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LexisNexis Risk Solutions and the open source HPCC Systems platform have hit another milestone – we are celebrating our 6th Anniversary!  It was way back in 2011 when we decided to open the platform up to the broader open source community for further development, more widespread use and to tap into the continuous innovation that open source brings into any technology.  Our goal was to make big data analytics more accessible to organizations of all sizes, by sharing with them the home grown and proven solution that we have been developing and using for more than 15 years.  Over the years, our commitment to that goal has not waivered and we continue to make it easy for developers and end users to tackle big data problems.

Today, I am pleased to announce two new and exciting events – the recent launch of the new HPCC Systems website and the upcoming HPCC Systems 6.4.0 release!

On June 2nd, we launched our new and improved website, which showcases a fresh, updated look and improved content organization. The new open source portal makes navigation easier and features enhanced download capabilities to help users quickly get to the files that they need, combined with a flexible design that can be used on mobile devices and tablets.

The packaged version of the latest platform release candidate for HPCC Systems 6.4.0, is available for you to download now, along with the latest release notes and the GitHub repository has been tagged for 6.4.0 too. Testing will continue over the next few weeks while we move towards taking it gold. Linux users should note that we have added Ubuntu 17.04 to the list of distros that we now support. This release includes several new features and a number of enhancements that will improve the overall performance of the platform, particularly in ROXIE.

Our Machine Learning Library is experiencing a complete restructuring as we group together similar algorithms into bundles. We are very pleased to announce that HPCC Systems 6.4.0 includes the first two new bundles, for Logistic Regression and Linear Regression. There is also a new full performance test suite for PBblas.  Find out more about our Machine Learning Library restructuring which will be continuing for the rest of 2017 and through 2018, with more blogs to follow. Stay tuned!

If you use our ECL IDE to write your ECL code, you will notice that we have added some cool new usability features. Your repository list, for example, will now indicate types of files more clearly and we have added iconization and colorization for different file types. There are also good news for KEL and HIPIE users, because ECL IDE has been enhanced with extended syntax highlighting for both these languages. 

On a related topic, frequent users of the EMBED feature, can now take advantage of the easier install process for the R embed feature, as well as the new scoping rules added for this language, which allow you to use data from one call within another in a way similar to the Python embed feature. While we are on the subject of Python, we now also support Python 3 as an embedded language.

If you haven’t already, I recommend that you read Richard Chapman’s blog post about File Layout Resolution at Compile Time. It illustrates how to use this new 6.4.0 feature which makes it seamless to deal with data layout changes in your HPCC Systems environments.

Of course, this is just a small subset of the new and enhanced capabilities shipping in 6.4.0. If you want to know more, please take a look at this list of notable fixes and the list of completed headline items on the HPCC Systems Roadmap.

The HPCC Systems open source community is active and vibrant because of every one of us (and especially you). And while we are at it, we’d like to hear from anyone who wants to get involved, whether you are an experienced user or just getting started. Post a comment in our forum if you have a question or comment and if you have something you want to contribute, all the better, this being code, documentation, experiences or anything else that could be of value to others!

I would like to wish everyone in our HPCC Systems open source community a very Happy Anniversary!  Our future looks bright and we will continue to work hard to help you with your big data needs.