Apache Spark - MLlib Introduction

 

In one of our earlier posts we have mentioned that we use Scalding (among others) for writing MR jobs. Scala/Scalding simplifies the implementation of many MR patterns and makes it easy to implement quite complex jobs like machine learning algorithms. Map Reduce is a mature and widely used framework and it is a good choice for processing large amounts of data – but not as great if you’d like to use it for fast iterative algorithms/processing. This is a use case...[More]

Apache Spark on MapR with MLlib

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-DB for use in Spark and Tableau, and finally use MLlib to build ...[more] 

Big Data Ecosystem – Spark and Tableau

 

In this article we give you the big picture of how Big Data fits in your actual BI architecture and how to connect Tableau to Spark to enrich your current BI reports and dashboards with data ...Read More....

Spark After Dark: Real time Advanced Analytics and Machine Learning with Spark