Name: Apache Hadoop Contributors Meetup
Start: 2019-01-30T09:00:00-08:00
End: 2019-01-30T17:00:00-08:00
Location: LinkedIn

LinkedIn is pleased to be hosting an all-day meetup event for Hadoop contributors and community members to gather together to share information and insights on the present, past and future of the Hadoop software we all know and love. The day will begin with a series
of presentations on important new features and improvements, followed by breakout discussion sessions on a variety of attendee-driven topics. The target audience is Hadoop contributors, committers, PMC members, and invested members of the community. Topics are generally focused around the future of Hadoop with special focus on scalability and integration with the cloud. Lunch and reception refreshments will be provided.

*** You MUST register in advance by Friday, Jan 25 at lnkd.in/HadoopContributorMeetup2019 in addition to RSVPing on Meetup. Spots are limited and only those who have registered will be allowed to attend. ***

Sessions will be recorded and made public pending approval from individual presenters, but we will not have a live stream available.

The full agenda is as follows:

9:00am - Arrival and check-in
9:30am - TensorFlow on YARN and Beyond [LinkedIn]
10:00am - HDFS Encryption (File & Column) and the Key Management Service [Cloudera/Uber]
10:30am - Break
10:45am - HDFS Scalability & Consistent Reads from an Observer
NameNode [LinkedIn]
11:30am - Router-Based Federation & HDFS Tiered Storage [Uber]
12:15pm - Lunch provided by LinkedIn
1:00pm - HDDS and Ozone [Cloudera]
1:30pm - Dynamometer and a Case Study in NameNode GC [LinkedIn]
2:00pm - Hadoop on Azure [Microsoft]
2:30pm - Mounting Remote Stores in HDFS [Microsoft]
3:00pm - Break
3:15pm - Breakout Sessions
5:00pm - Reception provided by LinkedIn

Breakout session topics will be chosen by attendees. A few suggestions will start as:
Treatment of Java versioning
The right way to handle RPC Encryption
Discussion of community support for a 2.10 bridge release
The future of HDDS & Ozone

Daniel Templeton

Zhe Zhang

Erik Krogen

Apache Hadoop YARN, HDFS & MapReduce Contributors

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Apache Hadoop Contributors Meetup

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Apache Hadoop YARN, HDFS & MapReduce Contributors

Apache Hadoop Contributors Meetup

Apache Hadoop YARN, HDFS & MapReduce Contributors

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