In this article, we will demonstrate how to achieve asynchronous replication automatic source failover when our replica is a Percona Server for MySQL (PS) and the source is a Percona XtraDB Cluster (PXC) cluster, using virtual IP (VIP) managed by Keepalived.

Let us consider our architecture below with async replication from PXC to Percona Server for MySQL:

PXC               PS-MySQL
==============    ==============
node1      +----> node4
node2      |       
node3 -----+

Our goal is to set node3 as the async replication primary source. Then, upon failure, VIP can move to node2 and then node1 when node2 also fails. Once node3 becomes available again, the virtual IP should come …

MySQL HeatWave enables users to process and query hundreds of terabytes of data in the object store—in a variety of file formats, such as CSV, Parquet, and Aurora/Redshift export files but let's see how we can benefit from Lakehouse to archive MySQL Data in OCI.

The ability to store data on Object Storage and retrieve it dynamically when necessary is a notable advantage of Lakehouse when managing MySQL historical data we would like to archive.

Let’s illustrate this with the following table:

CREATE TABLE `temperature_history` (
  `id` bigint unsigned NOT NULL AUTO_INCREMENT,
  `time_stamp` timestamp NULL DEFAULT CURRENT_TIMESTAMP,
  `device_id` varchar(30) DEFAULT NULL,
  `value` decimal(5,2) NOT NULL DEFAULT '0.00',
  `day_date` date GENERATED ALWAYS AS (cast(`time_stamp` as date)) STORED NOT NULL,
  PRIMARY KEY (`id`,`day_date`),
  KEY `device_id_idx` (`device_id`)
) ENGINE=InnoDB AUTO_INCREMENT=129428417 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci SECONDARY_ENGINE=RAPID
/*!50500 PARTITION BY RANGE  COLUMNS(day_date)
(PARTITION p0_before2023_11 VALUES LESS THAN ('2023-11-01') ENGINE = InnoDB,
 PARTITION p2023_12 VALUES LESS THAN ('2023-12-01') ENGINE = InnoDB,
 PARTITION p2024_01 VALUES LESS THAN …

Over 15 years ago, GitHub started as a Ruby on Rails application with a single MySQL database. Since then, GitHub has evolved its MySQL architecture to meet the scaling and resiliency needs of the platform—including building for high availability, implementing testing automation, and partitioning the data. Today, MySQL remains a core part of GitHub’s infrastructure and our relational database of choice.

This is the story of how we upgraded our fleet of 1200+ MySQL hosts to 8.0. Upgrading the fleet with no impact to our Service Level Objectives (SLO) was no small feat–planning, testing and the upgrade itself took over a year and …

Ensuring the security and resilience of your data hinges on having a robust backup strategy, and Percona XtraBackup (PXB), our open source backup solution for all versions of MySQL, is designed to make backups a seamless procedure without disrupting the performance of your server in a production environment.

When combined with the versatility of Docker containers, it becomes a dynamic duo, offering a scalable approach to data backup and recovery. Let’s take a look at how they work together.

Working with Percona Server for MySQL 8.1 and PXB 8.1 Docker imagesStart a Percona Server for MySQL 8.1 instance in a Docker container

Percona Server for MySQL has an official Docker image hosted on Docker Hub. For additional details on how to run an instance in a Docker environment, refer to this section in …

Microprocessors have become quite common and they for a variety of reasons. Check out this blog post on how to install MySQL on a Raspberry Pi to use it as a database server.

During an interview or while having general discussions, I have found some funny responses that can be easily classified as “Wrong Answers,” but at times, they’re thought-provoking or involve a deep meaning within. This blog is regarding some of the usual MySQL database conversations and responses, which can appear “wrong” or “funny,” but there’s actually more to them. I will share a selection of such seemingly “wrong” or whimsical responses and take a closer look at the valuable lessons and perspectives they offer.

Let the “MySQL Interview” begin.

Q: How will you improve a slow query?

A: Let’s not execute it at all. A query avoided is a query improved.

While this is a fact, we should carefully consider whether a query is necessary before executing it. Avoiding unnecessary queries and fetching only the required data can significantly optimize the query’s performance.

An …

Senior Backend Engineer Tanner Record discusses PHP, WordPress, and SQL in this developer interview for OpenLampTech.

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…

Let's check is MySQL HeatWave improves query response time.

You may have come across numerous presentations showcasing MySQL HeatWave as a Query Accelerator for MySQL. However, if you have not yet had the opportunity to test it yourself (if you have, you already know the answer), allow us to conduct a test using actual data to determine the potential benefits of utilizing a MySQL HeatWave Cluster.

Data & Queries

The data is simple, some arduinos with a DHT22 sensor sending temperature and humidity.

So first let’s have a look at the amount of collected data:

select format_bytes(sum(data_length)) DATA,
       format_bytes(sum(index_length)) INDEXES,
       format_bytes(sum(data_length + index_length)) 'TOTAL SIZE'
from information_schema.TABLES order by data_length + index_length;
+-----------+-----------+------------+
| DATA      | INDEXES   | TOTAL SIZE |
+-----------+-----------+------------+
| 21.89 GiB | 14.06 GiB | 35.95 GiB  |
+-----------+-----------+------------+
1 …