MySQL Group Replication is a plugin that helps to implement highly available fault-tolerant replication topologies. In this blog, I am going to explain the complete steps involved in the below two topics.

• How to convert the group replication member to an asynchronous replica
• How to convert the asynchronous replica to a group replication member

Why Am I Converting From GR Back to Old Async?

Recently I had a requirement from one of our customers running 5 node GR clusters. Once a month they are doing the bulk read job for generating the business reports. When they are doing the job, it affects the overall cluster performance because of the flow control issues. The node which is executing the read job is overloaded and delays the certification and writes apply process. The read job queries can’t be split across the cluster.  So, they don’t want that …

While I was working on my grFailOver POC, I have also done some additional parallel testing. One of them was to see how online DDL is executed inside a Group Replication cluster.

The online DDL feature provides support for instant and in-place table alterations and concurrent DML. Checking the Group Replication (GR) official documentation, I was trying to identify if any limitation exists, but the only thing I have found was this:

“Concurrent DDL versus DML Operations.  Concurrent data definition statements and data manipulation statements executing against the same object but on different servers is not supported when using multi-primary mode. During execution of Data Definition Language (DDL) statements on an object, executing concurrent Data Manipulation Language (DML) on the …

Where x is >= 22

The Problem

There are few things your data does not like. One is water and another is fire. Well, guess what:

If you think that everything will be fine after all, take a look:

Given my ISP had part of its management infrastructure on OVH, they had been impacted by the incident.

As you can see from the highlight, the ticket number in three years changes very little (2k cases) and the date jumps from 2018 to 2021. On top of that, I have to mention I had opened several tickets the month before that disappeared. 

So either my ISP was very lucky and had very few cases in three years and sent all my tickets to /dev/null… or they have lost THREE YEARS of data.   

Let us go straight to the chase; they have lost their …

This blog provides high availability (HA) guidelines using group replication architecture and deployment recommendations in MySQL, based on our best practices.

Every architecture and deployment depends on the customer requirements and application demands for high availability and the estimated level of usage. For example, using high read or high write applications, or both, with a need for 99.999% availability.

Here, we give architecture and deployment recommendations along with a technical overview for a solution that provides a high level of high availability and assumes the usage of high read/write applications (20k or more queries per second).

Layout

Components

This architecture is composed of two main layers:

• Connection and distribution layer
• RDBMS …

Chasing bugs can be a tedious task, and multi-threaded software doesn’t make it any easier. Threads will be scheduled at different times, instructions will not have deterministic results, and in order for one to reproduce a particular issue, it might require the exact same threads, doing the exact same work, at the exact same time. As you can imagine, this is not straightforward.

Let’s say your database is crashing or even having a transient stall.  By the time you get to it, the crash has happened and you are stuck restoring service quickly and doing after-the-fact forensics.  Wouldn’t it be nice to replay the work from right before or during the crash and see exactly what was happening?

Record and Replay is a technique where we record the execution of a program allowing it to be replayed over and over producing the same result. Engineers at …

So your MySQL server has crashed.  What do you do now?  When a server is down, in my opinion, there are two steps that are essential and both are extremely important and neither should be neglected:

1. Save diagnostic information for determining the root cause analysis (RCA).
2. Get the server back up and running.

Too many people rush to Step #2 and lose pertinent diagnostics from Step #1.  Likewise, too many people will spend too much time on Step #1 and delay getting to Step #2 and restoring service.  The goal is to collect diagnostics as quickly as possible for later review while getting service restored as fast as possible.

As a Technical Account Manager (TAM) and assisting on server restoration calls, I have seen both issues at play.  Technical resources have a tendency to get so bogged down in trying to understand the cause of the server outage that they …

(based on a conversation with a colleague, and a bit of Twitter)

A Conundrum

A developer colleague paged me with this:

mysql> select
UNIX_TIMESTAMP("2021-03-26 03:07:00" + INTERVAL 2 YEAR) -
UNIX_TIMESTAMP("2021-03-26 02:07:00" + INTERVAL 2 YEAR) as delta\G
delta: 420

It is obviously wrong, and weirdly so. It only works for “2 year”, not with other values:

mysql> select
UNIX_TIMESTAMP("2021-03-26 03:07:00" + INTERVAL 1-11 year_month) -
UNIX_TIMESTAMP("2021-03-26 02:07:00" + INTERVAL 1-11 year_month) as delta\G
delta: 3600

mysql> select
UNIX_TIMESTAMP("2021-03-26 03:07:00" + INTERVAL 1-12 year_month) -
UNIX_TIMESTAMP("2021-03-26 02:07:00" + INTERVAL 1-12 year_month) as delta\G
delta: 3600

mysql> select
UNIX_TIMESTAMP("2021-03-26 03:07:00" + INTERVAL 1-13 year_month) -
UNIX_TIMESTAMP("2021-03-26 02:07:00" + INTERVAL 1-13 …

As database footprints continue to explode, many companies are looking for ways to deal with such rapid growth.  One approach is to refactor traditional relational databases to fit into a NoSQL engine, where horizontal scalability is easier.  However, in many cases, this is in no way a trivial undertaking.

Another approach that has been gaining interest is the use of MyRocks as an alternative storage engine to the traditional InnoDB.  While not for everyone, in certain use cases it could be a potential solution.  As with so many things open source, the next standard questions are: which version should I use?  Any differences with the engine if I use MyRocks with MySQL 5.7 vs 8.0?

In this post, I wanted to touch on this and give some high-level thoughts on MyRocks when it comes to the version of MySQL.

…

Recovering to a particular time in the past is called Point-In-Time Recovery (PITR). With PITR you can rollback unwanted DELETE without WHERE clause or any other harmful command.

PITR with Percona XtraBackup is pretty straightforward and perfectly described in the user manual. You need to restore the data from the backup, then apply all binary logs created or updated after the backup was taken, but skip harmful event(s).

However, if your data set is large you may want to recover only the affected database or table. This is possible but you need to be smart when filtering events from the binary log. In this post, I will show how to perform such a partial recovery using Percona XtraBackup, …

Nobody likes change, especially when that change may be challenging.  When faced with a technical challenge, I try to remember this comment from Theodore Roosevelt: “Nothing in the world is worth having or worth doing unless it means effort, pain, difficulty.”  While this is a bit of an exaggeration, in this case, the main concept is still valid.  We shouldn’t shy away from an upgrade path because it may be difficult.

MySQL 8.0 is maturing and stabilizing.  There are new features (too many to list here) and performance improvements.  More and more organizations are upgrading to MySQL 8 and running it in production, which expedites the stabilization.  While there is still some significant runway on 5.7 and it is definitely stable (EOL slated for October 2023), organizations need to be preparing to make the jump if they haven’t already. 

What Changed?

So …