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- 482 pages
- 17 hours of reading
More about the book
Explore big data concepts, platforms, analytics, and their applications using the power of Hadoop 3. Key features include learning to build effective big data analytics solutions on-premise and in the cloud, integrating Hadoop with tools like R, Python, Apache Spark, and Apache Flink, and utilizing real-world examples to exploit big data. Apache Hadoop is the leading platform for big data processing, and this resource provides insights into its software and benefits through practical examples. After reviewing Hadoop 3's latest features, you'll gain an overview of HDFS, MapReduce, and YARN, which enhance big data processing efficiency. You'll learn to integrate Hadoop with open-source tools for data analysis, visualization, and statistical computing. Additionally, the book covers using Hadoop 3 with Apache Spark and Apache Flink for real-time analytics and stream processing. You'll also discover how to build analytics solutions on the cloud and create an end-to-end pipeline for big data analysis through practical use cases. By the end, you'll be equipped with the analytical capabilities of the Hadoop ecosystem, enabling you to build powerful big data analytics solutions effortlessly. This resource is ideal for those looking to create high-performance analytics solutions using Hadoop 3, requiring a basic understanding of Java.
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Big Data Analytics with Hadoop 3, Sridhar Alla
- Language
- Released
- 2018
- product-detail.submit-box.info.binding
- (Paperback)
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- Title
- Big Data Analytics with Hadoop 3
- Subtitle
- Build Highly Effective Analytics Solutions to Gain Valuable Insight Into Your Big Data
- Language
- English
- Authors
- Sridhar Alla
- Publisher
- Packt Publishing
- Released
- 2018
- Format
- Paperback
- Pages
- 482
- ISBN10
- 1788628845
- ISBN13
- 9781788628846
- Series
- Description
- Explore big data concepts, platforms, analytics, and their applications using the power of Hadoop 3. Key features include learning to build effective big data analytics solutions on-premise and in the cloud, integrating Hadoop with tools like R, Python, Apache Spark, and Apache Flink, and utilizing real-world examples to exploit big data. Apache Hadoop is the leading platform for big data processing, and this resource provides insights into its software and benefits through practical examples. After reviewing Hadoop 3's latest features, you'll gain an overview of HDFS, MapReduce, and YARN, which enhance big data processing efficiency. You'll learn to integrate Hadoop with open-source tools for data analysis, visualization, and statistical computing. Additionally, the book covers using Hadoop 3 with Apache Spark and Apache Flink for real-time analytics and stream processing. You'll also discover how to build analytics solutions on the cloud and create an end-to-end pipeline for big data analysis through practical use cases. By the end, you'll be equipped with the analytical capabilities of the Hadoop ecosystem, enabling you to build powerful big data analytics solutions effortlessly. This resource is ideal for those looking to create high-performance analytics solutions using Hadoop 3, requiring a basic understanding of Java.