MySQL is an outstanding database for online transaction processing. With suitable hardware, it is easy to execute more than 1M queries per second and handle tens of thousands of simultaneous connections. Many of the most demanding web applications on the planet are built on MySQL. With capabilities like that, why would MySQL users need anything else?  

Well, analytic queries for starters. Analytic queries answer important business questions like finding the number of unique visitors to a website over time or figuring out how to increase online purchases. They scan large volumes of data and compute aggregates, including sums, averages, and much more complex …

Oracle releases updates to MySQL on a quarterly basis and the Release Notes for 8.0.31 arrived just before the software.  This time around there are some very interesting new features that will be handy including SQL standards support, as well as over 130 bug fixes.

The TL;DR:  Some nice new features but nothing spectacular.

• FULL is now a reserved word.
• InnoDB now supports parallel index builds, which improves index build performance. In particular, loading sorted index entries into a B-tree is now multithreaded.
• The OpenSSL library for MySQL Server has been updated to version 1.1.1q.
• The optimizer has been improved so that the old ER_NOT_SUPORTED_YET is not thrown when you try something like this:
  

      ((SELECT a, b, c FROM t ORDER BY a LIMIT 3) ORDER BY b LIMIT 2) ORDER …

As we have Kubernetes installed in part one (see Using Percona Kubernetes Operators With K3s Part 1: Installation), now we will install Percona Server for MySQL Operator into the running cluster.

I will copy some ideas from Peter’s Minukube tutorial (see Exploring MySQL on Kubernetes with Minkube).

In this case, I will use not Percona XtraDB Cluster Operator but a regular Percona Server for MySQL with Asynchronous replication.

We have recently released version 0.3.0 and it is still in the technical preview state, so we are actively looking for more feedback!

If we go with all …

A few weeks back, we faced an issue in a replication environment for a Managed Services client:

LAST_ERROR_MESSAGE: Worker 2 failed executing transaction ‘UUID:GTID’ at master binlog.0012345, end_log_pos 98765; Error ‘Operation CREATE USER failed for ‘test_user’@’10.10.10.10” on query. Default database: ‘mysql’. Query: ‘CREATE USER ‘test_user’@’10.10.10.10’ IDENTIFIED WITH ‘mysql_native_password’ AS ‘************”

After some initial investigation, we noticed that the user in the replica didn’t exist! Was MySQL going crazy? But then the customer mentioned they had the following error in the primary before being able to execute the query successfully:

root@localhost [mysql]> CREATE USER 'test_user'@'10.10.10.10' identified WITH 'mysql_native_password' BY …

If you watched Finding Poorly Designed Schemas and How to Fix Them you witnessed Marcos Albe use some very interesting queries. These queries let you find tables without primary keys, tables with non-integer primary keys, tables that do not use InnoDB, tables and indexes with the most latency, indexes that are 50% larger than the table, find duplicate indexes, and find unused indexes. As promised, they are below.

— Find tables without PK
SELECT t.table_schema,t.table_name,t.engine
FROM information_schema.tables t
JOIN information_schema.columns c
ON t.table_schema=c.table_schema
AND t.table_name=c.table_name
WHERE t.table_schema NOT IN (‘mysql’, ‘information_schema’, ‘sys’, ‘performance_schema’)
AND t.table_type = ‘BASE TABLE’
GROUP BY t.table_schema,t.table_name, t.engine
HAVING …

Geo locations are a cornerstone of modern applications. Whether you’re a food delivery business or a family photographer, knowing the closest “something” to you or your clients can be a great feature.

In our ‘Scaling and Optimization’ training class for MySQL, one of the things we discuss is column types. The spatial types are only mentioned in passing, as less than 0.5% of MySQL users know of their existence (that’s a wild guess, with no factual basis). In this post, we briefly discuss the POINT type and how it can be used to calculate distances to the closest public park.

Import the data

To start off, we need a few tables and some data. The first table will hold the mapping between the zip code and its associated latitude/longitude. GeoNames has this data under the Creative Commons v3 license, …

The microservice architecture is not a new pattern but has become very popular lately for mainly two reasons: cloud computing and containers. That combo helped increase adoption by tackling the two main concerns on every infrastructure: Cost reduction and infrastructure management.

However, all that beauty hides a dark truth:

The hardest part of microservices is the data layer

And that is especially true when it comes to classic relational databases like MySQL. Let’s figure out why that is.

MySQL and the microservice

Following the same two pillars of microservices (cloud computing and containers), what can one do with that in the MySQL space? What do cloud computing and containers bring to the table?

Cloud computing

The magic of the cloud is that it allows you to be cost savvy by letting you easily SCALE UP/SCALE DOWN the size of your instances. No more wasted money on …

When you develop an application you expect success, and often success comes with growth problems.  These problems especially show themselves in the area of data storage, where being stateful is not as easy to scale as the stateless parts of the application.

There are several stages of approaching database scalability:

1. Configuration and query optimization. This step can help a lot, and I would recommend a recent book by Daniel Nichter “Efficient MySQL Performance: Best Practices and Techniques”, which goes into this topic.
2. If #1 is done and you continue to push the limits of your database, the next step is to improve the hardware: adding extra memory, improving storage throughput (regular SSD, NVMe storage layer, etc.), or increasing the size of the cloud instances (this is what I call “optimization by credit card”). This typically should help, but only to a certain limit. And there is only so much …

We are looking to provide simplified ways to deploy Percona software in cloud environments, especially for more advanced scenarios like replication and multi-node cluster (in the case of Percona XtraDB Cluster).

For this I propose trying out our new Terraform provider, with the capabilities:

• Deploy in AWS or GCP Cloud. The provider will automatically create instances and deploy Percona Server for MySQL
• Deploy either Percona Server for MySQL or Percona XtraDB Cluster
• Choose instance size
• Choose storage volume size, type, and IOPs
• Multi-node async replication or multi-node Percona XtraDB Cluster
• Customize MySQL configuration file
• Capability to deploy MyRocks …

In a post written earlier this year – Percona Server for MySQL Encryption Options and Choices –  I discussed some of the options around encryption in MySQL.  Being such a complex topic, that post was meant to clarify and highlight various aspects of “encryption” at different levels.  I recently had this topic come up again, but specifically around column-level encryption and various options so I wanted to touch on this in more detail.

As of the current release of Percona Server for MySQL, there is no built-in way to define a single column as encrypted.  Ideally, there could be some metadata passed in a create statement and this would just automatically happen, such as this:

CREATE TABLE pii_data ( …