English | MP4 | AVC 1920×1080 | AAC 48KHz 2ch | 1h 22m | 272 MB
Perform Big Data analytics and draw conclusions from data without extensive programming knowledge
This course will show you how to acquire structured, semi-structured, and unstructured content from different data sources. You’ll learn to query data using Spark SQL and acquire and load data via the Spark processing tool. You will learn to import structured and unstructured data from different data sources. Going further, you will learn how to use Apache Spark to perform complex processing without extensive programming knowledge and how to leverage those tools to perform data -analytics.
By the end of the course, you will have learned to create real-world apps and stream high-velocity data with Spark Streaming.
This course will help you perform data analysis; each subject is accompanied by examples and practice exercises to make you more productive after each video.
What You Will Learn
- Easy data computation via Spark SQL.
- Learn basic Spark functionalities
- Achieve efficient task scheduling, memory management, and fault recovery with Spark components
- Adopt the right framework for better performance.
- Provide uniform wrapping across all data access with SparkSession.
- Attain fast data processing on your unstructured data with Spark RDD.
- Achieve high-level abstraction with DataFrames, Datasets, and structured/semi-structured data.
Table of Contents
APACHE SPARK ECOSYSTEM FOR BIG DATA PROCESSING
The Course Overview
Introduction to Spark
Setting up and Running Apache Spark Programs
Spark Versus MapReduce- Choosing the Preferred Framework
EXPLORING THE SPARK MODULE
Working with Spark
Interacting with SparkSession
Spark SQL
SPARK FOR DATA PROCESSING
Resilient Distributed Datasets (RDDs)
Working with DataFrames and Datasets
Data Pre-Processing
STRUCTURED STREAMING
Applications of Structured Streaming
Developing Structured Streaming Applications
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