Many of you have already heard about NoSQL databases and one of the the most used tool is Memcached, where you add a cache layer between the application and database. Since MySQL version 5.6, a new plugin is available to do the integration between MySQL and Memcached. On this article, we will learn how to install it on linux, and some basic configurations of it.

Pre-requirements:
Install libevent

Installation:
To install memcached support we will need to create a few tables responsible for MySQL and memcached integration. MySQL already includes the file which creates those tables (innodb_memcached_config.sql), you can find this file in a sub folder of your basedir. To discover where is your basedir, run the bellow command:

mysql> SHOW VARIABLES LIKE 'basedir';
+---------------+-------+
| Variable_name | Value |
+---------------+-------+
| basedir       | /usr  | …

Driven by popularity of previous post about Debian/Ubuntu builds of WebScaleSQL and long discussions during FOSDEM conference this weekend, PSCE engineering team decided to put even more effort into.

We would like to introduce:

• RPM packages available for download
• RedHat/CentOS repository

Architectures covered:

• x86 (32-bit)
• x86_64 (64-bit)

Please note that “WebScaleSQL does not currently maintain compatibility for anything except GNU/Linux x86_64.” (WebScaleSQL FAQ)”

RedHat/CentOS releases:

• CentOS 6
• CentOS 7

Packages can be downloaded from …

We have been looking at the WebScaleSQL project with great excitement. As with any new enhancements to the MySQL world, we need to test extensively to ensure we can give PSCE customers the best advice possible. Since this project is source only, we decided to add WebScaleSQL builds to our repo, so we could examine the changes being introduced by all the different collaborators.

So what is WebscaleSQL?

WebScaleSQL is a collaboration among engineers from several companies that face the same challenges in deploying MySQL at scale, and seek greater performance from a database technology tailored for their needs.

— WebScaleSQL, Frequently Asked Questions

What makes this project so special, is the level of collaboration between some of the most …

Long running transactions can be problematic for OLTP workloads, particularly where we would expect most to be completed in less than a second. In some cases a transaction staying open just a few seconds can cause behaviour that is entirely unexpected, with the developers at a loss as to why a transaction remained open. There are a number of ways to find long running transactions, luckily versions of MySQL from 5.6 onwards provide some very insightful instrumentation.

Here we will use the information_schema coupled with the …

Oracle have just made availble the Release Candidate for MySQL Cluster 7.4 (MySQL Cluster 7.4.3) – it can be downloaded from the development release tab here. Note that this is not a GA release and so we wouldn’t recommend using it in production.

The delta between this RC and the 7.4.2 DMR can be viewed in the MySQL Cluster 7.4.3 Release Notes

There are three main focus areas for this RC and the purpose of this post is to briefly introduce them:

• Active-Active (Multi-Master) Replication
• Performance
• Operational improvements (speeding up of restarts; enhanced memory …

The other day a customer asked me to do capacity planning for their web server farm. I was looking at the CPU graph for one of the web servers that had Hyper-threading switched ON and thought to myself: “This must be quite a misleading graph – it shows 30% CPU usage. It can’t really be that this server can handle 3 times more work?”

Or can it?

I decided to do what we usually do in such case – I decided to test it and find out the truth. Turns out – there’s more to it than meets the eye.

How Intel Hyper-Threading works

Before we get to my benchmark results, let’s talk a little bit about hyper-threading. According to Intel, Intel® Hyper-Threading Technology (Intel® HT Technology) uses processor resources more …

TokuDB offers high throughput for write intensive applications, and the throughput scales with the number of concurrent clients.  However, when the binary log is turned on, TokuDB 7.5.2 throughput suffers.  The throughput scaling problem is caused by a poor interaction between the binary log group commit algorithm in MySQL 5.6 and the way TokuDB commits transactions.   TokuDB 7.5.4 for Percona Server 5.6 fixes this problem, and the result is roughly an order of magnitude increase in SysBench throughput for in memory workloads.

MySQL uses two phase commit protocol to synchronize the MySQL binary log with the recovery logs of the storage engines when a transaction commits.  Since fsync’s are used to ensure the durability of the data in the various logs, and fsync’s can be very slow, the fsync can easily become a bottleneck.  A …

One of great innovation in MySQL 5.7 is memory summary tables в Performance Schema and corresponding views in sys schema

And as troubleshooting freak I have huge reason to greet this feature.

Before version 5.7 we had very limited abilities to diagnose memory issues in MySQL. We could use operating system tools, such as vmstat, top, free, but they only showed what MySQL server uses memory, but do not show how. In version 5.7 things changed.

Lets examine what can we study about memory usage by MySQL Server.

At first, this is total amount of memory, used by all internal MySQL structures:

mysql> select * from …

Thanks to everyone who attended and participated in last week’s webinar on 'Galera Cluster for MySQL vs MySQL (NDB) Cluster: A High Level Comparison'. If you missed the sessions or would like to watch the webinar again & browse through the slides, they are now available online.

In this webinar, Severalnines VP of Products, Alex Yu, who was part of the team at Ericsson who originally developed the NDB storage engine in 2001, gave an overview of the two clustering architectures and discussed their respective strengths and weaknesses: 

1. MySQL Cluster architecture: strengths and limitations
2. Galera Architecture: strengths and limitations
3. Deployment scenarios
4. Data migration
5. Read and write workloads (Optimistic/pessimistic locking)
6. WAN/Geographical replication
7. Schema changes
8. Management and monitoring …

In MySQL 5.6 we introduced a huge improvement in the way that index and table statistics are gathered by InnoDB and subsequently used by the Optimizer during query optimization: Persistent Statistics. Some aspects of the way that Persistent Statistics work could be improved further though, and we’d really like your input on that.

How much to sample?

The statistics are gathered by picking some pages semi-randomly, analyzing them, and deriving some conclusions about the entire table and/or index from those analyzed pages. The number of pages sampled can be specified on a per-table basis with the STATS_SAMPLE_PAGES clause. For example:

ALTER TABLE t STATS_SAMPLE_PAGES=500;

This way …