Analyzing Apache Access Logs with Databricks
Databricks provides a powerful platform to process, analyze, and visualize big and small data in one place. In this blog, we will illustrate...
New MLlib Algorithms in Apache Spark 1.3: FP-Growth and Power Iteration Clustering
This is a guest blog post from Huawei’s big data global team. Huawei, a Fortune Global 500 private company, has put together a...
The Easiest Way to Run Apache Spark Jobs
Recently, Databricks added a new feature, Jobs, to our cloud service. You can find a detailed overview of this feature here . This...
Celtra Scales Big Data Analysis Projects Six-Fold with Databricks
We are thrilled to announce that Celtra selected Databricks to scale its big data analysis projects, increasing the amount of ad-hoc analysis done...
Running Apache Spark GraphX algorithms on Library of Congress subject heading SKOS
This is a guest post from Bob DuCharme. Original article appeared in: http://www.snee.com/bobdc.blog/2015/04/running-spark-graphx-algorithm.html Well, one algorithm, but a very cool one. Last month...
Deep Dive into Spark SQL's Catalyst Optimizer
Check out the Why the Data Lakehouse is Your Next Data Warehouse ebook to discover the inner workings of the Databricks Lakehouse Platform...
A Look Back at Spark Summit East
We are delighted about the success of the first Spark Summit East , held in New York City on March 18th. The summit...
Timeful Chooses Databricks to Enable Intelligent Time Management
We are thrilled to announce that Timeful chose Databricks to enable intelligent time management with data analytics. Timeful helps its users manage their...
Learning how to write Apache Spark applications in Databricks with the Integrated Search feature
We built Databricks on top of the Apache Spark framework to make data analysis simple. In the same spirit, we want to make...
Apache Spark 2.0: Rearchitecting Spark for Mobile Platforms
Yesterday, to celebrate Apache Spark’s 5 year old birthday, we looked back at the history of the project. Today, we are happy to...