A Deep-dive into Structured Streaming / Predictive Analytics with SparkR

A Deep-dive into Structured Streaming

In Apache Spark 2.0, we have extended DataFrames and Datasets in Spark to handle streaming data. Streaming Datasets not only provides a single programming abstraction for batch and streaming data, it brings support for event-time based processing, out-of-order/delayed data, sessionization and tight integration with non-streaming data sources and sinks. In this talk, Burak will take a deep dive into the concepts and the API and show how this simplifies building complex “continuous applications."

Burak Yavuz is a Software Engineer at Databricks. He's been contributing to Spark since Spark 1.1, and is the maintainer of Spark Packages ( https://spark-packages.org (https://spark-packages.org/), https://spark-packages.appspot.com/ ).

Predictive Analytics with SparkR

• Introduction to SparkR

• Installation

• Predictive Analytics

• Application

Olgun Aydın is a Data Scientist at STM, he is also PhD Candidate at Mimar Sinan University Department of Statistics. He has been studying on so many different areas like Biometry, Finance, Social Science. He has so many academic papers, proceedings about applications of these areas. Olgun enjoys to play with data on Big Data platform. He is familiar with reporting tools, big data query languages.