MySQL Group Replication is here and with it comes the need to install and configure the underlying group communication toolkit that supports it: Corosync. Corosync is a well known and reliable Group Communication System that is used in such applications as Pacemaker.

In term of support, we develop MySQL Group Replication based on Corosync version 1.4.6, so this tutorial is based on this version. Regardless of this, no known problems are know to exists when using newer versions, but no extensive testing has been done on those.

Along with Corosync we also encourage the use of NSS to better secure your data that is transmitted in the group.

Installing

To install Corosync, you can rely on your packet manager for most distributions or compile it from source.

==> From the package manager

• Debian distributions

$ sudo apt-get install corosync …

The new addition to the MySQL planet, MySQL Group Replication is now on Labs Release for you to try it! It offers you update everywhere capabilities on any group of normal, out of the box, MySQL servers. Concurrent updates on a setup of several MySQL servers is now possible and this with our trademark: the ease of use.

In fact we ship MySQL Group Replication in such a way that for you to form a group and add new nodes, all that is needed is to configure the servers with your unique group id and just press start. In this post we show you the “behind the scenes” of this process, on how the node catches up with the remaining servers through distributed recovery.

The basics about Distributed Recovery

If we were to summarize what distributed recovery is, we could describe it as the process through which a new server gets missing data from a live node, while paying attention to what happens in the group, eventually catching …

Introduction

The multi master plugin for MySQL is here. MySQL Group Replication ensures virtually synchronous updates on any node in a group of MySQL servers, with conflict handling and failure detection. Distributed recovery is also in the package to ease the process of adding new nodes.

For a better understanding on how things work, we go under the hood in this post and you will have a better understanding about the communication layer functionality and implementation.

Group Communication concepts Figure 1 – Plugin Architecture

As the architecture shown in Figure 1, Group Replication is a classic modular and layered piece of software and the bottom two layers comprise the communication module. But, it is not a regular …

The first preview  release of MySQL Group Replication, a MySQL plugin that brings multi-master update everywhere to MySQL, is available on labs. This plugin ties together concepts and technologies from distributed systems, such as group communication, with traditional database replication. The ultimate result is a seamlessly distributed and replicated database over a set of MySQL servers cooperating together to keep the replicated state strongly consistent.

Introduction

Before diving into the details of MySQL Group Replication, lets first introduce some background concepts and an overview of how things work. These will provide some context to help understand what this is all about and what are the differences between traditional MySQL replication and the one implemented in this new plugin.

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Both MySQL Connector/Python 2.0.1 and 1.2.3 are now available through the Python Package Index or PyPI. Leaving the previous version available is probably a good idea as you can always go back if needed.

Note that we still have no files hosted at PyPI.

Both MySQL Connector/Python 2.0.1 and 1.2.3 are now available through the Python Package Index or PyPI. Leaving the previous version available is probably a good idea as you can always go back if needed.

Note that we still have no files hosted at PyPI.

In a previous blog post we presented some of the issues with the current optimizer cost model and listed several ideas for improvements. The new 5.7.5 DMR contains the result of our initial work on improving the optimizer’s cost model:

• Cost Model for WHERE Conditions. In previous versions of MySQL, the estimated number of rows from a table that will be joined with the next table only takes into account the conditions used by the access method. This often led to record estimates that were far too high and thus to a very wrong cost estimate for the join. With wrong cost estimates, the join optimizer might not find and choose the best join order. To solve this issue, a cost model that includes the …

Indeed, MySQL 5.7 rocks ;-)

This is the part1 of the following blog posts about various benchmark results on MySQL 5.7 - and this particular one is dedicated to the Sysbench OLTP_RO Point-Select 8-tables workload.

We've already published the over 500K QPS on SQL Point-Selects before @32cores-HT server, so may reconfirm it again with MySQL 5.7 DMR5 -vs- other engines :


and now on a similar server, but with 40cores-HT we're able to confirm 645 QPS on the same workload!

If you missed the long story about how we arrived on such a performance level and how to reproduce the test - you may find all here. This workload is the most killing from all Read-Only Sysbench OLTP tests.. And it's really for the first time we started to scale here with MySQL! …

In this third installment in this series, I'll explain why the smart solution I described in the previous post actually wasn't that good, and then I go on to explain how to fix it, and why that fix wasn't such a smart thing after all. So, this was the design we ended with last time:
We have Oracle replicating to a Materialized View, this to ensure that we can run triggers when the is a commit, and then triggers on this Materialized View updates MariaDB by sending a UDP message to a server that in turn is connected to MariaDB.

The issue with the above thingy was that a Materialized View by default is refreshed in it's entirety when there is a refresh, so if the table has 10.000 rows and 1 …

Business Wire  Oracle Open World 2014, Booth # 430- Continuent, Inc., a leading provider of open source database clustering and replication solutions, today announced Continuent Tungsten 3.0, a powerful solution that combines advanced clustering and replication technologies to meet the transaction processing and analytic needs of the entire business. Continuent Tungsten 3.0 enables constant,