Databricks Bi-Weekly Digest: 7/18/16

Today, we're kicking off a new series: the Databricks Bi-Weekly Digest. Our goal with this digest is to summarize Spark related content, compiled by Databricks, for the community. It will cover Spark technical content: blog posts, meetups tech-talks, conference talks, and noteworthy news articles pertaining to Apache Spark.

Here’s what’s happened in the last two weeks:

• A hands on Tutorial how to use SparkR presented at the useR 2016 conference: SparkR Tutorials at useR 2016. Peruse through presentations and try the Notebooks in Databricks.
• Vote for Apache Spark 2.0 RC4 Update from Reynold Xin is underway.
• JIRAs closed:
  • Experimental support for Kafka 0.10 in Spark 2.0
• Want to be heard, want to share your thoughts? Please take our Databricks 2016 Apache Spark Survey and make a difference.
• Tim Hunter presented Combining Machine Learning Frameworks with Apache Spark at the Hadoop Summit.
• Databricks released Stanford CoreNLP wrapper for Apache Spark with an example notebook. Try it on Databricks.
• Joseph Bradley spoke at the NYC Spark Meetup: Distributed ML in Apache Spark Meetup Tech Talk. Learn about DataFrames in MLlib.
• A blog explained A Tale of Three Apache Spark APIs: RDDs, DataFrames, and Datasets. Find out when to use which API and why.
• Three Apache Spark related tech-talks presented at Bay Area Apache Spark Meetup Tech-Talks @ SAP. You can watch the video on YouTube.

What’s Next?

To stay abreast with what’s happening with Apache Spark follow us on Twitter @databricks and visit sparkhub.databricks.com.