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E11 - Spark and DB2 – A perfect couple

Session Number: 3286
Track: App Dev
Session Type: Podium Presentation
Primary Presenter: Pallavi Priyadarshini [IBM]
Room(s)/
Time(s):

San Antonio => Wed, May 25, 2016 (01:00 PM - 02:00 PM)

Speaker Bio: Pallavi has over 14 years of experience in product development. She is currently the Technical Architect and Product Manager of DB2 Connect in India Software Labs. Pallavi has developed core functionalities in DB2 z/OS server engine in Silicon Valley Labs. She has also developed web based and security applications as part of two Silicon Valley startups. She regularly delivers best practice presentations in conferences and is the technical advocate for several enterprise accounts. Pallavi has authored patents and papers in data centric solutions and Redbook on DB2 in SOA. She has completed her Masters in Computer Science from San Jose State University, California and Bachelors in Computer Science from Nanyang Technological University, Singapore.
Audience experience level: Intermediate
Presentation Category: Application Design, Data Management, Emerging Technology
Presentation Platform: Cross Platform
Audiences this presentation will apply to: Application Developers, Data Architects
Technical areas this presentation will apply to: Data Warehousing and Business Intelligence, Database Performance (DB2 for LUW), Database Performance (DB2 for z/OS)
Objective 1: Spark fundamentals relevant to database integration
Objective 2: Integration between Spark and IBM data servers through DataFrame API
Objective 3: Loading DB2 data into Spark and writing Spark data into DB2
Objective 4: Spark Use Cases

Abstract:  Spark will be a gamechanger for analytics and is emerging as a de-facto analytics “operating system”. DB2 being the preferred systems of record, can leverage analytics abilities of Spark. This session will take you through examples of loading DB2 data (both z/OS and distributed) in Spark and accessing those Spark datasets through developer friendly interfaces such as Scala, Python & Java. We will show how standards that most developers are familiar with today such as SQL & JDBC can be utilized in Spark. We will also demonstrate examples of using Spark to easily join DB2 data with heterogeneous data sources such as Biginsights, JSON store & flat files. Join us to get a headstart on how Spark can provide a value add in your DB2 environments.

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