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October 2009

May 2009

March 2009

3D Dewey Visualization : Reza with Processing

by karlcow

For my final project for MAT 259 (Data Visualization) I wanted to explore the topics of 3D Space, particle systems, OpenGL and java, alpha blending, bill boarding, user interactivity, self-organizing algorithms (Kohonen), and electromagnetic attractions and repulsion. The end result is what you see above and below. I used one year of transaction data (books, DVDs, etc) from the Seattle Public Library to drive the visualization. Each particle/sphere is given properties, such as what category/subcategory it represents and how many items where checked out in that category. This is used to drive the physics system that is used to separate the nodes evenly on the surface of the sphere, moreover I wrote a Kohonen-like to cluster the nodes that are related (same category) together. The visualization is interactive; it allows the user to manipulate how they see the data and the properties of the system.

Authentication of viewstate failed

by ms_michel
1) If this is a cluster, edit configuration so all servers use the same validationKey and validation algorithm. AutoGenerate cannot be used in a cluster. 2) Viewstate can only be posted back to the same page. 3) The viewstate for this page might be corrupted.

plists - Google Code

by jpcaruana
plists is a drop-in replacement for the Erlang module lists, making most list operations parallel. It can operate on each element in parallel, for IO-bound operations, on sublists in parallel, for taking advantage of multi-core machines with CPU-bound operations, and across erlang nodes, for parallizing inside a cluster. It handles errors and node failures. It can be configured, tuned, and tweaked to get optimal performance while minimizing overhead.

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February 2009

Lyon veut développer son forum Truck & Bus

by glisseco
Le pôle de compétitivité "Lyon Urban Truck and Bus" a donné naissance à un "cluster" automobile de la région Rhône Alpes.

January 2009

December 2008

severalnines.com

by camel (via)
CMON is a daemon that aggregates information from MySQL Cluster that earlier was only accessible from the cluster log or the management client, such as: * cluster state * node state * backup statistics * statistics * cluster events (cluster log basically) .. and let's you access the information using SQL, because CMON logs the information into ordinary MYISAM tables! So, it is really easy to use! In the package you also get get php scripts that you can put on your webserver to generate graphs and get a www interface to CMON. CMON can also start ndbd nodes and make decisions on how they should be started (with or without --initial). CMON starts as a daemon and will automatically create cmon database and install the necessary tables automatically.

November 2008

Execute commands simultaneously on multiple servers Using PSSH/Cluster SSH/Multixterm -- Ubuntu Geek

by camel
If you have multiple servers with similar or identical configurations (such as nodes in a cluster), it’s often difficult to make sure the contents and configuration of those servers are identical. It’s even more difficult when you need to make configuration modifications from the command line, knowing you’ll have to execute the exact same command on a large number of systems . In this tutorial we will see some tools to execute one command on multiple remote servers using ssh.First you need to make sure you have ssh installed in your machine or you can install using the following command

xen:live-migration_infrastructure [docs]

by camel
In order to be able to do a live migration of a Xen guest from one cluster member to another, some sort of shared storage is required. As the Xen guest won’t run on more than one cluster member at a time, a cluster filesystem is not required. That is, as long as you configure Xen to access the Xen guest by a physical device, not a file.

Tutoriel mysql-proxy rw-splitting Réplication MySQL « Sangokode

by camel & 1 other (via)
Quand un site web dynamique commence à avoir un trafic important, généralement on va essayer de multiplier les serveurs web qui hébergent les fichiers. Multiplier les serveurs web n’est pas le plus difficile, il suffit de faire une réplication des données à chaque mise à jour de votre site et de multiplier les sous-domaines. Les choses se compliquent lorsque vous souhaitez avoir plusieurs serveurs de base de données. La base de données que nous étudierons ici est MySQL. Nous ne parlerons pas de cluster MySQL dans cet article. Le but de l’article est de montrer comment séparer un serveur MySQL en trois serveurs distincts : 1 maitre et deux esclaves, avec un seul point d’entrée (le proxy MySQL). Le proxy devra envoyer les requêtes de lecture vers les serveurs esclaves et toutes les autres requêtes vers le serveur d’écriture.

Linux.com :: Parallel SSH execution and a single shell to control them all

by camel (via)
Many people use SSH to log in to remote machines, copy files around, and perform general system administration. If you want to increase your productivity with SSH, you can try a tool that lets you run commands on more than one remote machine at the same time. Parallel ssh, Cluster SSH, and ClusterIt let you specify commands in a single terminal window and send them to a collection of remote machines where they can be executed. Why you would need a utility like this when, using openSSH, you can create a file containing your commands and use a bash for loop to run it on a list of remote hosts, one at a time? One advantage of a parallel SSH utility is that commands can be run on several hosts at the same time. For a short-running task this might not matter much, but if a task needs an hour to complete and you need to run it on 20 hosts, parallel execution beats serial by a mile. Also, if you want to interactively edit the same file on multiple machines, it might be quicker to use a parallel SSH utility and edit the file on all nodes with vi rather than concoct a script to do the same edit. Many of these parallel SSH tools include support for copying to many hosts at once (a parallel version of scp) or using rsync on a collection of hosts at once. Because the parallel SSH implementations know about all the hosts in a group, some of them also offer the ability to execute a command "on one host" and will work out which host to pick using load balancing. Finally, some parallel SSH projects let you use barriers so that you can execute a collection of commands and explicitly have each node in the group wait until all the nodes have completed a stage before moving on to the next stage of processing.

