Hadoop Crash Course

Apache Hadoop Crash Course

Introduction: This workshop will provide a hands on introduction to Apache Hadoop using the HDP Sandbox on students’ personal machines.
Format: A short introductory lecture about Apache Hadoop and a few key additional Apache projects in the extended ecosystem used in the lab followed by a demo, lab exercises and a Q&A session.
Objective: To provide a quick and short hands-on introduction to Hadoop. This lab will use the following Hadoop components: HDFS, YARN, Pig, Hive, Spark, and Ambari User Views. You will learn how to move data into HDFS, explore the data, clean the data, issue SQL queries and then build a report with Zeppelin.
Pre-requisites: Registrants will receive an email one week before the event on prerequisites and lab setup. You must bring a machine that can run the Hortonworks Sandbox.
Seating is limited for these sessions. Register now.

Apache Spark Crash Course

Introduction: This workshop will provide a hands on introduction to Apache Spark using the HDP Sandbox on students’ personal machines.
Format: A short introductory lecture about Apache Spark components used in the lab followed by a demo, lab exercises and a Q&A session. The lecture will be followed by lab time to work through the lab exercises and ask questions.
Objective: To provide a quick and short hands-on introduction to Apache Spark. This lab will use the following Spark and Hadoop components: Spark, Spark SQL, HDFS, YARN, ORC, and Ambari User Views. You will learn how to move data into HDFS using Spark APIs, create Hive tables, explore the data with Spark and Spark SQL, transform the data and then issue some SQL queries.
Pre-requisites: Registrants will receive an email one week before the event on prerequisites and lab setup. You must bring a machine that can run the Hortonworks Sandbox.
Seating is limited for these sessions. Register now.

Apache Nifi Crash Course

Introduction: This workshop will provide a hands on introduction to simple event data processing and data distribution using a Sandbox on students’ personal machines.
Format: A short introductory lecture to Apache NiFi computing used in the lab followed by a demo, lab exercises and a Q&A session. The lecture will be followed by lab time to work through the lab exercises and ask questions.
Objective: To provide a quick and short hands-on introduction to Apache NiFi. In the lab, you will install and use Apache NiFi to collect, conduct and curate data-in-motion and data-at-rest with NiFi. You will learn how to connect and consume streaming sensor data, filter and transform the data and persist to multiple data sources.
Pre-requisites: Registrants will receive an email one week before the event on prerequisites and lab setup. You must bring a machine that can run the Hortonworks Sandbox.
Seating is limited for these sessions. Register now.

Internet of Things Crash Course

Introduction: This workshop will provide a hands on introduction to the Hadoop stack powering the Internet of Things (IoT) using a Sandbox on students’ personal machines.
Format: A short introductory lecture about IoT components used in the lab followed by a demo, lab exercises and a Q&A session. The lecture will be followed by lab time to work through the lab exercises and ask questions.
Objective: To provide a quick and short hands-on introduction to IoT. In the lab, you will use the following IoT components: NiFi, Storm, Kafka, HDFS, Hive, HBase. You will learn how to consume streaming sensor data into HDFS, explore the data, apply real time processing to streaming data and then issue some SQL queries to analyze historical data.
Pre-requisites: Registrants will receive an email one week before the event on prerequisites and lab setup. You must bring a machine that can run the Hortonworks Sandbox.
Seating is limited for these sessions. Register now.

Data Science Crash Course

Introduction: This workshop will provide a hands on introduction to basic Machine Learning techniques with Spark ML using a Sandbox on students’ personal machines.
Format: A short introductory lecture on a select important supervised and unsupervised Machine Learning techniques followed by a demo, lab exercises and a Q&A session. The lecture will be followed by lab time to work through the lab exercises and ask questions.
Objective: To provide a quick and short hands-on introduction to Machine Learning with Spark ML. In the lab, you will use the following components: Apache Zeppelin (a "Modern Data Science Toolbox") and Apache Spark. You will learn how to analyze the data, structure the data, train Machine Learning models and apply them to answer real-world questions.
Pre-requisites: Registrants will receive an email one week before the event on prerequisites and lab setup. You must bring a machine that can run the Hortonworks Sandbox.
Seating is limited for these sessions. Register now.

MeetUps

Fremont Big Data and Cloud Meetup
Title: IoT for Big Machines
Speaker: Jayant Thomas - Sr.Engineering Manager for the Predix Apps - GE
Registration Link: http://www.meetup.com/datariders/events/230919430/
Room: LL21F


Apache NiFi Users Group - DC VA MD
Title: Apache NiFi: Knack Over Flow
Speaker: Aldrin Piri - PMC Member, Apache NiFi
Title: The Thing About Protecting Data Is, You Have To Protect Data
Speaker: Andy LoPresto – Software Engineer, Hortonworks
Registration Link: http://www.meetup.com/ApacheNiFi/events/231191180/
Room: LL20D


Big Data Science
Title: Mathematics to converge IoT, Cloud and Big Data
Speaker: Ted Dunning - Chief Application Architect, MapR
Registration Link: http://www.meetup.com/Big-Data-Science/events/227573002/
Room: LL21C

