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Make Data Work
September 26–27, 2016: Training
September 27–29, 2016: Tutorials & Conference
New York, NY

A deep dive into Structured Streaming in Spark

Ram Sriharsha (Databricks)
11:20am–12:00pm Thursday, 09/29/2016
Spark & beyond
Location: Hall 1B Level: Beginner
Tags: real-time
Average rating: ***..
(3.25, 8 ratings)

Prerequisite knowledge

  • Basic familiarity with Spark
  • What you'll learn

  • Explore the basics of Structured Streaming, continuous applications, and their integration with your existing stack
  • Description

    Structured Streaming is a new effort in Apache Spark to make stream processing simple without the need to learn a new programming paradigm or system. Ram Sriharsha offers an overview of Structured Streaming, discussing its support for event-time, out-of-order/delayed data, sessionization, and integration with the batch data stack to show how it simplifies building powerful continuous applications.

    Photo of Ram Sriharsha

    Ram Sriharsha

    Databricks

    Ram Sriharsha is the product manager for Apache Spark at Databricks and an Apache Spark committer and PMC member. Previously, Ram was architect of Spark and data science at Hortonworks and principal research scientist at Yahoo Labs, where he worked on scalable machine learning and data science. He holds a PhD in theoretical physics from the University of Maryland and a BTech in electronics from the Indian Institute of Technology, Madras.

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    Comments

    10/03/2016 5:19am EDT

    Ram , can you pls share the powerpoint you presented on structured streaming and spark2.0