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Michael Hausenblas in Large-scale Data Processing

Feb 8, 2015

How to kick-start Spark development on IntelliJ IDEA in 4 steps

2 responses

Michael Hausenblas in Large-scale Data Processing

Apr 18, 2013

Google Omega

Just recently, I stumbled upon a new Google paper—Omega: ﬂexible, scalable schedulers for large compute clusters, published these days at the EuroSys 2013.

This contribution is, after GFS/MapReduce, Dremel, Percolator, Pregel and only last year Spanner maybe one of the most…

Sqrrl

Mar 24, 2014

What are Iterators in Accumulo?

The “cell-level secure” database system has some interesting quirks…

Michael Hausenblas in I. M. H. O.

Aug 21, 2013

Sensors: primary source of Big Data

How the Internet of Things/M2M/the Programmable Web will require us to think differently about processing data.

Michael Hausenblas in Applying the Lambda Architecture

Dec 30, 2013

Google Cloud Computing

It is end of 2013 and here I’m looking back at the year and what has happened…

Michael Hausenblas in Large-scale Data Processing

May 27, 2013

Dataspaces have arrived

It took less than 10 years to deliver on Alon Halevy’s vision.

Michael Hausenblas in Large-scale Data Processing

May 22, 2013

Serendipity

Serendipitous discovery in distributed real-time query engine development.CERN team deserves attention and credits.

Due to a sheer coincidence I got in touch with Fons Rademakers, a very interesting chap…

Michael Hausenblas in Large-scale Data Processing

May 7, 2013

On infrastructures and applications

What do roads & cars, the electricity grid & TVs, the Internet &…

Michael Hausenblas in Large-scale Data Processing

May 20, 2013

Ubi fumus, ibi ignis.

Thoughts on TCO of data-driven business decisions.

Michael Hausenblas in I. M. H. O.

Oct 31, 2013

JAX London rocks!

Hint: it’s not all about Java and Big Data played a big role.

These were the top 10 stories published by Large-scale Data Processing; you can also dive into yearly archives: 2013, 2014, and 2015.

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Large-scale Data Processing

Experiences with, stories about and insights from using frameworks for large-scale data processing and distributed applications: incl. but not limited to Hadoop, HBase, Storm, Drill, Spark, Mesos, YARN, Myriad, etc.

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Michael Hausenblas