Big Data Processing with Apache Spark
Processing big data in real-time is challenging due to scalability, information consistency, and fault tolerance. This course shows you how you can use Spark to make your overall analysis workflow faster and more efficient. You'll learn all about the core concepts and tools within the Spark ecosystem, like 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.
After completing this course, you will be able to:
2 days
This course is aimed at IT professionals seeking to learn Spark to process big data. This course is get you up and running with Apache Spark and Python. You'll integrate Spark with AWS for real-time analytics. Finally, you'll apply processed data streams to machine learning APIs of Apache Spark.
Big Data Processing with Apache Spark 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.
For an optimal experience with the hands-on labs and other practical activities, we recommend the following hardware configuration:
Lesson 1: Introduction to Spark Distributed Processing
Lesson 2: Introduction to Spark Streaming
Lesson 3: Spark Streaming Integration with AWS
Lesson 4: Spark Streaming, ML, and Windowing Operations
SKU | 035435SC |
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Weight | 0.7320 |
Coming Soon | No |
Days of Training | 2.0 |
Audience | Student |
Product Family | Partnerware |
Product Type | Print and Digital Courseware |
Electronic | Yes |
ISBN | No |
Language | English |
Page Count | 124 |
Curriculum Library | No |
Year | No |
Manufacturer's Product Code | No |
Current Revision | 1.0 |
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Revision Notes | No Revision Information Available |
Original Publication Date | 2018-12-14 00:00:00 |