You know how much I praise and like MySQL Shell but if like me, for you too, old habits die hard, I advise you to create these different aliases in your ~/.bashrc (or ~/.bash_aliases) file to force yourself to use MySQL Shell even for a small statement check:

alias mysql="mysqlsh --sql mysql://localhost"
alias mysqlx="mysqlsh --js mysqlx://localhost"

Of course you can specify the user you want, by default it uses the same user as the system one.

For example, if this is your test machine and you want to always use the root account (even if not recommended), you can specify it like this by modifying the URI:

alias mysql="mysqlsh --sql mysql://root@localhost"

Example:

So now when using mysql MySQL Shell is launched and it connects directly to localhost in SQL mode using the classic protocol.

With …

Full table scans can be problematic for performance. Certainly if the scanned tables are large. The worst case is when full table scans are involved in joins and particularly when the scanned table is not the first one (this was dramatic before MySQL 8.0 as Block Nested Loop was used) !

A full table scans means that MySQL was not able to use an index (no index or no filters using it).

Effects

When Full Table Scans happen (depending of the size of course), a lot of data gets pulled into the Buffer Pool and maybe other important data from the working set is pulled out. Most of the time that new data in the Buffer Pool might even not be required by the application, what a waste of resources !

You then understand that another side effect of Full Table Scans is the increase of I/O operations.

The most noticeable symptoms of Full Table Scans are:

• increase of CPU usage
• increase of …

This is the second article of the series dedicated to MySQL trending.

As I wrote before, understanding your workload and seeing the evolution of it over time can help anticipating problems and work on solutions before the breakdown.

This article covers MySQL History List Length also known as HLL.

MySQL History List is related to InnoDB Undo Logs. InnoDB is a multi-version storage engine (MVCC). It keeps information about old versions of changed rows to support transactional features such as concurrency and rollback. This information is stored in undo tablespaces in a data structure called a rollback segment.

This means that you can start a transaction and continue to see a consistent snapshot even if the data changed by other transaction. This behavior is related to the …

In a previous post, I explained how you can collect and plot metrics using MySQL Shell.

This is a new series of article where I will explain how to read and understand some of the generated graphs.

Understanding your workload and seeing the evolution of it over time can help anticipating problems and work on solutions before the breakdown.

Let’s start the series with a concept that is not always well understood or at least not always considered at its true value: MySQL Checkpoint Age.

example of checkpoint age graphInnoDB Checkpointing

Before analyzing the graph, we need to understand what is MySQL InnoDB Checkpointing.

Each change to a data page in the InnoDB Buffer Pool are also written into the Write Ahead Logs.

In the literature they are sometimes called Transaction …

We had an interesting set of questions regarding the REGEXP comparison operator in MySQL today in both sections of Database Design and Development. They wanted to know the default behavior.

For example, we built a little movie table so that we didn’t change their default sakila example database. The movie table was like this:

CREATE TABLE movie
( movie_id     int unsigned primary key auto_increment
, movie_title  varchar(60)) auto_increment=1001;

Then, I inserted the following rows:

INSERT INTO movie 
( movie_title )
VALUES
 ('The King and I')
,('I')
,('The I Inside')
,('I am Legend');

Querying all results with this query:

SELECT * FROM movie;

It returns the following results:

+----------+----------------+
| movie_id | movie_title    |
+----------+----------------+
|     1001 | The King and I |
|     1002 | I              |
|     1003 | The I Inside   |
|     1004 | I am Legend …

I could have also called this article When Pandas meet Dolphins in MySQL Shell.

Some time ago, I wrote a post related on how to collect initial relevant data when trying to seek help for MySQL.

Since then, the MySQL Shell engineering team implemented another powerful native utility that collect all the essential information and more and store them in a single zip file.

This zip archive contains TSV and YAML files that, for example, the MySQL Support Team could use to solve your eventual issue.

For more information regarding MySQL Shell’s util.debug.collectDiagnostics(), I encourage you to check the manual.

This tool is …

Recently we saw how we can catch audit information using invisible column, JSON data type and triggers in MySQL 8.0:

• Poorman’s MySQL table audit information
• Poorman’s MySQL table audit information – part 2

Of course, the creation of these triggers can quickly become a tedious operation. Once again, MySQL has all what we need to make it simple.

As you may know, it’s impossible to create triggers from store procedure, so using a sys schema function would not be something possible. However, MySQL Shell is again the answer ! It’s very easy to use a python plugin to perform the necessary operations.

I’ve written such example, available on …

MySQL Database Service on OCI is all over the tech news with the latest HeatWave ML announcement [1][2][3][4][5].

This article explains how to perform a live migration of your Azure/MySQL to OCI/MySQL.

As Azure allows public connections directly to the database, this is what …

This post is the third and last of a series of articles dedicated to MySQL Database Service (MDS):

• Using MySQL Database Service in OCI – Part 1: creating a MySQL DB System
• Using MySQL Database Service in OCI – Part 2: importing Data to MySQL DB System
• Using MySQL Database Service in OCI – Part 3: faster with MySQL HeatWave !

The goal of this series if to get familiar with MDS, HeatWave and useful MySQL Shell utilities.

We can now start a query on our MDS instance that has been populated with >200M rows:

 SQL > SELECT year, Reporting_Airline,  
              AVG(ArrDelay) AS avgArrDelay …

This post is the second of a series of articles dedicated to MySQL Database Service (MDS):

• Using MySQL Database Service in OCI – Part 1: creating a MySQL DB System
• Using MySQL Database Service in OCI – Part 2: importing Data to MySQL DB System
• Using MySQL Database Service in OCI – Part 3: faster with MySQL HeatWave !

The goal of this series if to get familiar with MDS, HeatWave and useful MySQL Shell utilities.

Before we start, I would like to highlight that the fastest and recommended way to import data to a MySQL DB System in OCI is to use a parallel dump created using MySQL to Object Storage and load it …