SparkR Tutorial at useR 2016
AMPLab and Databricks gave a tutorial on SparkR at the useR conference. The conference was held from June 27 - June 30 at...
Apache Spark Key Terms, Explained
This article was originally posted on KDnuggets The Spark Summit Europe call for presentations is open, submit your idea today As observed in...
Approximate Algorithms in Apache Spark: HyperLogLog and Quantiles
Introduction Apache Spark is fast, but applications such as preliminary data exploration need to be even faster and are willing to sacrifice some...
New Content in Databricks Community Edition
At the Spark Summit New York , we announced Databricks Community Edition (CE) beta. CE is a free version of the Databricks service...
The Unreasonable Effectiveness of Deep Learning on Apache Spark
Update: this post is an April Fools joke. It is not an actual project we're working on. For the past three years, our...
Apache Spark Trending in the Stack Overflow Survey
Last week, Stack Overflow released the result of their 2016 developer survey . This is one of the most significant surveys in the...
Apache Spark 2015 Year In Review
To learn more about Apache Spark, attend Spark Summit East in New York in Feb 2016 . 2015 has been a year of...
Introducing Redshift Data Source for Spark
This is a guest blog from Sameer Wadkar, Big Data Architect/Data Scientist at Axiomine. The Spark SQL Data Sources API was introduced in...
Guest blog: PMML Support in Apache Spark's MLlib
This is a guest blog from our friend Vincenzo Selvaggio who contributed this feature. He is a Senior Java Technical Architect and Project...
Announcing Apache Spark Packages
Today, we are happy to announce Apache Spark Packages ( http://spark-packages.org ), a community package index to track the growing number of open source packages and libraries that work with Apache Spark. Spark Packages makes it easy for users to find, discuss, rate, and install packages for any version of Spark, and makes it easy for developers to contribute packages.