Return to page
h2o_logo h2o_logo
Request Live Demo
On-demand Demos
X

BLOG

In-memory Big Data: Spark + H2O

headshot

By H2O.ai Team | minute read | March 25, 2014

Category: Uncategorized
Blog decorative banner image

Big Data has moved in-memory. Customers using SQL in their Join & Munging efforts via SHARK and Apache Spark need to use Regressions  and Deep Learning. To make their experiences great & seamlessly weave SQL workflows with Data Science  and Machine Learning, we are architecting a simple RDD data import-export in H2O. This brings continuity to their in-memory interactive experience. And support for Spark MLI using our native Scala API – Shalala.
Big Data users can now use SHARK to extract and fuse datasets and H2O for better predictions.

H2O_Spark-800x559 H2O_Spark-800x559 
 hdfs | Spark | SHARK/SQL | RDD | h2o.readRDD() | h2o.deepLearning() | h2o.predict() | h2o.persist(RDD or HDFS)

Calling h2o.deepLearning() from within Scala interface alongside Spark (via Shalala) will make the workflow even more seamless for end users.

Explore similar content by topic

headshot

H2O.ai Team

At H2O.ai, democratizing AI isn’t just an idea. It’s a movement. And that means that it requires action. We started out as a group of like minded individuals in the open source community, collectively driven by the idea that there should be freedom around the creation and use of AI.

Today we have evolved into a global company built by people from a variety of different backgrounds and skill sets, all driven to be part of something greater than ourselves. Our partnerships now extend beyond the open-source community to include business customers, academia, and non-profit organizations.