In our everyday life, we always keep on searching something. In the morning, we search for a toothbrush, newspaper, search stock prices, bus schedule, office bag, and so on. The list goes on and on. This search activity stops when we go to bed at the end of the day. We use a lot of tools and techniques to search these things to minimize the actual search time. We use Google to search most of the things such as news, stock prices, bus schedule, and anything and everything we need. To search a particular page of a book, we use the book's index. So, the point is that search is a very important activity of our life. There are two important concepts can be surfaced out of this, that is, search tool and search time. Just think of a situation where you want to know about a particular stock price of a company and it takes a few minutes to load that page. You...
Modern Big Data Processing with Hadoop
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Modern Big Data Processing with Hadoop
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Overview of this book
The complex structure of data these days requires sophisticated solutions for data transformation, to make the information more accessible to the users.This book empowers you to build such solutions with relative ease with the help of Apache Hadoop, along with a host of other Big Data tools.
This book will give you a complete understanding of the data lifecycle management with Hadoop, followed by modeling of structured and unstructured data in Hadoop. It will also show you how to design real-time streaming pipelines by leveraging tools such as Apache Spark, and build efficient enterprise search solutions using Elasticsearch. You will learn to build enterprise-grade analytics solutions on Hadoop, and how to visualize your data using tools such as Apache Superset. This book also covers techniques for deploying your Big Data solutions on the cloud Apache Ambari, as well as expert techniques for managing and administering your Hadoop cluster.
By the end of this book, you will have all the knowledge you need to build expert Big Data systems.
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Current Title:
Modern Big Data Processing with Hadoop
Table of Contents (12 chapters)
Preface
Free Chapter
Enterprise Data Architecture Principles
Hadoop Life Cycle Management
Hadoop Design Consideration
Data Movement Techniques
Data Modeling in Hadoop
Designing Real-Time Streaming Data Pipelines
Large-Scale Data Processing Frameworks
Building Enterprise Search Platform
Designing Data Visualization Solutions
Developing Applications Using the Cloud
Production Hadoop Cluster Deployment
Customer Reviews