In this post, I am going to show you how to run Orchestrator on FreeBSD. The instructions have been tested in FreeBSD 11.3 but the general steps should apply to other versions as well.

At the time of this writing, Orchestrator doesn’t provide FreeBSD binaries, so we will need to compile it.

Preparing the Environment

The first step is to install the prerequisites. Let’s start by installing git:

[vagrant@freebsd ~]$ sudo pkg update
Updating FreeBSD repository catalogue...
Fetching meta.txz: 100% 944 B 0.9kB/s 00:01
Fetching packagesite.txz: 100% 6 MiB 492.3kB/s 00:13
Processing entries: 100%
FreeBSD repository update completed. 31526 packages processed.
All repositories are up to date.

[vagrant@freebsd ~]$ sudo pkg install git
Updating FreeBSD repository catalogue...
FreeBSD repository is up to date.
All repositories are up to date.
New …

In the past year, GitHub engineers shipped GitHub Packages, Actions, Sponsors, Mobile, security advisories and updates, notifications, code navigation, and more. Needless to say, the development pace at GitHub is accelerated.

With MySQL serving our backends, updating code requires changes to the underlying database schema. New features may require new tables, columns, changes to existing columns or indexes, dropping unused tables, and so on. On average, we have two schema migrations running daily on our production servers. Some days we have a half dozen migrations to run. We’ll cover how this amounted to a significant toil on the database infrastructure team, and how we searched for a solution to automate the manual parts of the process.

What’s in a migration?

At first …

Using numbers produced already with MySQL Cluster 7.6.10 we have
shown that NDB Cluster is the world's fastest Key-Value store using
the Yahoo Cloud Serving Benchmark (YCSB) Workload A.

Presentation at Slideshare.net.

We reached 1.4M operations using 2 Data Nodes and 2.8M operations
using a 4 Data Node setup. All this using a standard JDBC driver.
Obviously using a specialised ClusterJ client will improve performance
further. These benchmarks was executed by Bernd Ocklin.

The benchmark was executed in the Oracle Cloud. Each Data Node used
a Bare Metal Server using DenseIO which have 52 CPU cores with
8 NVMe drives.

The MySQL Servers and Benchmark clients was executed on Bare Metal
servers with 2 MySQL Server per server (1 MySQL Server per …

This blog is the first part of a two-articles series. In this article, I’m going to introduce the Common Table Expression (CTE), a new feature available on MySQL 8.0, as well as Percona Server for MySQL 8.

What is a Common Table Expression?

We can define a CTE as an alternative to a derived table. In a small way, CTE simplifies complex joins and subqueries, improving the readability of the queries. CTE is part of ANSI SQL 99 and was introduced in MySQL 8.0.1. The same feature is available even on Percona Server for MySQL 8.0.

The main reasons for using CTE are:

• Better readability of the queries
• Can be referenced multiple times in the same query
• Improved performance
• A valid alternative to a VIEW, if your user cannot create VIEWs
• Easier chaining of multiple CTE …

Through the courtesy of Intel I have access to a machine with 6 TB of Intel
Optane DC Persistent Memory. This is memory that can be used both as
persistent memory in App Direct Mode or simply used as a very large
DRAM in Memory Mode.

Slides for a presentation of this is available at slideshare.net.

This memory can be bigger than DRAM, but has some different characteristics
compared to DRAM. Due to this different characteristics all accesses to this
memory goes through a cache and here the cache is the entire DRAM in the
machine.

In the test machine there was a 768 GB DRAM acting as a cache for the
6 TB of persistent memory. When a miss happens in the DRAM cache
one has to go towards the persistent memory instead. The persistent memory
has …

As our Percona Kubernetes Operator for Percona XtraDB Cluster gains in popularity, I am getting questions about its performance and how to measure it properly. Sysbench is the most popular tool for database performance evaluation, so let’s review how we can use it with Percona XtraDB Cluster Operator.

Operator Setup

I will assume that you have an operator running (if not, this is the topic for a different post). We have the documentation on how to get it going, and we will start a three-node cluster using the following cr.yaml file:

apiVersion: pxc.percona.com/v1-3-0
kind: PerconaXtraDBCluster
metadata:
  name: cluster1
  finalizers:
    - delete-pxc-pods-in-order
spec:
  secretsName: my-cluster-secrets
  sslSecretName: …

In this tutorial, we'll learn to build an Angular CRUD example from scratch using the latest version which is as the time of this writing Angular 9.

We'll be using a CRUD REST API mocked using json-server which lets you generate a complete working API with nearly zero-lines of code.

We'll not be learning how to use json-server but you can see the complete instructions from this tutorial after generating the Angular project.

Step 1 — Mocking the Backend Using json-server Step 2 — Creating an Angular 9 Module Step 3 — Importing Angular HttpClientModule and FormsModule Step 4 — Creating Angular Component(s) Step 5 — Adding Angular Routing Step 6 — Creating an Angular Service Step 7 — Creating a Model Step 8 — Implementing the CRUD Methods Step 9 — Calling the CRUD Methods

Prerequisites

As always, we'll need to have a few prerequisites for this tutorial:

The basic concepts of …

This is the tutorial and serves as a sample ONLY.  Every environment can be different.  It is a test trial for the Upgrade MySQL InnoDB Cluster with version 5.7.25 to MySQL 8.0.19 where the MySQL InnoDB Cluster Metadata has changed from V1 to V2 in 8.0.19.
1.      Assuming the following SETUP            i.              MySQL Server 5.7.25           ii.              MySQL Shell : 8.0.15         iii.              MySQL Router : 8.0.15 2.      3 nodes are running on the same machine for this tutorial            …

Monitoring is a must in all environments, and databases aren’t the exception. Once you have your database infrastructure up-and-running, you’ll need to keep tabs on what’s happening. Monitoring is a must if you want to be sure everything is going fine but also if you make necessary adjustments while your system grows and evolves. That will enable you to identify trends, plan for upgrades or improvements, or react adequately to any problems or errors that may arise with new versions, different purposes, and so on.

For each database technology, there are different things to monitor. Some of these are specific to the database engine, vendor, or even the particular version that you’re using. Database clusters heavily depend on the underlying infrastructure, so network and operating stats are interesting to see by the database administrators too. 

When running multiple database systems, the monitoring of these systems can …

We know the MySQL Shell is the advanced client tool for communicate to the MySQL server . MySQL Shell has lot of features like InnoDB Cluster control , InnoDB ReplicaSet, MySQL Shell utilities , MySQL server management etc … Today I came to know, MySQL shell helps lot in monitoring as well ( query, threads, resource consumption , locking ) .

In this blog I am going to explain how to use the MySQL Shell for monitor your server .

MySQL Shell provides two hot commands \show and \watch for monitor the MySQL server and report generating purpose .

\show : Execute the report with the provided options

\watch : Execute the report in loop with provided options

\show with thread example :

\show with query example :

You can execute any query within the double quotes .

\show with threads example :