Perform real-time data analytics with Hadoop
About This Video
- Analyze large volumes of data effectively by combining the power of big data processing tools such as Hadoop and Spark Streaming
- Work with different kinds of data and perform real-life data operations
- Explore best use cases, identify problem areas, and solve them with the best open source tools
This course is your guide to performing real-time data analytics and stream processing with Spark. Use different components and tools such as HDFS, HBase, and Hive to process raw data. Learn how tools such as Hive and Pig aid in this process.
In this course, you will start off by learning data analysis techniques with Hadoop using tools such as Hive. Furthermore, you will learn to apply these techniques in real-world big data applications. Also, you will delve into Spark and its related tools to perform real-time data analytics, streaming, and batch processing on your application.
Finally, you'll learn how to extend your analytics solutions to the cloud.
Please note that this course is based on Hadoop 3.0 but the code used in the course is compatible with Hadoop 3.2.
Table of Contents
- Chapter 1 : HDFS and HBase – The Hadoop Database
- Chapter 2 : Data Processing Using MapReduce
- Chapter 3 : Analyzing Data Using Hive and Pig
- Chapter 4 : Performing Real-Time Events Analysis Using Spark Streaming
- Title: Hands-On Big Data Analysis with Hadoop 3
- Release date: August 2018
- Publisher(s): Packt Publishing
- ISBN: 9781788999908