Back in January, Apache Spark was lauded in the ‘InfoWorld Technology of the Year 2015 Awards’ as being the “hands-down the winner in almost every respect” when pitted against traditional Hadoop machine learning models. And its shooting star like trajectory looks set to continue with the release of Spark 1.5 – burning up more of […]

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What’s the latest from Hazelcast? David Brimley and Christoph Engelbert chat to Voxxed about what’s new in version 3.5 of the in-memory data grid, and why they’re working hard on their testing lab. We also discuss how Hazelcast is working with their community to build the next version of the software, and how they hope […]

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Today’s amounts of collected data are showing a nearly exponential growth. More than 75% of all the data have been collected in the past 5 years. To store this data and process it in an appropriate time you need to partition the data and parallelize the processing of reports and analytics. This talk will demonstrate […]

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Today, Java in-memory data grid specialists Hazelcast have announced the release of version 3.5 of their signature offering. The headline feature of this release is the new availability of 100’s of GB of near caching from the Hazelcast High Density Memory Store to clients on a single application server, generating massive application scalability. This adds […]

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Whilst a nice work-life balance is a valuable commodity in itself these days, those solid gold MacBooks and tiger skin hoodies don’t pay for themselves – so it’s useful to know which technology skills you should be channeling your efforts into if you want to rake it in. Luckily job hub Dice.com has just published their […]

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You may have heard a lot about caching, but if you’re not so familiar with the tech behind it, now’s your chance for a quick deep dive. Christoph Engelbert chats to Tonya Rae Moore at DevNexus 2015.

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Scala based Apache Spark may have only graduated from incubator status last February, but in a short space of time, it’s become the most active open source big data project around  – a rise that’s segued with the decline of old faithful tool Hadoop MapReduce. Just this week, Spark was named in the ‘InfoWorld Technology […]

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The original MapReduce paper was pushed out in 2004  by Google – but times have changed. Where does data crunching at Google go from here? In this interview, filmed at Devoxx 2014, Martin Gorner discusses the newly-announced Google Cloud Dataflow product, and how it solves some common data analysis with or without map reduce.

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By Geoffrey De Smet To solve a planning or optimization problem, some solvers tend to scale out poorly: As the problem has more variables and more constraints, they use a lot more RAM memory and CPU power. They can hit hardware memory limits at a few thousand variables and few million constraint matches. One way […]

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A talk given by Neta Barkay at the Underscore meetup on December 23rd, 2013. Underscore is the Israeli Scala user group, join us at: https://groups.google.com/forum/#!forum/underscore-il andhttp://www.meetup.com/underscore/  

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