Read Rise of the Data Lakehouse to explore why lakehouses are the data architecture of the future with the father of the data...

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.

We at Databricks are thrilled to announce the release of Apache Spark 1.2! Apache Spark 1.2 introduces many new features along with scalability...

A month ago, we shared with you our entry to the 2014 Gray Sort competition, a 3rd-party benchmark measuring how fast a system...

Our friends at Twitter have contributed to MLlib, and this post uses material from Twitter’s description of its open-source contribution , with permission...

Update November 5, 2014 : Our benchmark entry has been reviewed by the benchmark committee and Apache Spark has won the Daytona GraySort...

The brain is the most complicated organ of the body, and probably one of the most complicated structures in the universe. It’s millions...

With an ever-growing community, Apache Spark has had it’s 1.1 release . MLlib has had its fair share of contributions and now supports...

This is a guest post by Nick Pentreath of Graphflow and Kan Zhang of IBM , who contributed Python input/output format support to Apache Spark 1.1. Two powerful features of Apache Spark include its native APIs provided in Scala, Java and Python, and its compatibility with any Hadoop-based input or output source. This language support means that users can quickly become proficient in the use of Spark even without experience in Scala, and furthermore can leverag