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Displaying posts with tag: MySQL 8.0 (reset)
Exploring Aurora Serverless V2 for MySQL

Aurora Serverless V2 is generally available around the corner recently 21-04-22 for MySQL 8 and PostgreSQL, with promising features that overcome the V1 disadvantages. Below are those major features

Features

  • Online auto instance upsize (vertical scaling)
  • Read scaling (Supports up to 15 Read-replica)
  • Supports mixed-configuration cluster ie, the master can be normal Aurora(provisioned) and readers can be in serverlessv2 and vice versa
  • MultiAZ capability (HA)
  • Aurora global databases (DR)
  • Scaling based on memory pressure
  • Vertically Scales while SQL is running
  • Public IP allowed
  • Works with custom port
  • Compatible with Aurora version 3.02.0 ie., >= MySQL 8.0.23 (only supported)
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A graph a day, keeps the doctor away ! – MySQL Checkpoint Age

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 …

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MySQL 8.0.29: thank you for the contributions

When it’s time for a new MySQL release, it’s also time to thank our contributors !

Released on April 26th, MySQL 8.0.29 contains several contributions from our awesome Community and on behalf of the entire MySQL Team, I would like to thank you all !

This new releases contains patches from Vilnis Termanis, Luke Weber, Meik Milevczik, Song Zhibai, Zheng Lai, Øystein Grøvlen, Facebook, Biran Yue, Hope Lee, Rahul Malik, Christopher Chavez, Chen Yi, Ning PeiPei, Jianjian Song, Jack Wotherspon and Bin Wang.

Once again, thank you all for your great contributions and to the company you are working for.

Here is the list of the above contributions and related bugs:

Clients / Connectors

  • #81519 Connector/Python: Guarantee file closing of input files in optionfiles module – Vilnis Termanis
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Poorman’s MySQL monitoring/trending

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 …

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Poorman’s MySQL table audit information – part 3

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

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 …

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Poorman’s MySQL table audit information – part 2

I really enjoyed to dig into the solution I described yesterday in this post, to generate table audit information using invisible columns and triggers.

In this post, I will focus only on the solution using a JSON column to store the audit information.

Yesterday, I wrote that it’s also possible to track all changes an not only the last one but also keep information about what changed.

I wanted to illustrate that with an example, let’s start with the output:

This is exactly what I was looking for !

And of course we can search in that audit information. For example let’s search for all records that have been modified and where the old or new name was/is frederic:

We can verify that indeed that record had frederic as initial value.

Triggers

Compare …

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Poorman’s MySQL table audit information

Today, somebody asked me how he could track the creation of a record (who created it and when) and who and when it was last modified.

Usually, this is performed in a different table, called audit table. In MySQL you can create an audit table and populate it using triggers.

But of course, this person had some constraints, otherwise it would have been too easy:

  1. no other table could be used/created
  2. the application should keep working without any changes

He was desperate for help…

MySQL 8.0 Invisible Columns

The answer is : Invisible Columns.

Let’s have a look at a simple table, containing an ID as primary key, a first name and a last name. And of course the application must work as expected… and unfortunately, it seems the application is …

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Deploying Apache Airflow on OCI with MySQL HeatWave Database Service

Apache Airflow is an open-source workflow management platform for data engineering pipelines.

Today we will see how we can deploy very easily Apache Airflow on a Compute instance in Oracle Cloud Infrastructure (OCI) using MySQL HeatWave Database Service (MDS).

I am sharing Terraform modules you can use to deploy in your architecture:

Architectures

With the modules you can deploy architectures like these:

with a single MDS instancewith MDS High Availabilitywith HeatWave Cluster

We will use the exact same modules built into a stack for OCI’s Resource Manager. This will allow us to deploy the architecture just in few clicks.

Deployment

We open in a browser the following GitHub repository: …

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Readable MultiAZ Cluster with AWS RDS MySQL under the hood.

Amazon Web Services (AWS) very recently(March 02, 2022) announced the GA of its new RDS feature “Readable standby with Multi-AZ deployments” for MySQL. Yes !! you heard it right you can now use the standby instances created with Multi-AZ deployments for failover as well as for Read-scaling starting with version 8.0.26 and later for MySQL in RDS

Launching a MultiAZ Cluster

Now let us see how to launch this readable-Multi AZ cluster?

Region Availability: As this is a new feature now it is currently limited to the regions US-EAST-1 (N.Virginia), US-WEST-1 (Oregon), and EU-WEST-1 (Ireland), this list would be extended progressively

VPC requirement:

Before launching the instance, you should have SUBNET created for 3 AZ(Availability Zone) within the VPC since the cluster instances would be spawn across 3AZ by default

Hereunder the “Engine Option” …

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How to modify a JSON field in SQL ?

Let’s start with some info about how MySQL Document Store handles JSON documents.

Document Store and CRUD

We know that MySQL 8.0 Document Store handles JSON documents with CRUD operations. We can add, delete and modify those documents very easily:

 JS >db.mycollection.find()
{
    "_id": "0000624d3e890000000000000001",
    "name": "my_iot1",
    "type": "sensor",
    "capabilities": "{'temperature':'true','humidity':'true'}"
}
{
    "_id": "0000624d3e890000000000000002",
    "name": "my_iot2",
    "type": "sensor",
    "capabilities": "{'temperature':'true'}"
}
2 documents in set (0.0007 sec)

To modify a document, the modify method can be used in different ways:

As illustrate above, we have:

  • set()
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