Limit search to available items
Streaming video
Author Franco Galeano, Manuel Ignacio, author

Title Big data processing with Apache Spark / Manuel Ignacio Franco Galeano, Nimish Narang
Published [Place of publication not identified] : Packt Publishing, 2019

Copies

Description 1 online resource (1 streaming video file (3 hr., 30 min., 14 sec.))
Summary "Processing big data in real time is challenging due to scalability, information consistency, and fault-tolerance. Big Data Processing with Apache Spark teaches you how to use Spark to make your overall analytical workflow faster and more efficient. You'll explore all core concepts and tools within the Spark ecosystem, such as Spark Streaming, the Spark Streaming API, machine learning extension, and structured streaming. You'll begin by learning data processing fundamentals using Resilient Distributed Datasets (RDDs), SQL, Datasets, and Dataframes APIs. After grasping these fundamentals, you'll move on to using Spark Streaming APIs to consume data in real time from TCP sockets, and integrate Amazon Web Services (AWS) for stream consumption. By the end of this course, you'll not only have understood how to use machine learning extensions and structured streams but you'll also be able to apply Spark in your own upcoming big data projects."--Resource description page
Notes Title from resource description page (Safari, viewed March 15, 2019)
Performer Presenter, Nimish Narang
SUBJECT Spark (Electronic resource : Apache Software Foundation) http://id.loc.gov/authorities/names/no2015027445
Spark (Electronic resource : Apache Software Foundation) fast (OCoLC)fst01938143
Subject Big data.
Python (Computer program language)
Application program interfaces (Computer software)
Cloud computing.
Electronic data processing.
APIs (interfaces)
Application program interfaces (Computer software)
Big data.
Cloud computing.
Electronic data processing.
Python (Computer program language)
Form Streaming video
Other Titles Sub-title on title screen: Efficiently tackle large datasets and perform big data analysis with Spark and Python