Arm yourself with the knowledge to employ all of Apache Spark 2.0’s benefits with this collection of technical blogs, talks, and code.
Arm yourself with the knowledge to employ all of Apache Spark 2.0’s benefits with this definitive collection of technical blogs, Spark Summit talks, and sample code, written and presented by leading Spark contributors and members of the Spark PMC.
$1.44 per Terabyte: Setting a New World Record with Apache Spark
Databricks and partners optimized Spark in the cloud to reduce the per-terabyte cost by two-thirds in the CloudSort benchmark.
Databricks Expands Platform for Turnkey Production Apache Spark Deployments
New features enable data engineers to bypass the difficult and tedious tasks of developing, configuring, tuning and securing infrastructure to easily achieve production reliability and security requirements.
Oil and Gas Asset Optimization with AWS Kinesis, RDS, and Databricks
Learn how you can use Databricks alongside AWS Kinesis and RDS to stream sensor readings and detect anomalies in an example Spark application.
HIPAA-Compliant Offering and AWS Public Sector Partner Status
Demand for Apache Spark has surged in regulated industries. For healthcare organizations, Databricks now has a HIPAA-compliant offering; For the public sector, AWS recognized Databricks for its expertise in delivering Spark to support government, education, and nonprofit missions with the Public Sector Partner Status.
Comprehensive Online Guide for Databricks and Apache Spark Launched
Our goal is to create a definitive resource for Databricks users and the most comprehensive set of Apache Spark documentation on the web. The guide includes Spark tutorials and How-Tos, in addition to Databricks product documentation.
How to Make Your Mark as a Woman in Big Data
Databricks Marketing VP Kavitha Mariappan offers five points of advice to women who want to make a mark in big data.
On-Demand Webinar: How to Evaluate Cloud-based Apache Spark Platforms
Nik Rouda, Senior Analyst from ESG Research, presents a comprehensive evaluation framework: defining the evaluation criteria, running a successful proof of concept, and estimating the return on investment.
Apache Spark MLlib 2.x:
Migrating ML Workloads to DataFrames
Apache Spark:
The Unified Engine for All Workloads
Apache Spark News
Scaling Spark in the Real World: Performance and Usability
Apache Spark: A Unified Engine for Big Data Processing
UC Berkeley AMPLab Project Symposium
UC Berkeley AMPLab Project Symposium Videos
Upcoming Apache Spark Events
Dec 6 - Apache Spark: A Deep-dive into Structured Streaming - Lisbon, Portugal
Dec 7 - Performance Improvements to Apache Spark 2.0: 20x SQL Speedup Techniques - New York, NY
Dec 9 - Barcelona Apache Spark Meetup: Deep learning on a mixed cluster w/ Deeplearning4J & Spark - Barcelona, Spain
Dec 17 - Spark Saturday – Hands-on Workshop with Apache Spark 2.x on Databricks - Fremont, CA
Dec 23 - 2nd Annual Kathmandu Meetup: Jumpstart with Apache Spark 2.0 on Databricks - Kathmandu, Nepal
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