Featured Author

Nick Amato
Director Technical Marketing, MapR

Nick Amato is Director, Technical Marketing for MapR, focused on creating developer-friendly ways to use the MapR Converged Data Platform. Nick's background includes prior technical leadership roles at Riverbed and Cisco, and over 15 years of experience in developing, deploying and benchmarking enterprise software.

Author's Posts

Posted on October 6, 2016 by Nick Amato

In this week's whiteboard walkthrough, Nick Amato, Director Technical Marketing at MapR, explains the advantages of a publish-subscribe model for real-time data streams.

Posted on July 14, 2016 by Nick Amato

Sooner or later, if you eyeball enough data sets, you will encounter some that look like a graph, or are best represented a graph. Whether it's social media, computer networks, or interactions between machines, graph representations are often a straightforward choice for representing relationships among one or more entities.

Posted on May 4, 2016 by Nick Amato

If you’ve had a chance to work with Hadoop or Spark a little, you probably already know that HDFS doesn't support full random read-writes or many other capabilities typically required in a production-ready file system.

Posted on April 20, 2016 by Nick Amato

One of the most useful things to do with machine learning is inform assumptions about customer behaviors. This has a wide variety of applications: everything from helping customers make superior choices (and often, more profitable ones), making them contagiously happy about your business, and building loyalty over time.

Posted on March 3, 2016 by Nick Amato

Moving a data analysis platform from a “submit the job and wait” model to a “make things happen in real-time” one isn’t easy. If it were, the world wouldn’t spend so much time talking about it.

Posted on November 10, 2015 by Nick Amato

This blog describes how to get an instance of the MapR-DB Document Database Developer Preview image running on Amazon AWS using one of the pre-configured AMI images supplied by MapR. With this AMI, you can start writing JSON-based applications on MapR-DB using the open source Open JSON Application Interface, or OJAI.

Posted on November 3, 2015 by Nick Amato

Handling large JSON-based data sets in Hadoop or Spark can be a project unto itself. Endless hours toiling away into obscurity with complicated transformations, extractions, handling the nuances of database connectors, and flattening ‘till the cows come home is the name of the game.

Posted on June 29, 2015 by Nick Amato

Drill offers life-changing ways to simplify connecting to Hadoop-scale data in an application or script. OK, maybe not life-changing, but still pretty cool. In this post we will look at how to do it in your language of choice.

Posted on May 27, 2015 by Nick Amato

In this demo we are using Spark and PySpark to process and analyze the data set, calculate aggregate statistics about the user base in a PySpark script, persist all of that back into MapR-DB for use in Spark and Tableau, and finally use MLlib to build logistic regression models.

Posted on May 12, 2015 by Nick Amato

In this post, I’ll give an example of how we can make predictions that enable us to maximize revenue and ensure the best customer experience. We'll do this using the output of the Spark code from our last adventure.


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