Sessions
WindyCityDB is a two-day conference that will cover four NoSQL databases: MongoDB, Neo4j, Couchbase, and Hadoop. The schedule limits presentations to 45 minutes per database. The remaining time will be spent in hands-on labs with experts in the room.
Sessions
Each session will run 45-minutes in length and will be followed by a two hour lab.
MongoDB: Schema Design by Example
Kevin Hanson, 10gen
Jesse Davis , 10gen
MongoDB has been designed for versatility, but the techniques you might use to build, say, an analytics engine or a hierarchical data store might not be obvious. In this talk, we’ll learn about MongoDB in practice by looking at four hypothetical application designs (based on real-world designs, of course). Topics to be covered include schema design, indexing, transactions (gasp!), trees, what’s fast, and what’s not. Sprinkled with tips, tricks, shoots, ladders, and trap doors, you’re guaranteed to learn something new in this interdisciplinary talk.
About the Speaker
Kevin Hanson is a Solutions Architect at 10gen, where he supports customers looking to implement MongoDB into their current architecture. Previously he was a Solutions Architect at MarkLogic.
A. Jesse Jiryu Davis is a Python programmer at 10gen. Previously, he freelanced in the NYC startup scene building iOS apps and Python / MongoDB web services for Major League Baseball, GameChanger, and ShopWiki. Jesse has been building high-performance Python systems since 2004, when he joined Wireless Generation to develop their educational-data products. Jesse holds a BA in Computer Science from Oberlin College, spent a year meditating at Zen Mountain Center, and does documentary photography on the side.
Neo4j: Adding a Recommendation Engine to Your Existing Application
Max De Marzi, Gtrot
A recommendation engine can deliver relevant and engaging personalized content to your users. This presentation (followed by a 2-hour lab) will demonstrate how to write a graph-based recommendation algorithm using the graph database Neo4j. We will be using the publicly available MovieLens dataset, but you’ll also learn how to import your own data into Neo4j.
About the Speaker
Max De Marzi will help you understand Graphs and apply them to your project. Because data is becoming increasingly connected and Graphs help you mine those connections. Because you are moving fast and need unlimited flexibility in your schema. Because your data is deeply associative and user generated (network-shaped or hierarchical data). Because friends don’t let friends write atrocious recursive joins in SQL.
Simple, Fast and Elastic with Couchbase
Raghavan “Rags” Srinivas, Couchbase
This session will begin with a very quick overview of Couchbase NoSQL, the ecosystem and what it means to developers, architects and implementers. We will demonstrate with examples of how to use the different language APIs with liberal but simple code examples on Couchbase to drive home some of these concepts. We will cover a simple application and also some real-life case studies from big social gaming applications.
About the Speaker
Raghavan “Rags” Srinivas is a Developer Advocate at Couchbase getting his hands dirty with emerging technology directions and trends. His general focus area is in distributed systems, with a specialization in cloud computing. He worked on Hadoop and HBase during its early stages. He has spoken on a variety of technical topics at conferences around the world, conducted and organized Hands-on Labs and taught graduate classes in the evening.
Hadoop and Hive - The NoDatabase Database
Mike Segel, Think Big Analytics
Dean Wampler, Think Big Analytics
Hadoop is a general-purpose Big Data platform that offers distributed scalability for data storage and flexible options for working with data. In this session, we’ll learn how various Hadoop tools and techniques address particular data scenarios, including traditional reporting, NoSQL data management, and Machine Learning. In the lab, we’ll use Hive, the SQL engine for Hadoop, to query data at scale, as if Hadoop were a traditional data warehouse.
We will spend the 45 minute talk laying out the Hadoop landscape and how you would approach different kinds of problems using different tools. The 2-hour lab will focus on one tool, Hive, the SQL tool for using Hadoop as a data warehouse. The goal is to discuss how Hadoop is a flexible environment for all kinds of data needs, some well outside the traditional realms of data “solutions”, for example doing Machine Learning, and it supports NoSQL options. The lab shows how the traditional approach of using SQL to query the data still works with Hadoop, when that’s the most appropriate tool for particular needs. Actually, you get most of what SQL traditionally provides. We’ll highlight what’s different.
About the Speaker
Mike Segel is a Big Data addict! He is the organizer of the Chicago area Hadoop User Group (CHUG). Mike started using Hadoop (Cloudera’s CDH2) in 2009. Today he works with Cloudera’s releases and MapR. Michael has been described as having a face for Radio. Thus to protect everyone, we’ve replaced Michael’s photo with this cute image of the CHUG logo.
Dean Wampler does consulting and training on Hadoop and other Big Data technologies for Think Big Analytics. He is a frequent conference speaker and the author/co-author of Functional Programming for Java Developers, Programming Scala, and Programming Hive (forthcoming). He is opinionated, even ornery, about languages, paradigms, and software processes.
