It is always hard to select a CPU for your own purpose. You could waste hours reviewing different benchmarks, reviews, and bloggers, and in the end, we would limit all our requirements to performance and price. For performance measuring we already have some specific metrics (e.g. in MHz to some specific tool), however, for economic comparison, it is quite hard.  Mostly we are limited by our budget. Again, for our personal purposes, we are limited only with the cash in our pockets. It is easy to compare only two or three CPUs; it is required just to compare their price and performance and then create a simple bar plot and then check the results. However, what do you do if you have at least three types of CPU, a different number of CPUs cores on board, and seven different scenarios?  It was a challenge to do it for performance, and for economic efficiency, it has become a nightmare. For a one-time purchase, it should be easier than for the …

On the previous article we saw how to easily deploy Apache Zeppelin on OCI with MySQL using Terraform.

In this article we will see how we can accelerate queries enabling MySQL HeatWave.

Enabling HeatWave

If you used a MySQL Database Service Shape compatible with HeatWave (MySQL.HeatWave.VM.Standard.E3), using the same Resource Manager Stack, you have the possibility to enable HeatWave and deploy a HeatWave Cluster for your MySQL.

The first think to do, is to edit the previous applied stack:

As we used a HeatWave compatible shape, we have the choice to deploy a HeatWave Cluster and we can choose it:

Save and Apply… the HeatWave cluster will be added:

If you …

Apache Zeppelin is a web-based notebook that enables data-driven,
 interactive data analytics, machine learning, and collaborative documents with SQL, Scala, Python, R.

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

You can manually deploy a compute instance and install zeppelin on it then connect to MySQL Database Service or you can use the Terraform modules I’m sharing on GitHub: https://github.com/lefred/oci-zeppelin-mds

Finally you can also deploy all this by just clicking on the follow button to use …

Recently we published the first part (m5, m5a, m6g) and the second part (C5, C5a, C6g) of research regarding comparing Graviton ARM with AMD and Intel CPU on AWS. We selected general-purpose EC2 instances with the same configurations (amount of vCPU in the first part). In the second part, we compared compute-optimized EC2 instances with the same conditions. The main goal was to see the trend and make a general comparison of CPU types on the AWS platform only for MySQL. We didn’t set the goal to compare the performance of different CPU types. Our expertise is in MySQL performance tuning. We share research “as is” with all scripts, and anyone interested could rerun and reproduce it.
All scripts, …

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 …

This post is the first 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.

In this first article we will start by creating a MySQL DB System and a Compute instance in OCI. One of the goal is also to see the benefits of HeatWave, so we will start by creating this …

We have a quickstart guide for how to install Percona Distribution for MySQL Operator on minikube. Installing the minimal version works well as it is described in the guide. After that, we will have one HAproxy and one Percona XtraDB Cluster (PXC) node to work with.

Minikube provides Kubernetes locally. One can try using the provided local k8s to try the more advanced scenarios such as the one described here.

Following that guide, everything works well, until we get to the part of deploying a cluster with

deploy/cr.yaml

Even after that, things seemingly work.

$ kubectl get pods
NAME READY STATUS RESTARTS AGE …

A recommendation we often give to our customers is along the lines of “archive old data” to reduce your database size. There is a tradeoff between keeping all our data online and archiving part of it to cold storage.

There could also be legal requirements to keep certain data online, or you might want to query old data occasionally without having to go through the hassle of restoring an old backup.

In this post, we will explore a very useful feature of AWS RDS/Aurora that allows us to export data to an S3 bucket and run SQL queries directly against it.

Archiving Data to S3

Let’s start by describing the steps we need to take to put our data into an S3 bucket in the required format, which is called Apache Parquet.

Amazon states the Parquet format is up to 2x faster to export and consumes up to 6x less storage in S3, compared to other text formats.

1. Create a snapshot of the database (or …

On behalf of the Vitess maintainers, I am pleased to announce the general availability of Vitess 12. Major Themes # In this release, Vitess Maintainers have made significant progress in several areas, including Gen4 planner, VTAdmin, and other improvements. Please take a moment to review the Release Notes. Please read them carefully and report any issues via GitHub. Gen4 Planner # The newest version of the query planner, Gen4, becomes an experimental feature as part of this release.