Richmond Apache Spark Meetup Group - July 27, 2016 - VA

Document created by aalvarez on Jul 11, 2016Last modified by aalvarez on Sep 1, 2016
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SUMMARY

Date:July 27, 2016
Location:

Ippon USA

2700 East Cary Street
The Power plant at Lucky Strike
Richmond, VA

Time:18:00
Registration Link:

http://www.meetup.com/Richmond-Apache-Spark-Meetup/events/232385539/

Ticket PriceFree

    

ABOUT THE EVENT

The Richmond Big Data Group is a community for users, enthusiasts, and explorers of Apache Spark (http://spark.apache.org/) in the area of Richmond, Virginia. Apache Spark is a fast and general open source engine for large-scale data processing, supporting SQL, streaming, and complex analytics.

 

During this event Craig Warman, Solutions Engineer/Architect at MapR, will be delivering his talk "Spark SQL & Machine Learning - A Practical Demonstration". Join this event here: http://www.meetup.com/Richmond-Apache-Spark-Meetup/events/232385539/

 

AGENDA

  • Spark SQL & Machine Learning - A Practical Demonstration by Craig Warman - Solutions Engineer/Architect at MapR

Description

This presentation explores how SQL developers can deliver powerful machine learning applications by leveraging Spark's SQL and MLlib libraries.  A brief overview covering Spark components and architecture kicks things off, and then we dive right in with a live demonstration of loading and querying data using Spark SQL.  Next, we'll examine the basics of machine learning algorithms and workflows before getting under the hood of a Spark MLlib-based recommendation engine.  Our final demonstration looks at how familiar tools can be used to query our recommendation data before we wrap up with a survey of real-world use cases.

 

Outline

• Spark Background/Overview - Brief Spark background, the Spark+Hadoop team, Spark's five main components, How to download a ready-to-use sandbox VM

• Spark SQL Architecture - Features, Languages, How DataFrames work, The SQLContext, Data sources

• Demo #1: Loading And Querying a Dataset with Spark SQL - Live demonstration of setting up a SQLContext, loading it with data, and running queries against it

• Machine Learning with Spark MLlib - Collaborative filtering basics, Alternating Least Squares (ALS) algorithm, General machine learning workflow

• Demo #2: Under The Hood With A Spark MLlib Recommendation Engine - Recommender model code review and live demonstration of training-test loop iterations

• Demo #3 Putting It All Together - Live demonstration of how to leverage Spark SQL ODBC/JDBC connectivity to query recommendation data using familiar tools

• Some Real-World Use Cases - Basically answer the questions "What's it good for?" and "Who's using this?"

 

Prerequisite Knowledge

• Basic knowledge of typical object-oriented programming languages and concepts is helpful

• Basic understanding of databases, filesystems, and SQL

 

Audience Type

Technical

 

Parking and Directions

Directions: http://www.ipponusa.com/directions

Please park in lots marked Odell (one by the office, two on top), or on Pear Street.

 

SPEAKER MATERIALS

 

 

 

OTHER RELATED MATERIALS

On apache spark

 

 

 

On Craig Warman:

 

Find more on: spark hadoop mapr

 

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