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MySQL Connector/J 8.0.20 has been released

Dear MySQL users,

MySQL Connector/J 8.0.20 is the latest General Availability release of
the MySQL Connector/J 8.0 series.  It is suitable for use with MySQL
Server versions 8.0, 5.7, and 5.6.  It supports the Java Database
Connectivity (JDBC) 4.2 API, and implements the X DevAPI.

This release includes the following new features and changes, also
described in more detail on

https://dev.mysql.com/doc/relnotes/connector-j/8.0/en/news-8-0-20.html

As always, we recommend that you check the “CHANGES” file in the
download archive to be aware of changes in behavior that might affect
your application.

To download MySQL Connector/J 8.0.20 GA, see the “General Availability
(GA) Releases” tab at …

[Read more]
Webinar 5/11: Percona & PlanetScale Present: Introduction to Vitess on Kubernetes for MySQL

During this joint webinar our speakers, Alkin Tezuysal, Technical Expert at Percona and Sugu Sougoumarane, Co-Founder and CTO at PlanetScale, will provide attendees with hands-on experience using Vitess using Kubernetes. They will start by providing a quick overview of Vitess – including key concepts and terminology, and then describe the deployment options for both in Kubernetes.

The hands-on exercises will cover many of the key workflows with running a sharded system:

– Moving from an unsharded system to a vertical split one (moving some tables to a different host)
– Sharding large tables across several instances
– Backups, Recoveries, and failovers (both planned and unplanned).

Attendees are not expected to have any prior experience with Vitess but will find it useful if they have prior experience completing these tasks in a MySQL environment and general know-how …

[Read more]
MySQL Connector/NET 8.0.20 has been released

Dear MySQL users,

MySQL Connector/NET 8.0.20 is the latest General Availability release of
the MySQL Connector/NET 8.0 series. This version supports .NET Core 3.1
and the X DevAPI, which enables application developers to write code
that combines the strengths of the relational and document models using
a modern, NoSQL-like syntax that does not assume previous experience
writing traditional SQL.

To learn more about how to write applications using the X DevAPI, see
http://dev.mysql.com/doc/x-devapi-userguide/en/index.html. For more
information about how the X DevAPI is implemented in Connector/NET, see
http://dev.mysql.com/doc/dev/connector-net.
NuGet packages provide functionality at a project …

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What makes MySQL LRU cache scan resistant

The MySQL InnoDB Storage engine uses LRU cache but it suffers from a notorious problem. In this article, we find how by using Midpoint Insertion Strategy and changing one aspect of LRU, MySQL becomes scan resistant and super performant.

Choosing the best indexes for MySQL query optimization

Many of our users, developers and database administrators, keep asking our team about EverSQL's indexing recommendations algorithm. So, we decided to write about it.

The first option is to use EverSQL to automatically find indexes that are best for your database.

The second option is to read our detailed tutorial below and learn more about indexing best practices.

This tutorial won't detail all the internals of the algorithm, but rather try to lay out the basic and important aspects of indexing, in simple terms.
Also, and most importantly, we'll present practical examples for properly indexing your tables and queries by relying on a set of …

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MySQL Threads Running

Queries per second (QPS) measures database throughput, but it does not reflect how hard MySQL is working. The latter is measured by Threads_running, expressed as a gauge (whereas QPS is a rate). Before discussing Threads_running, let’s consider an analogy: The image above is a digital instrument cluster from a car. The big circle on the left is the speedometer, and the big circle on the right is the tachometer. Speedometers are familiar to most: they show how fast the car is going.

MySQL Threads Running

Queries per second (QPS) measures database throughput, but it does not reflect how hard MySQL is working. The latter is measured by Threads_running, expressed as a gauge (whereas QPS is a rate). Before discussing Threads_running, let’s consider an analogy:

MySQL Threads Running

Queries per second (QPS) measures database throughput, but it does not reflect how hard MySQL is working. The latter is measured by Threads_running, expressed as a gauge (whereas QPS is a rate). Before discussing Threads_running, let’s consider an analogy:

MySQL Threads Running

Queries per second (QPS) measures database throughput, but it does not reflect how hard MySQL is working. The latter is measured by Threads_running, expressed as a gauge (whereas QPS is a rate). Before discussing Threads_running, let’s consider an analogy:

Use Case: Geo-Scale Multi-Master MySQL with Disaster Recovery

How to build a multi-region, multi-master MySQL cloud database back-end capable of serving a global high volume cloud contact center

This global SaaS provider is a Cloud Contact Center solution provider (the leading Salesforce telephony solution), who needed to deliver up-to-date data to clients as quickly as possible. Its cloud-based call center software frees users to make every conversation personal; it supports the creation of exceptional customer experiences that help serve better and sell more. Its technology is 100% cloud-based and device-agnostic for telephony infrastructure.

What is the Challenge?

Active/Active (multi-master) MySQL clustering is needed when there is significant update load on geographically distributed applications. These require fast response times both for updates and reads, and they also need to share data on a global scale.

  • Regional distribution of data
  • Deliver …
[Read more]
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