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  1. DZone
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  4. Hortonworks Announcements: April 2016

Hortonworks Announcements: April 2016

Announcements and news from Hortonworks from the European Hadoop Summit.

Tim Spann user avatar by
Tim Spann
CORE ·
Apr. 14, 16 · News
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Hortonworks has released a flurry of amazing announcements coming out of Hadoop Summit in Europe.

Hadoop, Data Lakes, and Building a Next Gen Big Data Architecture

(Link)

Hortonworks will resell Syncsort DMX-h for data integration and is deployable by Ambari. For more information, read here. This will help bring enterprise tools to enterprises. 

Apache Spark and Apache Zeppelin: What's Coming In HDP 2.4.2

(Link)

The HDP maintenance release will include the latest Spark (1.6.1) and will deliver some important feature.

  • Certified SparkSQL With ODBC (ODBC Driver Available From Hortonworks).
  • Bug Fixes In Spark Oozie Action For A Kerberos Enabled Cluster.
  • Spark Streaming With Apache Kafka Support In A Kerberos Enabled Cluster.
  • SparkSQL & ORC Performance Improvements.
  • Final Technical Preview Of Apache Zeppelin That Includes Kerberos Support, LDAP Authentication, And Identity Propagation.

Hortonworks is working with the community on the release of Spark 2.0. For Zeppelin, Git support will be added for sharing notebooks!

Announcing CloudBreak 1.2

(Link) (Docs)

CloudBreak brings cluster auto-scaling, support for the Cloud Providers (AWS, Azure, Google, OpenStack) and is built on Docker, Ambari, Swarm and Consul. This brings some awesome DevOps to a cloud hosted Big Data platform.

Credit Card Fraud Prevention on a Connected Data Platform

(Link) (Code)

Utilizing Hortonworks Connected Data Platform allows enterprises to curate real-time data, end-to-end security, data traceability, provide a centralized architecture for applications with strong support for enterprise operations. At the summit Hortonworks will demo how HDP can help prevent credit card fraud. Using Zeppelin, developers, engineers, data scientists and users alike can run queries, create visualizations and analyze the data in a comfortable UI. The demo utilizes Apache Storm, Java, Kafka, HDFS, Apache NiFi (HDF), Ambari, and Docker.

Big data Data science Docker (software) kafka

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