Book Image

Spark Analytics for Real-Time Data Processing [Video]

By : Nishant Garg
Book Image

Spark Analytics for Real-Time Data Processing [Video]

By: Nishant Garg

Overview of this book

<p>This tutorial is focused on analytics and real-time data processing using Apache Spark. You will begin with Spark SQL, using the Spark SQL API and built-in functions; within Apache Spark, you will go through some interactive analysis and look at some integrations between Spark and Java/Scala/Python.</p> <p>You will explore Spark Streaming, streaming context, and DStreams. You will learn how Spark streaming works on top of the Spark core, thus inheriting its features. You will stream data and also learn best practices for managing high-velocity streaming and external data sources.</p> <p>By the end of this course, you will be able to load data from a variety of structured sources (for example, JSON, Hive, and Parquet) using Spark SQL and schema RDDs and will perform real-time data processing.</p> <h1>Style and Approach</h1> <p>Filled with examples, this course will help viewers perform real-time data analysis and help them get started with analytics. Viewers will learn to build streaming applications and handle high-velocity streaming.</p>
Table of Contents (3 chapters)
Chapter 3
Advance Spark Streaming
Content Locked
Section 2
Best Practices for External Data Sources
Aim of this video is to explain about the Best practice for external data sources such as Flume, Kafka, Sockets and Message Queue protocol. - First it explains about Flume in context of Streaming - Next it explains about Kafka in context of Streaming - In the last it explains usage of Sockets and Message Queue protocol