MySQL, an open source database developed by Oracle, powers some of Facebook’s most important workloads. We actively develop new features in MySQL to support our evolving requirements. These features change many different areas of MySQL, including client connectors, storage engine, optimizer, and replication. Each new major version of MySQL requires significant time and effort to migrate our workloads. The challenges  include:

• Porting our custom features to the new version
• Ensuring replication is compatible between the major versions
• Minimizing changes needed for existing application queries
• Fixing performance regressions that prevent the server from supporting our workloads

Our last major version upgrade, to MySQL 5.6, took more than a year to roll out. When version 5.7 was released, we were still in the …

With MySQL 8.0, the version of MySQL Database Service aka MDS, the default character set has changed from latin1 to ut8mb4. The default collation is utf8mb4_0900_ai_ci but what does that mean ? and why are the utf8mb4_0900_* the recommended ones ?

Collations like utf8mb4_unicode_520_ci and utf8mb4_0900_ai_ci are based on Unicode Collation Algorithm (UCA). The number in the collation defines the UCA version:

• UCA 9.0.0 (recommended)
  - example: utf8mb4_0900_ai_ci
• UCA 5.2.0 (not recommended, see problems below)
  - example: utf8mb4_unicode_520_ci

The …

MySQL Server 8.0.26 and 5.7.35, new versions of the popular Open Source Database Management System, have been released in conjunction with the 8.0.26 Connector and Component products. 

We are also pleased to announce the release of MySQL Cluster 8.0.26, the latest GA, along with 7.6.19, 7.5.23, 7.4.33. MySQL Cluster is the distributed, shared-nothing variant of MySQL. 

These releases are recommended for use on production systems and are available in source and binary form for a number of platforms from our MySQL Community download pages at:

https://dev.mysql.com/downloads/

Windows packages are available via the Installer for Windows or .ZIP (no-install) packages for more advanced needs. The point and click configuration wizards and all MySQL products are …

    Pandas is a Python software library for data analysis and manipulation.  It allows you to import data from CSV files, SQL, and Excel.  And it is open source.

    Pandas works well with the MySQL Shell.  After installing Pandas with pip install pandas on my Fedora test system, I was able to load Pandas.  The documentation is excellent at pandas.pydata.org   and I was quickly able to get one of their examples working from within mysqlsh.

Did I mention SQL as a source of data? Reading from MySQL is very easy.  

…

This article will show you how to create and manage views in MySQL. A view is a virtual table that does not store its own data but rather displays data that is stored in other tables. Essentially, a view is a result of SQL query execution, which returns the required rows of data from one […]

The post How to Create a View in MySQL appeared first on Devart Blog.

The Problem

State Snapshot Transfer can be a very long and expensive process, depending on the size of your Percona XtraDB Cluster (PXC)/Galera cluster, as well as network and disk bandwidth. There are situations where it is needed though, like after long enough node separation, where the gcache on other members was too small to keep all the needed transactions.

Let’s see how we can avoid SST, yet recover fast and without even the need for doing a full backup from another node.

Below, I will present a simple scenario, where one of the cluster nodes was having a broken network for long enough that it will make …

Problem Statement

Having backups of binary logs is fairly normal these days. The more recent binary logs are copied offsite, the better RPO (Recovery Point Objective) can be achieved. I was asked multiple times recently if something could be done to “stream” the binary logs to S3 as close to real-time as possible. Unfortunately, there is no readily available solution that would do that. Here, I show what can be done and also show a proof of concept implementation, which is not suitable for production use.

In this example, the instance has two binary log files (mysql-bin.000001 and mysql-bin.000002) already closed and mysql-bin.000003 being written. A trivial solution for backing up these binary log files would be to back up just the closed ones (the one that is not written). The default size of the binary log file is 1 GB. This means with this solution we would have a 1 GB binlog not backed up in the worst-case scenario. On …

As some of you likely know, I have a favorable view of ZFS and especially of MySQL on ZFS. As I published a few years ago, the argument for ZFS was less about performance than its useful features like data compression and snapshots. At the time, ZFS was significantly slower than xfs and ext4 except when the L2ARC was used.

Since then, however, ZFS on Linux has progressed a lot and I also learned how to better tune it. Also, I found out the sysbench benchmark I used at the time was not a fair choice since the dataset it generates compresses much less than a realistic one. For all these reasons, I believe that it is time to revisit the performance aspect of MySQL on ZFS.

ZFS Evolution

In 2018, I reported ZFS performance results based on version 0.6.5.6, the default version available in Ubuntu Xenial. The present post is using …

Yesterday my friend and ex-colleague Sveta published a blog post on how to migrate ownership of stored routines, views and triggers in MySQL.

I usually agree a lot with her and even if I agree with what she wrote, there is one single point I would like to comment: use MySQL Shell !

In the blog post, Sveta recommends the use of mysqldump which I don’t. For any logical dump & load operations, I really recommend the use of MySQL Shell’s Dump & Load Utility ! It’s much faster, it has many nice options like hidden Primary Key creation, and is compatible with OCI.

And of course, MySQL Shell also provides …

Benchmarking is a critical technique for delivering high performance software. The basic idea behind benchmarking is measuring and comparing the performance of one software version against another. Over the years, many benchmarking techniques have emerged, but we can broadly separate them into two categories: micro and macro benchmarks. Micro-benchmarks measure a small part of the codebase, usually by isolating a single function call and calling it repeatedly, whereas macro-benchmarks measure the performance of the codebase as a whole and run in an environment similar to what end-users experience.