When: afternoons of 19 and 20th of October 2017

Where: UNIFR / HEIA-FR

What (in french): Ce workshop organisé par IT-Valley s’adresse à tout informaticien désirant découvrir l’univers du Big Data et de la Data Science. Au programme, deux journées jalonnées d’exercices pratiques autour des technologies Hadoop et des frameworks d’analyse distribués.  Une partie des exercices se feront sur l’infrastructure DAPLAB

Registration:  https://goo.gl/uQD99T

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Thanks to a great team effort, the DAPLAB stack has been updated to the latest version. We are now running HDP 2.6.1 !

The following technologies have also been upgraded in the process:

We hope you will enjoy the new features that are now available,

happy coding !

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We’ll open the room C00.11/15 at Haute Ecole d’Ingénierie et d’Architecture de Fribourg (HEIA-FR) at 5:30pm to give time to warmup our laptops and environments. Signs will be put in place to make your way safely to the room. The official contest starts at 6:30 pm and last for 4 hours. Drinks will be available for participants.

Please reach out in Hipchat or @DAPLABCH for more details. Teams can be formed on Thursday, but you MUST register before Feb 20. Please mention you’ll participate through the Fribourg’s Hub, this will help our logistic!

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Summer is flying. It’s almost dark again outside when it’s Hacky Thursday’s time  

Hence, the menu proposed till the end of the year will be:

(Apache) Streams Processing WTF?

If you ever know the answer of this question, you’re more then welcome to contribute to one or another session

If, like me, you keep stacking articles about these technologies and you promised yourself in your new year resolutions to hack around, it’s not too late to achieve this goal.

In short, we’ll build a use case to try all of these technologies and compare them using requirements we’ll set in advance, such as ramp up time, ease of deploy, integration with YARN, debugging, performance, etc…

We’ll obviously use Kafka as dispatcher, so we’ll dig into Kafka before starting the heavy duty so that everyone is on the same page.

The planning is given below. It might be subject to few changes but you get the main idea.

• September 1: Warm up — use case definition and event generator
• September 8: DAPLAB/iCoSys/eXascale Barbecue
• September 15: Kafka and Kafka internals
• September 22: Spark
• September 29: Flink
• October 6: Apex
• October 13: Kafka Streams
• October 20: Fall’s break
• October 27: Storm
• November 3: Beam
• November 10: Samza
• November 17: Gearpump
• November 24: Ignite
• December 1:Recap. We’ll pick one (called winner below) and spend the December digging deeper into this winner
• December 8: winner 1/2
• December 15: winner 2/2
• December 22: Fondue

If you know one of this technology and like to take ownership of the session, let me know, this would be greatly appreciated.

Last but not least, starting September, companies will have the opportunity to sponsorize the aperos. Please reach out to me if you’re interested or know some companies which might.

Thanks, and see you soon!

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In total, 8 machines with Intel Xeon E5-2630V3 2.40GHZ processors (8 cores) have been incorporated. A special thank you to Christophe Bovigny for the installation and the provisioning of the new machines. Great work !

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DAPLAB has made available the resources needed to create the dataset as well as to perform some of the computations. A great thanks to our collaborators Benoit Perroud and Chistophe Bovigny for their work !

We hope this is just the beginning of fruitful collaborations with external researchers and companies and that our infrastructure will help more researchers in their ground-breaking works.

Taking advantage of the growing amount of structured data produced on the Web is critical for a number of tasks, from identifying tail entities to enriching existing knowledge bases with new properties as they emerge on the Web. While this information has been essentially exploited by commercial companies, it remains an under-explored ground for the research community where several fundamental research challenges arise.

VoldemortKG’s goal is to provide tools, knowledge and models to extract and match structured pieces of data with high confidence in addition to provenance data, which constitutes a playground for researchers interested in a number of tasks including entity disambiguation & linking, entity typing, ad-hoc object retrieval or provenance management.

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DAPLAB actually interested many people who contacted us after the presentation. DAPLAB is indeed offering a good opportunity for SMEs to enter the Big Data and Data Analytics arena.

Extract of what was said during the presentation and Q/A session (in French):

 … DAPLAB est un laboratoire ouvert à toutes les entreprises et chercheurs qui se posent la question du Big Data. Dans ce domaine, le ticket d’entrée est cher, il faut des machines et des experts. Les grands s’y mettent. Nous réduisons la barrière à l’entrée pour les PME. Nous les accompagnons dans l’exploration et la valorisation des données. Le Canton de Fribourg participe au financement …

The post Big Data For SME – Presentation of DAPLAB at the 49es Journées romandes des arts et métiers appeared first on DAPLAB - Data Analysis and Processing Lab.

• We are now safer by occupying two server rooms. In case of fire or cooling defect, we are “room redundant”;
• We can now acquire more capacity – we expect good news in the next few weeks for more storage and more computation power in DAPLAB;
• The network link between the two legs of DAPLAB is not optimal yet (i.e. no fibers). We however fight for it. For now let’s see how Yarn handles this situation and let’s see if our server split was well-thought.

Keep tuned for more news soon.

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The official Apache versions of most HDP 2.4.2 components are unchanged from HDP 2.4.0.0, with the exception of Spark and Kafka. Spark is upgraded from 1.6.0 to 1.6.1; Kafka is upgraded from 0.9.0 to 0.9.0.1.

More info: Hortonworks HDP 2.4.2 release notes

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