Want to deploy WordPress 5.0 on the Now platform by ZEIT? Our friends over at ZEIT’s Now global serverless deployment platform whipped up a great tutorial for WordPress5-on-Now using cheap MySQL hosting instances from ScaleGrid. With such strong interest in this installation, we decided to write up the steps to configure your MySQL database on the ScaleGrid side to get you up and running ever faster with WordPress on Now.

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@now/wordpress summary:
◆ λ size = 13mb
◆ Just needs `wp-config.php`
◆ All static assets output directly to CDN …

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The slow query log is the trusted old method of recording slow query, so the database administrator can determine which queries are in the most need for optimization. Since MySQL 5.6, it has to some extend been overshadowed by the Performance Schema which has lower overhead and thus allows collecting statistics about all queries. The slow query log has one major advantage though: the data is persisted. In MySQL 8.0.14 which was recently released, there is an improvement for the slow query log: additional statistics about the recorded queries.

The slow query log with log_slow_extra enabled.

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In a MySQL hosting replication setup, the parameter Seconds_Behind_Master (SBM), as displayed by the SHOW SLAVE STATUS command, is commonly used as an indication of the current replication lag of the slave. In this blog post, we examine how to understand and interpret this value in various situations.

Possible Values of  Seconds Behind Master

The value of SBM, as explained in the  MySQL documentation, depends on the state of the MySQL slave in general, and the states of MySQL slave SQL_THREAD and IO_THREAD in particular. While IO_THREAD connects with the master and reads the updates, SQL_THREAD applies these updates on the slave. Let’s examine the possible values of SBM during different states of the MySQL Slave.

When SBM Value is Null

• SBM is …

Partitioning is a process in which a single larger table is split into several smaller tables (physically) and still considered as a single table.It is generally a good idea for the tables whose size is in a few 100 GB’s.

While performing select,update,delete operations in a partitioned tables, we can notice a better performance in queries .This simple process of optimization is called partition pruning in which we can avoid scanning the certain partitions which does not have any matching values based on partition key.

The following example will explain you in detail about the partition pruning

Here I have used an Amazon linux 2 machine

Hardware Info

1 core CPU
1 GB RAM 
20 GB Disk (SSD) 
maximum of 3000 IOPS

MySQL 5.7 is installed in this machine and two tables (one is not partitioned and other is partitioned) with 1.7 million records of  same data is loaded in using …

During our recent consulting with one of our client, We came across an interesting issue on RDS. The baseline is that “Low IO size on your RDS instance can affect your DB performance”.  Yes, It’s IO size, Not IOPS.

We had our production systems running on RDS MySQL with a single master, 3 replicas. All instances are of same type db.m4.4xlarge with same parameter group configuration and the disk size is 1.5 TB. According to the AWS user guide, each of these instances can support up to 4500 (sustained IOPS) guaranteed IOPS.

Find below the Write IOPS graph for all the instances.

It’s understood that Write IOPS / pattern on Master can vary when compared with Slave, due to a lot of factors like binlog row format, log writing etc. But it has to be almost similar for all the slaves given that it …

In Part I, we introduced a High Availability (HA) framework for MySQL hosting and discussed various components and their functionality. Now in Part II, we will discuss the details of MySQL semisynchronous replication and the related configuration settings that help us ensure redundancy and consistency of the data in our HA setup. Make sure to check back in for Part III where we will review various failure scenarios that could arise and the way the framework responds and recovers from these conditions.

What is MySQL Semisynchronous Replication?

Simply put, in a …

We know that MySQL query cache is deprecated as of MySQL 5.7.20 and removed in MySQL 8.0 and It has been recommended to use ProxySQL (or other) external query cache instead.

In this blog post, we’ll present the ProxySQL query cache functionality and how does it help us.

How to setup ProxySQL between client and database servers is out of the scope of this article.

If you are looking for other articles on ProxySQL Series :

• MySQL replication Read-Write Split up
• Replication Switchover using Proxysql And …

As promised, here are slides about MySQL 8.0 Performance from my talks at Oracle Open World 2018 and Percona LIVE Europe 2018 -- all is combined into a single PDF file to give you an overall summary about what we already completed, where we're going in the next updates within our "continuous release", and what kind of performance issues we're digging right now.. ;-))
Also, I'd like to say that both Conferences were simply awesome, and it's great to see a constantly growing level of skills of all MySQL Users attending these Conferences ! -- hope you'll have even more fun with MySQL 8.0 now ;-))

This article is inspired by Percona blog post comparing MySQL 8.0 and Percona Server 5.7 on IO-bound workload with Intel Optane storage. There are several claims made by Vadim based on a single test case, which is simply unfair. So, I'll try to clarify this all based on more test results and more tech details..
But before we start, some intro :
InnoDB Parallel Flushing -- was introduced with MySQL 5.7 (as a single-thread flushing could no more follow), and implemented as dedicated parallel threads (cleaners) which are involved in background once per second to do LRU-driven flushing first (in case there is no more or too low amount of free pages) and then REDO-driven flushing (to flush …

MySQL replication has evolved a lot in 5.6 ,5.7 and 8.0. This presentation focus on the changes made in parallel replication. It covers MySQL 8.0. It was presented at Mydbops database meetup on 04-08-2016 in Bangalore.