The MySQL Document Store is a NoSQL JSON document store built upon well known MySQL database technology.  PHP runs about eight percent of the Internet.  So putting the two together is a big priority for me. So this blog post is about getting all this together on a Ubuntu 18.04 system.

Note that I will be teaching PHP and the X DevAPI at Oracle Code One and hopefully in some tutorials/workshops this year.  These session will feature the X DevAPI installed on Virtual Box images and I probably will not have time to cover these steps in detail but I will point to this as reference material.


PHP 7.2 PHP's performance has really skyrocketed with the seven series and the newer betas are looking very impressive.  But to use the new X Devapi you will need to get the shared object for it into your PHP server. 

The MySQL X DevAPI PECL Extension
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How To Create Comment Nesting In Laravel From Scratch is the today’s main topic. In any topic specific forum, there is always a structure, where you need to reply to someone’s comment and then somebody reply in their comment and so on. So comment nesting is very useful in any web application, which exposes public interest. In this tutorial, we will do it from scratch. We use Polymorphic relationship in this example.

Create Comment Nesting In Laravel From Scratch

As always, install Laravel using the following command. I am using Laravel Valet.

Step 1: Install and configure Laravel.

laravel new comments

# or

composer create-project laravel/laravel comments --prefer-dist

Go to the project.

cd comments …

Percona announces the release of Percona XtraDB Cluster 5.6.40-26.25 (PXC) on June 20, 2018. Binaries are available from the downloads section or our software repositories.

Percona XtraDB Cluster 5.6.40-26.25 is now the current release, based on the following:

• Percona Server for MySQL 5.6.40
• Galera/Codership WSREP API Release 5.6.39
• Galera Replication library 3.23

All Percona software is open-source and free. …

To quote book of all knowledge:

In cryptography, a brute-force attack consists of an attacker trying many
passwords or passphrases with the hope of eventually guessing correctly.
The attacker systematically checks all possible passwords and passphrases
until the correct one is found.

…

Serverless is a new buzzword in the database industry. Even though it gets tossed around often, there is some confusion about what it really means and how it really works. Serverless architectures rely on third-party Backend as a Service (BaaS) services. They can also include custom code that is run in managed, ephemeral containers on a Functions as a Service (FaaS) platform. In comparison to traditional Platform as a Service (PaaS) server architecture, where you pay a predetermined sum for your instances, serverless applications benefit from reduced costs of operations and lower complexity. They are also considered to be more agile, allowing for reduced engineering efforts.

In reality, there are still servers in a serverless architecture: they are just being used, managed, and maintained outside of the application. But isn’t that a lot like what cloud providers, such as Amazon RDS, Google Cloud, and Microsoft Azure, are already …

Please join Percona’s MySQL Database Administrator, Brad Mickel as he presents How to Analyze and Tune MySQL Queries for Better Performance on Thursday, June 21st, 2018, at 10:00 AM PDT (UTC-7) / 1:00 PM EDT (UTC-4).

Register Now

Query performance is essential in making any application successful. In order to finely tune your queries you first need to understand how MySQL executes them, and what tools are available to help identify problems.

In this session you will learn:

1. The common tools for researching problem queries
2. What an Index is, and why you should use one
3. Index limitations
4. When to rewrite the …

GitHub uses MySQL as its main datastore for all things non-git, and its availability is critical to GitHub’s operation. The site itself, GitHub’s API, authentication and more, all require database access. We run multiple MySQL clusters serving our different services and tasks. Our clusters use classic master-replicas setup, where a single node in a cluster (the master) is able to accept writes. The rest of the cluster nodes (the replicas) asynchronously replay changes from the master and serve our read traffic.

The availability of master nodes is particularly critical. With no master, a cluster cannot accept writes: any writes that need to be persisted cannot be persisted. Any incoming changes such as commits, issues, user creation, reviews, new repositories, etc., would fail.

To support writes we clearly need to have an available writer node, a master of a cluster. But just as important, we need …

\o/ thank you !

RDS is a Database as a Service (DBaaS) that automatically configures and maintains your databases in the AWS cloud. The user has limited power over specific configurations in comparison to running MySQL directly on Elastic Compute Cloud (EC2). But RDS is a convenient service, as long as you can live with the instances and configurations that it offers.

Amazon RDS currently supports various MySQL and MariaDB versions as well as the, MySQL-compatible Amazon Aurora DB engine. It does support replication, but as you may expect from a predefined web console, there are some limitations.

Amazon RDS Services

There are some tradeoffs when using RDS. These may not only affect the way you manage and provision your database instances, but also key things like performance, security, and high availability.

In this blog, we will take a look at the differences between using RDS and running MySQL on EC2, with focus on …

Since MySQL 5.7.5, we have been able to resize dynamically the InnoDB Buffer Pool. This new feature also introduced a new variable — innodb_buffer_pool_chunk_size — which defines the chunk size by which the buffer pool is enlarged or reduced. This variable is not dynamic and if it is incorrectly configured, could lead to undesired situations.

Let’s see first how innodb_buffer_pool_size , innodb_buffer_pool_instances  and innodb_buffer_pool_chunk_size interact:

The buffer pool can hold several instances and each instance is divided into chunks. There is some information that we need to take into account: the number of instances can go from 1 to 64 and the total amount of chunks should not exceed 1000.

So, for a server with 3GB RAM, a buffer pool of 2GB with 8 instances and chunks at default value (128MB) we are going to get 2 chunks per instance:

This means that there will be 16 chunks.

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