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Shinguz: Bootstrapping Galera Cluster the new way

Taxonomy upgrade extras: galeracluster

A while ago it was pretty inconvenient to start a complete Galera Cluster from scratch. Rolling restart an such things are already working well but bootstrapping was a pain.

With Galera v2.2 new functionality came in. We tried it out and it did not work as documented. :-( Thanks to Teemu's help we found there was a documentation bug in the Galera documentation.

The settings which were working for us are:

wsrep_cluster_address = "gcomm://192.168.1.2,192.168.1.3?pc.wait_prim=no"


And when all 3 nodes of the Galera Cluster are started and …

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MySQL Performance: MySQL 5.6 GA -vs- MySQL 5.5 @32cores

As you already know, MySQL 5.6 GA is announced today and, there is no doubt, it the best ever MySQL release for today!

If you've missed something about a long list of new features coming with MySQL 5.6, I'm inviting you to read excellent summaries written by Rob and Peter, as well many other detailed articles coming this week..

While my story will be, of course, about performance ;-)

I'll present here the results I've obtained on Sysbench workloads (Read-Only and Read-Write) and will update this article with more details along the day (as some other tests are still running)..

For my tests I'm using:

HW Config :

  • Server : 32cores bi-thread (HT) Intel …
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Tungsten University: Configure & provision Continuent Tungsten clusters

Are you unsure of the steps needed to get your Continuent Tungsten cluster up-and-running? In this virtual course, we will teach you how to get from a single database server to a scalable cluster, or from a brittle MySQL replication system to a transparent, manageable Tungsten cluster. 

We will discuss the benefits of leveraging Continuent Tungsten clustering with MySQL, and walk you through the

Galera Load Balancer RPMs

I have created Centos6 RPMs for Codership’s Galera Load Balancer version 0.9.2

License: GPLv2.
Warranty: none at all.

Downloads:
glb-0.9.2-1.x86_64.rpm md5: 49bfb241c6738056f6bf0bce4de6b96b
glb-0.9.2-1.i686.rpm md5: 2491370cb3f78c804831c078250ae611 

Source

Building MySQL 5.6 from source code

MySQl 5.6.10 is easily buildable from source code. In an earilier post I discussed the differences in using pre-packaged builds versus binaries bersus source code and had a few readers ask for details on building from scratch.

Step 1 — Download the source code from http://dev.mysql.com. Once again, you have the options of packages like RPM or a tar ball. In the following steps I usedthe good ol’ tar ball.

You too can build your own MySQL 5.6.10 from source code.

Step 2 — Unpack the downloaded code in the directory of your choice. I used the /usr/local/ of my Centos test server and executed tar xzf /home/dstokes/Downloads/mysql-5.6.10.tar.gz.

Step 3 — Inside /usr/local/mysql-5.6.10 you will find a file …

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SkySQL and MariaDB Announce 2nd Annual MySQL & Cloud Solutions Day, Friday, April 26, 2013

The MySQL & Cloud Solutions Day will take place at the Hyatt Regency Santa Clara, immediately following the Percona Live:  MySQL User Conference & Expo 2013

During this one day event, Monty Widenius and Patrik Sallner, SkySQL CEO, will share insights on the current and future trends pertaining to MySQL, MariaDB 10.0, and the Cloud.  The event will feature two technical tracks:  one focused on the MySQL database and related technologies, and a second on best practices for deploying database applications in the Cloud.  Speakers will also include SkySQL and MariaDB customers, users and partners.



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Introducing Data Fabric Design for Commodity SQL Databases

Data management is undergoing a revolution.  Many businesses now depend on data sets that vastly exceed the capacity of DBMS servers.  Applications operate 24x7 in complex cloud environments using small and relatively unreliable VMs.  Managers need to act on new information from those systems in real-time. Users want constant and speedy access to their data in locations across the planet.

It is tempting to think popular SQL databases like MySQL and PostgreSQL have no place in this new world.  They manage small quantities of data, lack scalability features like parallel query, and have weak availability models.  One reaction is to discard them and adopt alternatives like Cassandra or MongoDB.  Yet open source SQL databases have tremendous strengths:  simplicity, robust transaction support, lightning fast operation, flexible APIs, and broad communities of users familiar with their operation.  The …

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Concurrency Improvements in TokuDB v6.6 (Part 2)

In Part 1, we showed performance results of some of the work that’s gone in to TokuDB v6.6. In this post, we’ll take a closer look at how this happened, on the engineering side, and how to think about the performance characteristics in the new version.

Background

It’s easiest to think about our concurrency changes in terms of a Fractal Tree® index that has nodes like a B-tree index, and buffers on each node that batch changes for the subtree rooted at that node. We have materials that describe this available here, but we can proceed just knowing that:

  1. To inject data into the tree, you need to store a message in a buffer at the root of the tree. These messages are moved down the tree, so you can find messages in all the internal …
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Capturing errors and warnings from LOAD DATA INFILE

MySQL makes it easy to bulk load multiple rows of data from a flat file into a MySQL table using the LOAD DATA INFILE command, but that command can quickly get you into trouble if you are not careful about capturing the warnings and errors it produces.

Running LOAD DATA INFILE commands at the mysql prompt gives you pretty good output, but if you run the same command at the terminal or in a shell script you have to do a little bit of extra work to capture the errors and warnings.

Here are a few techniques I use when I run LOAD DATA INFILE at the terminal or in a shell script:

  1. Use double-verbose mode (--v) to capture the high level counts of Records, Deleted, …
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Capturing errors and warnings from LOAD DATA INFILE

MySQL makes it easy to bulk load multiple rows of data from a flat file into a MySQL table using the LOAD DATA INFILE command, but that command can quickly get you into trouble if you are not careful about capturing the warnings and errors it produces.

Running LOAD DATA INFILE commands at the mysql prompt gives you pretty good output, but if you run the same command at the terminal or in a shell script you have to do a little bit of extra work to capture the errors and warnings.

Here are a few techniques I use when I run LOAD DATA INFILE at the terminal or in a shell script:

  1. Use double-verbose mode (--v) to capture the high level counts of Records, Deleted, …
[Read more]
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