Join Percona’s, Architect, Manjot Singh as he presents Database Backup and Recovery Best Practices (with a Focus on MySQL) on Thursday, July 27, 2017 at 11:00 am PDT / 2:00 pm EDT (UTC-7).

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In the case of a failure, do you know how long it will take to restore your database? Do you know how old the backup will be? In this presentation, we will cover the basics of best practices for backup, restoration and business continuity. Don’t put your company on the line due to bad data retention and backup policies.

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Embedding Structured Query Language (SQL) within PHP, or other programming languages, has been problematic for some. Mixing two programming languages together is just plainly not aesthetically pleasing. Especially when you have a declarative language (SQL) mixed with a procedural-object oriented language. But now, with the MySQL XDevAPI PECL extension, PHP developers can now stop mixing the two languages together together. MySQL Document StoreThe MySQL Document Store eliminates the heavy burden for SQL skills. It is designed to be a high speed, schema-less data store and is based on the MySQL JSON data type. This gives you roughly a gigabyte of store in a document format to do with as needed. So you do not need to architect you data before hand when you have no idea how it will evolve. No need to normalize your data. Now behind the scenes …

The VideoThe find() function for the MySQL Document Store is a very powerful tool and I have just finished a handy introductory video. By the way -- please let me have feed back on the pace, the background music, the CGI special effects (kidding!), and the amount of the content. The ScriptFor those who want to follow along with the videos, the core examples are below. The first step is to connect to a MySQL server to talk to the world_x schema (Instructions on loading that schema at the first link above).

\connect root@localhost/world_x

db is an object to points to the world_x schema. To find the records in the countryinfo collection, use db.countryinfo.find(). But that returns 237 JSON documents, too many! So lets cut it down to …

I am starting a series of videos on the MySQL Document Store. The Document Store allows those who do not know Structured Query Language (SQL) to use a database without having to know the basics of relational databases, set theory, or data normalization. The goal is to have sort 2-3 minute episodes on the various facets of the Document Store including the basics, using various programming languages (Node.JS, PHP, Python), and materializing free form schemaless, NoSQL data into columns for use with SQL.

The first Episode, Introduction, can be found here.

Please provide feedback and let me know if there are subjects you would want covered in the near future.

Tumblr is a big user of MySQL, and MySQL automation at Tumblr is centered around a tool we built called Jetpants. Jetpants does an incredible job making risky operations safe and reliable, even fairly complex tasks like replacing failed master servers, or splitting a shard.

While Jetpants is an incredibly effective and valuable tool for Tumblr’s day-to-day operation, it has remained very difficult to implement a meaningful testing framework. Integration testing at this level is very challenging. In this article I’ll go through these challenges and how we’ve tackled them at Tumblr.

Requirements

Jetpants operates under the assumption you’re managing MySQL daemons on a fully functional host, and that it can:

• ssh to the target system
• manage processes via service or systemctl commands
• copy data around between systems …

A few weeks ago I started experimenting with MySQL InnoDB cluster. As part of the testing, I tried to kill a node to see what happens to the cluster.

The good news is that the cluster is resilient. When the primary node goes missing, the cluster replaces it immediately, and operations continue. This is one of the features of an High Availability system, but this feature alone does not define the usefulness or the robustness of the system. In one of my previous jobs, I worked at testing a commercial HA system and I've learned a few things about what makes a reliable system.

Armed with this knowledge, I did some more experiments with InnoDB Cluster. The attempt from my previous article had no other expectation than seeing operations continue with ease (primary node …

In this post I will explain how to transfer a multi terabyte size database between two MySQL instances using mydumper, which is a logical backup and restore tool that works in parallel. I will also cover the case where you need to transfer only a subset of data.

Big tables are often problematic because of the amount of time needed to do mysqldump/restore which is single threaded. It is not uncommon for this type of process to take several days.

From MySQL 5.6 and on, we also have transportable tablespaces, but there are some limitations with that approach.

Physical backups (e.g. xtrabackup) have the advantage to be faster, but there are some scenarios where you still need/want a logical backup (e.g migrating to RDS/Aurora/Google Cloud SQL).

Steps Install mydumper/myloader

The first thing …

New MariaDB/MySQL storage engines such as MyRocks and TokuDB have renewed interest in using engines other than InnoDB. This is great, but also presents new challenges. In this article, I will describe work that I am currently finishing, and which addresses one such challenge.

For example, the left bar in the figure shows what happens to MyRocks replication performance when used with a default install where the replication state table uses InnoDB. The middle bar shows the performance improvement from my patch.

Current MariaDB and MySQL replication uses tables to transactionally record the replication state (eg mysql.gtid_slave_pos). When non-InnoDB storage engines are introduced the question becomes: What engine should be used for the replication table? Any choice will penalise other engines heavily by injecting a cross-engine transaction with every replicated change. Unless all tables can be migrated to the …

InnoDB Cluster was released as GA a few weeks ago. I remember the initial announcement of the product at OOW 2016, promising a seamless solution for replication and high availability with great ease of use. I was a bit disappointed to see that, at GA release time, the InnoDB Cluster is a patchwork of three separate products (Group Replication, MySQL Router, MySQL Shell) which the users have to collect and install separately.

Given this situation, I was very pleased when Matthew Lord published Docker-InnoDB-Cluster, an image for Docker that contains everything you need to get the system up and running. The …

In this blog post, we are going to test load balancer solution for MySQL high availability by integrating it with Keepalived, HAProxy, xinetd software components.

High availability databases use an architecture that is designed to continue to function normally even when there are hardware or network failures within the system.

Why we need this?

Let’s take a scenario where we have MySQL Multi-Master / MASTER-SLAVE replication setup for high availability. In the case of Hardware/Network failure on MASTER, In order to failover to a next available server, we need to manually do the configuration changes for client connections.In this case, downtime is expected since manual failover will take some times. To solve this we can integrate load balancer with MySQL to take care of this manual work and do automatic failover connections.

To avoid such downtimes and for the maximum high …