Bay Area Apache Flink Meetup
Title: Robust Stateful Stream Processing with Apache Flink
Speaker: Jamie Grier - Director of Applications Engineering, data Artisans
Registration Link: http://www.meetup.com/Bay-Area-Apache-Flink-Meetup/events/231347668/
Room: LL21E


Accumulo-Users-DC
Title: Apache Accumulo 1.8 Overview
Speaker: Josh Elser - Senior Software Enginner, Hortonworks
Registration Link: http://www.meetup.com/Accumulo-Users-DC/events/231397927/
Room: LL21D


Intuit Meetup
Title: Scaling Innovation with A|B Testing at Intuit @ Hadoop Summit
Registration Link: http://www.meetup.com/A-B-Testing-Meetup/events/231545028/
Room: LL20A

Apache Ambari User Group
Title: Apache Ambari
Speaker: Yusaku Sako - Sr.Engineering Manager - Hortonworks
Registration Link: http://www.meetup.com/Apache-Ambari-User-Group/events/231576067/
Room: LL20C

Birds of a Feather Sessions

Hortonworks will sponsor several Birds of Feather (BoFs) sessions, hosted by Apache Committers, Hortonworks' architects, tech-leads, and engineers. Come share your experiences, challenges, interests and requirements on key Apache projects. And discuss what's on the roadmap and future design options. These sessions are not restricted to conference attendees; they're open to everyone.

Date: Thursday June 30, 2016
Time: 5:00pm - 7:00pm
Venue: San Jose Convention Center


Topic: Apache Spark, Apache Zeppelin & Data Science
Apache Spark is a fast, in-memory data processing engine with elegant and expressive development APIs to allow data workers to efficiently execute streaming, machine learning or SQL workloads that require fast iterative access to datasets. Come learn and discuss Spark and Data Science innovations and future directions.
Hosts: Owen O’Malley (Hadoop Committer), Vinay Shukla (Hortonworks Product Manager), Bikas Saha (Hadoop & Tez Committer) and Robert Hryniewicz (Hortonworks Data Science Advocate)
Room: Ballroom A

Topic: Apache Hive & Apache Pig
Hive is the de facto standard for SQL queries in Hadoop. The next phase of the Stinger. next initiative, the Apache community has greatly improved Hive’s speed, scale and SQL semantics. Come learn and discuss Hive 2.0.
Apache Pig is a robust and mature data processing engine that continues to evolve. Come learn about the latest developments.
Hosts: Alan Gates (Hive Committer), Carter Shanklin (Hortonworks Product Manager), Daniel Dai (Pig Committer) and Gopal Vijayaraghavan (Hive Committer)
Room: 210C


Topic: Cloud & Operations
Apache Ambari is a completely open source management platform for provisioning, managing, monitoring and securing Apache Hadoop clusters. Cloudbreak facilitates provisioning Hadoop in the cloud. Apache Oozie is a workflow scheduler for Hadoop.
Come learn and discuss the latest cloud & operations innovations and future directions.
Hosts: Tim Hall (Hortonworks Product Manager), Ram Ventatesh (Cloud Architect), Purushotam Shah (Oozie Committer) and Janos Matyas (Cloudbreak Architect)
Room: Ballroom B


Topic: Streaming & Data Flow
Real-time data processing with Apache NiFi, Apache Kafka, Apache Storm and Apache Spark Streaming provides the foundation for IoAT. Come learn and discuss the latest streaming & data flow innovations and future directions.
Hosts: Aldrin Piri (NiFi Committer), Andy LoPresto (NiFi Committer), Taylor Goetz (Storm Committer), Sriharsha Chintalapani (Kafka & Storm Committer)
Room: Ballroom C

Topic: Apache Hadoop - YARN BoF
Apache Hadoop YARN is the architectural center of Hadoop that allows multiple data processing engines to handle data stored in a single platform, unlocking an entirely new approach to analytics. Come learn and discuss the latest YARN innovations and future directions.
Hosts: Vinod Vavilapalli (Hadoop Committer)
Room: 230A


Topic: Apache Hadoop - HDFS BoF
Apache Hadoop HDFS is a distributed Java-based file system for storing large volumes of data. Come learn and discuss the latest HDFS innovations and future directions.
Hosts: Jitendra Pandey (Hadoop Committer)
Room: 230C


Topic: Apache HBase BoF
Apache HBase is the NoSQL store for Hadoop. Come learn and discuss HBase 2.0, Apache Phoenix, Spark integration and more.
Hosts: Enis Soztutar (HBase Committer)
Room: 211


Topic: Security & Governance
Apache Knox and Apache Ranger provide Hadoop security while Atlas provides a Hadoop metadata store and enterprise compliance. Come learn and discuss security & governance innovations and future directions.
Hosts: Bosco Durai (Ranger Committer), Srikanth Venkat (Hortonworks Product Manager) and Andrew Ahn (Atlas Committer)
Room: 210A


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