formats took a lot of time and efforts this weekend, I still plan to summarize my findings, questions, discussions, bugs and links I've collected over this week.

I've shared two links this week on Facebook that got a lot of comments (unlike links to my typical blog posts). The first one was to Marko Mäkelä's blog post at MariaDB.com, " …

(In the previous post, Part 4, we covered Compression and Bloom Filters)

In this blog post, we continue on our series of exploring MyRocks mechanics by looking at the configurable server variables and column family options. In our last post, I explained at a high level how compression and bloom filtering are applied to data files as they are initially flushed from immutable memtables and are subsequently passed through the compaction process. With that being covered, we should now have a clear understanding as to how data writing works in MyRocks and can start reviewing how data read requests are handled.

The Read Process

Let’s start off by talking about how read processes are handled at the file level. When a read request comes in, the first thing it needs to do is pull the …

(In the previous post, Part 3, we covered Compaction.)

In this blog post, we continue on our series of exploring MyRocks mechanics by looking at the configurable server variables and column family options. In our last post, I explained at a high level how data moves from its initial disk-written files into the full data set structure of MyRocks using a process called compaction. In this post, we’re going to look a little closer at two important features that are leveraged as data cascades down through this compaction process: bloom filters and compression.

Bloom filters

Before we approach how bloom filters are used in MyRocks, we need to know what a bloom filter is. The short definition is that a bloom filter is a space-efficient data structure used to tell you if an …