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Displaying posts with tag: MySQL (reset)
Discovering MySQL Database Service – Episode 10 – Connect to MySQL Database Service Using OCI Cloud Shell

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 tenth 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 the Oracle Cloud Infrastructure Cloud Shell.
It provides a pre-authenticated Oracle Cloud Infrastructure CLI and preinstalled developer tools for easily managing Oracle Cloud resources.

The post Discovering MySQL Database Service – Episode 10 – Connect to MySQL Database …

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Synchronize Tables on the Same Server with pt-table-sync

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 …

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MySQL SQL Filters

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
, …
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Horizontal Scaling in MySQL – Sharding Followup

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 …

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Discovering MySQL Database Service – Episode 9 – Connect to MySQL Database Service Using MySQL Workbench

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 …

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A Horizontal Scalability Mindset for MySQL

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, …

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MySQL Upgrade Checker, Review the Report, Before you Upgrade.

MySQL introduced the MySQL “Upgrade Checker” initially to support upgrades from MySQL 5.7 to 8.0 series. However, the continuous development initiative in the MySQL 8.0 release series has continued this tools usefulness, as it can also report on continuous delivered features throughout the MySQL 8.0 release series. Additionally, “Yes”, bug fixes are always part of that development release… Read More »

Enhanced Password Management Systems in MySQL 8: Part 1

MySQL 8 comes with a lot of good features, and recently I explored its password management systems. I wanted to put together a series of blogs about it, and this is the first part. In this post, I am going to explain the following topics in detail.

  • Password Reuse Policy
  • Random Password Generation

Password Reuse Policy

MySQL has implemented restrictions on reusing passwords. Restriction can be established in two ways:

  • Number of password changes
  • Time elapsed

Number of Password Changes

From the MySQL documents:

If an account is restricted on the basis of number of password changes, a new password cannot be chosen from a specified number of the most recent passwords.

To test this, in my local environment I have created the user with “number of password changes = 2”.

mysql> create user …
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Medium Cross-post – CodeIgniter 4 CRUD: Update

In some applications, data may never change. Yet, in others, data changes numerous times in its lifecycle. In SQL the UPDATE command changes existing rows of data. CodeIgniter 4 Models have 2 methods available for update operations: update() and save(). Continue reading and learn more about update()

Self-Promotion:

If you enjoy the content written here, by all means, share this blog and your favorite post(s) with others who may benefit from or like it as well. Since coffee is my favorite drink, you can even buy me one if you would like!

CodeIgniter 4 CRUD Series with MySQL

This post is a re-share of an article I originally published on my Medium account and is part 3 in the CodeIgniter 4 CRUD with MySQL series. Be sure and …

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Making Aurora Write Latency 15x Higher (or More!) by Choosing a Bad Primary Key

Primary Key design is an important thing for InnoDB performance, and choosing a poor PK definition will have an impact on performance and also write propagation in databases. When this comes to Aurora, this impact is even worse than you may notice.

In short, we consider a poor definition of a Primary Key in InnoDB as “anything but quasi sequential values”, which may cause very random access to data and thus increase the IO dependency.

In this post, I’ll try to demonstrate the potential impact of the primary key design when running on Aurora, and how a bad design can lead to a 15x write latency penalty (or more).

The Analysis

Recently I worked on a case where a customer was having issues with scaling writes in Aurora MySQL. While this is a known limitation in Aurora considering how the distributed storage layer syncs out data among all nodes of the cluster, we observed additional latency occurring when more …

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