October 2008

September 2008

XEN Cluster HowTo

by camel
I have tried to run both Debian Etch and Ubuntu 8.04 Server on the cluster nodes, in Dom0. I started my tests with Debian, but I had some issues with slow samba performance in one VM that I couldn't fix so I decided to try Ubuntu Server, for the first time. Both installation went OK, the main difference was that I used mainly source code in Debian, but only packages in Ubuntu. I actually ran into more problems with Ubuntu due to some early bugs in the 8.04 release, will describe them below as I go along. And I have still to prove that running this setup in Ubuntu is stable.

Disco

by greut

Disco is an open-source implementation of the Map-Reduce framework for distributed computing. As the original framework, Disco supports parallel computations over large data sets on unreliable cluster of computers.

The Disco core is written in Erlang, a functional language that is designed for building robust fault-tolerant distributed applications. Users of Disco typically write jobs in Python, which makes it possible to express even complex algorithms or data processing tasks often only in tens of lines of code. This means that you can quickly write scripts to process massive amounts of data.

Disco was started at Nokia Research Center as a lightweight framework for rapid scripting of distributed data processing tasks. This far Disco has been succesfully used, for instance, in parsing and reformatting data, data clustering, probabilistic modelling, data mining, full-text indexing, and log analysis with hundreds of gigabytes of real-world data.

Erlang + Python = complete beautifulness

August 2008

smtp-delay plug-in for qmail

by camel
smtp-delay is an add-on/plug-in intended for use with qmail. It was written primarily to add banner delays and antipipelining to qmail. These two features are known to be able to block certain types of spam and virus mail sent through non-rfc-compliant SMTP engines. When I looked around for programs to add this functionality to qmail, I found only one such program, and didn't like the way it was done. BTW...I have the same objections to the way its done in sendmail 8.13.x. Since banner delays (the server pausing for some time before issuing an SMTP banner) cause every SMTP connection to take longer, I thought it would be a good idea to somehow exempt "legitimate" mail servers...or at least not subject them to long banner delays. So I decided to tune the banner delay time based on the connecting IP's reverse DNS. IPs with no rDNS get treated the worst (longest banner delay). IPs with rDNS matching a regex intended to detect dynamic/end-user IPs get a moderate delay. All other IPs get a very short banner delay...just long enough to see if they immediately pipeline (send SMTP commands before the banner's been sent). The original intent for smtp-delay was that it should be run before rblsmtpd, and simply set the RBLSMTPD environment variable if applicable, letting rblsmtpd issue the 4xx response. Pretty early on, I realized smtp-delay should be able to run standalone (without dependence on rblsmtpd to do its talking) and issue a 4xx response on its own. Lately, the spam load against our mail cluster has gotten so bad that I've started running smtp-delay after rblsmtpd, based on the idea that there's no point waiting out a long banner delay holding an open socket to an IP we have no intention of accepting mail from anyway. This reduced our concurrency by about 20%.

July 2008

OpenNebula :: about

by camel
OpenNebula transforms a physical cluster into a flexible virtual infrastructure which dynamically adapts to the changing demands of a service workload. OpenNebula leverages existing virtualization platforms to create a new virtualization layer between the service and the physical infrastructure. This new layer supports the execution of the services on a physical cluster, extending the benefits of VMMs (Virtual Machine Monitors) from a single physical resource to a cluster of resources. OpenNebula effectively decouples a server (deployed as a pre-configured VM) not only from the physical infrastructure but also from its physical location.

Cool Solutions: Configuring a Xen VM for Live Migration within a Cluster

by camel
By default, migrating a Xen Virtual Machine (VM) resource causes it to shutdown on the current node and restart on the new one. Once you configure a Xen VM within the High Availability Storage Infrastructure (HASI), how do you configure the Xen VM resource to live migrate among the cluster nodes?

June 2008

How To Set Up A Load-Balanced MySQL Cluster With MySQL 5.1 | HowtoForge - Linux Howtos and Tutorials

by camel
This tutorial is based on Falko Timme's tutorial for MySQL Cluster 5.0. It shows how to configure a MySQL 5.1 cluster with five nodes: 1 x management, 2 x storage nodes and 2 x balancer nodes. This cluster is load-balanced by an Ultra Monkey package which provides heartbeat (for checking if the other node is still alive) and ldirectord (to split up the requests to the nodes of the MySQL cluster). In this document I use Debian Etch 4.0 for all nodes. Therefore the setup might differ a bit for other distributions. The two data nodes were x64 to use all of the 8GB RAM. Servers were compiled from source so you should be able to make it running on any platform. The MySQL version I use in this setup is 5.1.24-rc. It's a release candidate, but I wanted to use 5.1 to take advantage of Memory-Disk Based tables. Beginning with MySQL 5.1.6, it is possible to store the non-indexed columns of NDB tables on disk, rather than in RAM as with previous versions of MySQL Cluster.

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