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Showing entries 1 to 10 of 42 10 Older Entries

Displaying posts with tag: ndb (reset)

Webinar Replay & Slides: Performance Tuning of HAProxy for Database Load Balancing
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September 11, 2014 By Severalnines

 

Thanks to everyone who attended and participated in this week’s webinar on ‘Performance Tuning of HAProxy for Database Load Balancing’. And special thanks to our guest speaker, Baptiste Assmann of HAProxy Technologies. 

 

If you missed the sessions or would like to watch the webinar again & browse through the slides, they are now available online.

 

Watch the replay of this webinar to learn about what HAProxy can tell you about your application and database instances. And understand the difference between short-lived connections and

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Putting MySQL Cluster in a container
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To get more familiar with docker and to create a test setup for MySQL Cluster I created docker images for the various components of MySQL Cluster (a.k.a. NDB Cluster)

At first I created a Fedora 20 container and ran all components in one container. That worked and is quite easy to setup. But that's not how one is supposed to use docker.

So I created Dockerfile's for all components and one base image.

The base image:
  • contains the MySQL Cluster software
  • has libaio installed
  • has a mysql user and group 
  • serves as a base for the other images
The management node (ndb_mgmd) image:
  • Has ndb_mgmd as entrypoint
  • Has a config.ini for the cluster








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New Webinar on July 9th: How To Set Up SQL Load Balancing with HAProxy
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June 17, 2014 By Severalnines

 

We continuously see great interest in MySQL load balancing and HAProxy, so we thought it was about time we organised a live webinar on the topic!

 

As most of your will know, database clusters and load balancing go hand in hand. 

 

Once your data is distributed and replicated across multiple database nodes, a load balancing mechanism helps distribute database requests, and gives applications a single database endpoint to connect to. 

 

Instance failures or

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MySQL Cluster on Raspberry Pi - Sub-second failover
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MySQL Cluster claims to achieve sub-second failover without any data loss for commited transactions. And I always wanted to show this in a demo. Now we created that demo finally. See Mark's blog and Keith's blog for setting up MySQL Cluster on RaspberryPi.
The nice thing about the RPis is that you can easily pull the plug to test failover. Ok, that is only one possible failure scenario but for sure the most obvious and more impressive than "kill -9".


That demo application is constantly using the database for storing new lines, removing old lines and reading all line data for the graphical view. There is no caching. It uses JDBC directly.
To document the setup here is the config.ini file




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Ghosts of MySQL Past, Part 8: The First Fork.
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This is the 8th installment in the rather long series that started with Part 1 about a month ago.

Back in 2006, we were in the situation where MySQL 5.0 had taken forever, and the first “GA” release was not suitable for production. Looking towards MySQL 5.1, it was also unlikely to be out any time soon. The MySQL Cluster team had customers that needed new features in a stable release. The majority of users didn’t use the MySQL server at all, they directly used the C++ NDB API for the vast majority of queries – so the vast majority of release blocker bugs in the MySQL server would not affect the production

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Percona XtraDB Cluster – A Drop-in-place Clustering Solution for MySQL
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Emphasis on clustering solutions comes up quite a lot when talking to customers about High Availability. The reason is because clustering is supposed to provide an easier solution for maintaining high availability and so that you do not have to rely on other tools and techniques outside of the database server. I thought it would be good to share the gist of many of my discussions around clustering, in the form of a blog post. So here I will be doing a high-level comparison between MySQL NDB Cluster and Percona XtraDB Cluster.

The post Percona XtraDB Cluster – A Drop-in-place Clustering Solution for MySQL appeared first on ovais.tariq.

High-availability options for MySQL, October 2013 update
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The technologies allowing to build highly-available (HA) MySQL solutions are in constant evolution and they cover very different needs and use cases. In order to help people choose the best HA solution for their needs, we decided, Jay Janssen and I, to publish, on a regular basis (hopefully, this is the first), an update on the most common technologies and their state, with a focus on what type of workloads suite them best. We restricted ourselves to the open source solutions that provide automatic failover. Of course, don’t simply look at the number of Positives/Negatives items, they don’t have the same values. Should you pick any of these technologies, heavy testing is mandatory, HA is never beyond scenario that have been tested.

Percona XtraDB  [Read more...]

The MySQL Cluster storage engine
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This is one close to my heart. I’ve recently written on other storage engines: Where are they now: MySQL Storage EnginesThe MERGE storage engine: not dead, just resting…. or forgotten and The MEMORY storage engine. Today, it’s the turn of MySQL Cluster.

Like InnoDB, MySQL Cluster started outside of MySQL. Those of you paying attention at home may notice a correlation between storage engines not written exclusively for MySQL and being at all successful.

NDB

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NoSQL Memcached API for MySQL: Latest Updates
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With data volumes exploding, it is vital to be able to ingest and query data at high speed. For this reason, MySQL has implemented NoSQL interfaces directly to the InnoDB and MySQL Cluster (http://www.mysql.com/products/cluster/) (NDB) storage engines, which bypass the SQL layer completely. Without SQL parsing and optimization, Key-Value data can be written directly to MySQL tables up to 9x faster, while maintaining ACID guarantees.

In addition, users can continue to run complex queries with SQL across the same data set, providing real-time analytics to the business or anonymizing sensitive data before loading to big data platforms such as Hadoop, while still maintaining all of the advantages of their existing relational database infrastructure.

This and more is discussed in the latest Guide to MySQL and NoSQL

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Some corrections and additions to my simple KVS tests.
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This is the first follow-up to my post on a simple test of KVS alternatives. To recap, I tested a simple single table schema in MySQL using the NDB and InnoDB storage engines. To have a Key-Value store to compare with, I did the same test in MongoDB. All tests were done of the same system, an 8-core AMD Linux box with 16 Gb RAM. The tests consisted of reading 1.000.000 rows, out of the total 105.000.000 in the table, distributed over 100 threads 10 times, a total of 10.000.000 rows read then. The test program I use makes sure that the same random ID's of the table are reused each time and the same are used for all servers.

Now, firstly, after some checking I realized that I had not fully cached the InnoDB engine, so it was doing a

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Showing entries 1 to 10 of 42 10 Older Entries

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