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Analyze Games from European Soccer Leagues with Apache Spark and Databricks

July 9, 2018 by Abhinav Garg and Denny Lee in
Try this notebook series in Databricks Introduction The global sports market is huge, comprised of players, teams, leagues, fan clubs, sponsors, etc., and...

Sharing R Notebooks using RMarkdown

July 6, 2018 by Hanyu Cui and Hossein Falaki in
At Databricks, we are thrilled to announce the integration of RStudio with the Databricks Unified Analytics Platform. You can try it out now...

Build a Mobile Gaming Events Data Pipeline with Databricks Delta

July 2, 2018 by Steven Yu and Denny Lee in
How to build an end-to-end data pipeline with Structured Streaming Try this notebook in Databricks The world of mobile gaming is fast paced...

Announcing RStudio and Databricks Integration

At Databricks, we are thrilled to announce the integration of RStudio with the Databricks Unified Analytics Platform. You can try it out now...

Accelerating Discovery with a Unified Analytics Platform for Genomics

Today we are proud to introduce the Databricks Unified Analytics Platform for Genomics. With a unified platform for genomic data processing, tertiary analytics...

Introducing MLflow: an Open Source Machine Learning Platform

Learn more about Managed MLflow on Databricks Everyone who has tried to do machine learning development knows that it is complex. Beyond the...

Announcing Databricks Runtime for Machine Learning

June 5, 2018 by Paul Ogilvie in
Databricks is thrilled to announce the Databricks Runtime for Machine Learning, including ready-to-use Machine Learning frameworks, simplified distributed training, and GPU Support. Register...

Securely Managing Credentials in Databricks

June 4, 2018 by Eric Wang in
Customers today leverage a variety of data sources to perform complex queries to drive business insight. For example, to better understand user behavior...

Announcing Databricks Runtime 4.1

May 23, 2018 by Cihan Biyikoglu in
We have recently shipped the new Databricks Runtime version 4.1 powered by Apache Spark™. Version 4.1 brings improved performance on read/write from sources...

Introducing Databricks Optimized Autoscaling on Apache Spark™

Databricks is thrilled to announce our new optimized autoscaling feature. The new Apache Spark™-aware resource manager leverages Spark shuffle and executor statistics to...