If you're looking to learn MySQL quickly and efficiently, Rick Silva's MySQL Crash Course is the perfect resource.

MySQL 5.7 reaches End of Life status this October. If you still need to start your migration, time is getting short. The first step for many is looking into the new reserved words in MySQL 8.0. As MySQL gets new functionality or the project matures, there are new additions to the list of reserved words you can not use as column names.

Reserved words added to 8.0

There is a list of the new reserved words later in this document that you need to review.

Odds are you are not using a column named Master_tls_ciphersuites, but what about Rank, System, Skip, or Lead? Those are a lot more common and may be in your table definitions, so your upgrade process will be harder. It is recommended that you use the util.checkForServerUpgrade() in the MySQL Shell to check for these Reserved Words.

So what happens if I use a reserved word?

Welcome back to the weekly OpenLampTech developer newsletter. I can’t thank you enough for reading the content each week. I hope you enjoy this week’s newsletter as much as I did. Thank you!

The Newsletter for PHP and MySQL Developers

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In OpenLampTech issue #72, we have content covering:

• WordPress settings API as a framework
• CodeIgniter and Laravel compared
• Laravel’s HTTP client
• SQL DELETE command in-depth
• And much, much more

If you are not already subscribed to the weekly …

In this article, we'll give a brief overview of SSH protocol and tunnel, as well as explore how to connect to a MySQL server remotely using the SSH tunnel created with the help of PuTTY, a popular Windows SSH client.

The post How to Connect to MySQL Remotely with SSH PuTTY Tunnels: A Step-by-Step Guide appeared first on Devart Blog.

In this new article about how to find the info when using MySQL Database Service on Oracle Cloud Infrastructure, we will learn about the query accelerator: HeatWave.

With HeatWave, you can boost the performance of your MySQL queries, providing your applications with faster, more reliable, and cost-effective access to data.

HeatWave is a high-performance in-memory query accelerator for MySQL Database Service on Oracle Cloud Infrastructure. It is designed to accelerate analytics workloads (OLAP) and increase the performance of your MySQL databases by orders of magnitude. This is achieved through the use of in-memory processing, advanced algorithms, and machine learning techniques to optimize query performance. If identified by the optimizer, OLTP requests can also be accelerated using HeatWave.

Today we will try to answer the following questions:

1. Can I use HeatWave ?
2. Is HeatWave enabled ?
…

New series of articles about how to find useful informarion when using MySQL Database Service.

I just booked my travel arrangements for Percona Live 2023.  In case you missed it, one of the most important MySQL Conference of the year is happening in Denver from Monday May 22 to Wednesday 24.  I will be there and I am giving a talk about how HubSpot operates Percona Server / MySQL with Vitess in Kubernetes.  My colleague, Mali Akmanalp, is also speaking about the tools we

With local or on-premise instances of MySQL, we can use the general_log to view the queries that are executed when we make calls to the MySQL Document Store API. This approach, however, does not work when working with MySQL Database Service (MDS) instances running in Oracle Cloud Infrastructure. In this post, we'll show you how to get the raw SQL that is executed on as MDS instance when we make calls to the Document Store API.

In a previous post, we talked about how you can view the underlying queries that are run when we make calls to the MySQL Document Store API. While this solution works well on a local or other on-premise instance of MySQL, it is not a viable option for viewing those same queries on a MySQL Database Service (MDS) instance running […]

A partitioned table in MySQL has its data separated into different tablespaces while still being viewed as a single table. Partitioning can be a useful approach in some cases when handling huge sets of data. Deleting huge data sets could be quickened up in a partitioned table, but if not handled properly, it can misplace your data in the table. In this blog, I will share how to check and fix the data in such a table with minimal disruption to the table.

In this example, we use a table partitioned based on a date range.

mysql> show create table salariesG
*************************** 1. row ***************************
       Table: salaries
Create Table: CREATE TABLE `salaries` (
  `emp_no` int(11) NOT NULL,
  `salary` int(11) NOT NULL,
  `from_date` date NOT NULL,
  `to_date` date NOT NULL,
  PRIMARY KEY (`emp_no`,`from_date`)
) ENGINE=InnoDB DEFAULT CHARSET=latin1
/*!50500 PARTITION BY RANGE  COLUMNS(from_date)
(PARTITION p01 VALUES LESS …