Connect PlanetScale to JetBrains DataGrip to use database branching, deploy requests, and non-blocking schema changes

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It is a common use case to synchronize data in two tables inside MySQL servers. This blog post describes one specific case: how to synchronize data between two different tables on the same MySQL server. This could be useful, for example, if you test DML query performance and do not want to affect production data. After few experiments, tables get out of sync and you may need to update the test one to continue working on improving your queries. There are other use cases when you may need to synchronize the content of the two different tables on the same server, and this blog will show you how to do it.

Table Content Synchronization

The industry-standard tool for table content synchronization – pt-table-sync – is designed to synchronize data between different MySQL servers and does not support bulk synchronization between two …

An interesting outcome of teaching SQL is discovering what skills new users require. One that I continuously rediscover is how to build a test case for various elements of SQL. This is a small article on querying with filters in the WHERE clause.

There are several of the exercises in Alan Beaulieu’s Learning SQL, 3rd Edition that would benefit from example setup. For example, Chapter 4 provides a snapshot of the payment table but doesn’t provide any instructions.

You can create an exercise_4_2 table with the following SQL statement if you plan to change the data:

CREATE TABLE exercise_4_2 AS
SELECT payment_id
,      customer_id
,      amount
,      payment_date
FROM   payment
WHERE  payment_id BETWEEN 101 AND 120;

Alternatively, you can create an exercise_4_2 view with the following SQL statement if you plan to only query the data:

CREATE VIEW exercise_4_2 AS
SELECT payment_id
, …

[…] I am connecting following Andrews advice: Stackoverflow Link Also, Monitoring and Managing […]

 Want to learn MySQL? Have an hour or so?  Go to Oracle's Learning Explorer and sign up for the FREE MySQL Explorer learning path.  It begins with an overview of MySQL, discusses the client/server model, and then leads you through the use of MySQL.  You do not need previous MySQL or database experience.

MySQL is the most-used opensource database and over the years I have has requests for introductory materials. Well, now I can send them to the MySQL Explorer for some web based training. And you can earn the explorer badge when you pass the end of class quiz.

…

In a previous post, A Horizontal Scalability Mindset for MySQL, I discussed the concerns around growing individual MySQL instances too large and some basic strategies:

• Optimizing/minimizing size with proper data types
• Removing unused/duplicate indexes
• Keeping your Primary Keys small
• Pruning data

Finally, if those methods have been exhausted, I touched on horizontal sharding as the approach to keep individual instances at a reasonable size. When discussing my thoughts across our internal teams, there was lots of feedback that we needed to dive into the sharding topic in more detail. This post aims to give more theory and considerations around sharding along with a lightweight ProxySQL sample implementation.

What is Sharding?

Sharding is a word that is frequently used but …

MySQL, the world’s most popular open source database, is available as a managed cloud service in Oracle Cloud Infrastructure (OCI) under the name of MySQL Database Service (MDS).

This is the ninth episode of “Discovering MySQL Database Service“, a series of tutorials where I will show you, step by step, how to use MySQL Database Service and some other Oracle Cloud Infrastructure services.

In this episode, we’ll learn how to connect to our MySQL Database Service instance using MySQL Workbench – a unified visual tool for database architects, developers, and DBAs that provides data modeling, SQL development, and comprehensive administration tools for server configuration, user administration, backup, and much more.

The post Discovering MySQL Database …

I ranted about hiring interviews, and the canned questions that people have to answer. One of the interviews we do is a systems design interview, where we want to see how (senior) people use components and patterns to design a system for reliability and scale-out.

A sample question (based on a Twitter thread

in German):

It is 2010, and the company has a database structure where a fixed number front end machines form a cell. Reads and writes are already split: Writes go to the primary of a replication tree, and are being replicated to the read instance of the database in each cell. Reads go to the database instance that is a fixed part of the cell.

Read and write handles are split in the application. Clients write to a primary MySQL database, which then replicates to a database instance that is fixed part of a cell. Clients …

I ranted about hiring interviews, and the canned questions that people have to answer. One of the interviews we do is a systems design interview, where we want to see how (senior) people use components and patterns to design a system for reliability and scale-out.

A sample question (based on a Twitter thread in German):

It is 2010, and the company has a database structure where a fixed number front end machines form a cell. Reads and writes are already split: Writes go to the primary of a replication tree, and are being replicated to the read instance of the database in each cell. Reads go to the database instance that is a fixed part of the cell.

Read and write handles are split in the application. Clients write to a primary MySQL database, which then replicates to a database instance that is fixed part of a cell. Clients from a …

As a Technical Account Manager at Percona, I get to work with many of our largest clients. While the industry verticals vary, one main core challenge generally remains the same – what do I do with all this data? Dealing with massive data sets in MySQL isn’t a new challenge, but the best approach still isn’t trivial. Each application is obviously different, but I wanted to discuss some of the main best practices around dealing with lakes of data.

Keep MySQL Instances Small

First and foremost, the architecture needs to be designed to keep each MySQL instance relatively small. A very common question I get from teams new to working with MySQL is: “So what is the largest instance size MySQL supports?”. My answer goes back to my time in consulting: “It depends”. Can my MySQL instance support a 20TB dataset? Maybe, but it depends on the workload pattern. Should I store 20TB of data in a single MySQL instance? In most cases, …