Thursday, January 26, 2017 at 8:00:00 PM Live Webinar, Kansas City, KS

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Streaming analytics and Internet Of Things ( IOT) are gaining momentum in the data and analytics industry. Apache Spark established itself as a leader in fast data processing with its ease of use. With its single execution engine and unified programming model for batch and streaming workloads, it stands out from other distributed stream processing engines. 

Join this webinar to go over basics and internals of the Streaming module of Apache Spark along with code samples. This topic is intended for audiences with some familiarity or working experience with Apache Spark core.​ 

Apache Spark Streaming:​ 

Architecture and Execution Model

Spark Streaming I/O

Programing model and Streaming Operations (api)

Fault tolerance and reliability

Performance Considerations

Presenter Bio:

  Suresh Matlapudi is an Open Source Analytics Solution Engineer with IBM. He is a hands-on Engineer with deep experience in distributed data processing, Big Data, Data Warehousing and Hybrid Information Architectures. His current work involves supporting sales teams with pre-sales and technical specifications for Open Source Analytics tools, specifically Hadoop/Spark and execution of several outreach programs to support Open Source adoption by Analytics teams. 

Before joining IBM he was involved in building some of the large-scale data processing systems at companies like eHarmony, Deem, American Express, Knights Bridge Solutions.

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