Video description
Efficiently tackle large data sets and big data analysis challenges using Spark and Python
About This Video
This course will allow the learner to:
- Get up and running with Apache Spark and Python
- Integrate Spark with AWS for real-time analytics
- Apply processed data streams to machine learning APIs of Apache Spark
In Detail
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.
Audience
This course is for you if you are a software engineer, architect, or IT professional who wants to explore distributed systems and big data analytics. Although you don‘t need any knowledge of Spark, prior experience of working with Python is recommended.
Table of Contents
Chapter 1 : Introduction to Spark Distributed Processing
Course Overview
Installation and Setup
Lesson Overview
Introduction to Spark and Resilient Distributed Datasets
Operations Supported by the RDD API
Map Reduce Operations
Self-Contained Python Spark Programs
Nested Functions and Standalone Python Programs
Introduction to SQL, Datasets, and DataFrames
Lesson Summary
Chapter 2 : Introduction to Spark Streaming
Lesson Overview
Introduction to Streaming Architectures
Introduction to Discretized Streams (Dstreams)
Operations Supported by the Spark Streaming API
Windowing Operations
Structured Streaming
Lesson Summary
Chapter 3 : Spark Streaming Integration with AWS
Lesson Overview
Spark Integration with AWS Services
Integrating AWS Kinesis and Python
AWS S3 Basic Functionality
Kinesis Streams and Spark Streams
Lesson Summary
Chapter 4 : Spark Streaming, ML, and Windowing Operations
Lesson Overview
Spark Integration with Machine Learning
Spark Streaming Windowing Operations
Lesson Summary