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HPCC Systems blog contributors are engineers and data scientists who for years have enabled LexisNexis customers to use big data to fulfill critical missions, gain competitive advantage, or unearth new discoveries. Check this blog regularly for insights into how HPCC Systems technology can put big data to work for your own organization.

Richard Chapman on 03/02/2017

by Richard Chapman

Richard Chapman on 12/13/2016

TensorFlowTM (see is a new open-source program from Google for performing linear algebra operations on tensors (matrices) and connecting multiple such operations together. It is particularly suited for machine learning applications, and supports operations on GPUs as well as cluster-based operations across multiple machines when dealing with data that is too large for a single machine to handle.

Richard Chapman on 11/23/2016

One downside of using embedded database calls such as MySQL or Cassandra in your ECL code was that specifying the fields to be returned (or passed in, when inserting rows) was a little clunky and potentially inefficient. Projecting fields into EMBEDs makes this process much easier and more efficient in HPCC Systems 6.2.0.

Let's take a step back and review the approach ECL Developers may have been using to date and then take a look at how to use this new feature.

Richard Chapman on 03/16/2016

Recently, the HPCC platform team held one of our offsite conferences, which usually involves us disappearing into the wilderness somewhere for a week. So, leaving the day to day pressures behind, we all decamped to a remote cottage in the frozen North of England to discuss how to improve HPCC Systems as well as future development plans. Something unusual often comes out of these gatherings and this was no exception.

Richard Chapman on 10/26/2015

If you are an ECL programmer, there are a lot of things you don’t need to worry about that programmers in low level languages like C or C++ need to think about: