We have just learned about Hive, which is a database where users can access data using SQL commands. But there are certain databases where users cannot use SQL commands. Those databases are known as NoSQL data stores. HBase is a NoSQL database. So, what is actually meant by NoSQL? NoSQL means not only SQL. In NoSQL data stores like HBase, the main features of RDBMS, such as validation and consistency, are relaxed. Also, another important difference between RDBMS or SQL databases and NoSQL databases is schema on write versus schema on read. In schema on write, the data is validated at the time of writing to the table, whereas schema on read supports validation of data at the time of reading it. In this way, NoSQL data stores support storage of huge data velocity due to the relaxation of basic data validation at the time of writing data. There are about 150 NoSQL data...
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