Contributor: Nick Amato

MapR Converge Blog author, Nick Amato

Nick Amato is Director, Technical Marketing for MapR, focused on creating developer-friendly ways to use the MapR 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.

Blog Posts by Nick Amato

August 29, 2017 | By Nick Amato

Setting up a Multi-Cloud Data Platform

Multi-cloud environments can be an effective way to hedge risk and enable future flexibility for applications. With a secure VPN in between two or more sites, you can leverage the global namespace and high availability features in MapR (like mirroring...

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March 22, 2017 | By Nick Amato

Tensorflow on MapR Tutorial: a Perfect Place to Start

Even if you haven't had a chance to check out TensorFlow in detail, it's clear that your choice of platform has a big impact just as it does for other machine learning frameworks. The adventure from trial to production involves many intermediate...

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October 06, 2016 | By Nick Amato

Connected vs. Converged Big Data Environments | Whiteboard Walkthrough

Nick Amato, Director Technical Marketing at MapR, explains the advantages of a converged environment for streaming applications vs. running these services in separate clusters. Additional resources: Streaming Architecture Ebook Key Requirements for...

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July 14, 2016 | By Nick Amato

Using Spark GraphFrames to Analyze Facebook Connections

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...

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April 20, 2016 | By Nick Amato

Predicting Airbnb Listing Prices with Scikit-Learn and Apache Spark

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...

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April 15, 2016 | By Nick Amato

Using Hive and Pig on Baseball Statistics

The Setup Still using MapReduce? Well, we haven't forgotten about you. In this blog post, we'll tackle one of the challenges of learning Hadoop, and that's finding data sets that are realistic yet large enough to show the advantages of distributed...

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March 03, 2016 | By Nick Amato

Real-Time Can't Just Be Fast, It Also Has to Be Real: An Impressive Streaming Benchmark with ESG

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. The challenges are numerous: every component from the ingest...

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November 10, 2015 | By Nick Amato

Using Amazon AMI Images of MapR Database Document Database Developer Preview to Start Writing JSON-based Applications

MapR Database is a powerful NoSQL database built into the MapR Distribution including Apache Hadoop with a proven record of performance, scale, and reliability. It recently gained document database capabilities with native JSON support, and is now available...

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November 03, 2015 | By Nick Amato

Now You Can Handle Large JSON-based Data Sets in Hadoop or Spark

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...

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June 29, 2015 | By Nick Amato

Using Drill Programmatically from Python, R and Perl

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May 27, 2015 | By Nick Amato

Demo: Apache Spark on MapR with MLlib

Editor's Note: 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 Database for use in Spark and Tableau, and finally...

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May 12, 2015 | By Nick Amato

Classifying Customers with MLlib and Spark

In my last post, I described an example scenario where we used Spark to compute summary statistics on customer data for building a real-time dashboard in Tableau. Our data source derives from a fictional music streaming service where listeners are connecting...

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May 11, 2015 | By Nick Amato

Real-Time User Profiles with Spark, Drill and MapR Database

At MapR we’re big fans of Spark, and every week we see more customers deploying or considering it for analytic workloads using MapR as the platform. Spark is becoming a key enabling technology in a wide variety of use cases across many industries – anything...

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March 11, 2015 | By Nick Amato

Tutorial: Fast Path to an IoT Proof of Concept

In the ever-expanding world of IoT, with so many choices and places to start, it’s easy to get decision paralysis and be distracted by all the options, architectures and platforms. Often, just getting started with an idea and trying a real-world example...

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December 15, 2014 | By Nick Amato

Social Media Analysis with MapR and Splunk Hunk

When you have a high-performance Hadoop cluster there are a lot of very impactful things you can do with it. As a platform for social media analytics, the MapR Distribution makes it easy not only to have a centralized data repository for data flowing...

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December 04, 2014 | By Nick Amato

SQL on Hadoop Demo Video: Using Apache Drill with MicroStrategy Analytics Desktop

The folks over at MicroStrategy have an excellent analytics tool, MicroStrategy Analytics Desktop, that provides fast, powerful analytics on all kinds of data. There are a lot of killer visualizations that let you get the most from all the data you can...

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December 01, 2014 | By Nick Amato

Using SAP Lumira and Apache Drill with Sensor Data - Achieving Simplicity While Embracing Industry Trends

At the recent SAP TechED && d-code event, we were excited to see what SAP is doing in terms of their major initiatives and how SAP (and MapR) will be able to help organizations around the world achieve simplicity while embracing the new trends...

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