Right now, all major cloud service providers, such as Amazon, Microsoft, and Google, offer matured Hadoop and Hive as services in the cloud. Using the cloud version of Hive is very convenient. It requires almost no installation and setup. Amazon EMR (http://aws.amazon.com/elasticmapreduce/) is the earliest Hadoop service in the cloud. However, it is not a pure open source version since it is customized to run only on Amazon Web Services (AWS). Hadoop enterprise service and distribution providers, such as Cloudera and Hortonworks, also provide tools to easily deploy their own distributions on different public or private clouds. Cloudera Director (http://www.cloudera.com/content/cloudera/en/products-and-services/director.html) and Cloudbreak (https://hortonworks.com/open-source/cloudbreak/), open up Hadoop deployments in the cloud through a simple, self...
Apache Hive Essentials. - Second Edition
By :
Apache Hive Essentials. - Second Edition
By:
Overview of this book
In this book, we prepare you for your journey into big data by frstly introducing you to backgrounds in the big data domain, alongwith the process of setting up and getting familiar with your Hive working environment.
Next, the book guides you through discovering and transforming the values of big data with the help of examples. It also hones your skills in using the Hive language in an effcient manner. Toward the end, the book focuses on advanced topics, such as performance, security, and extensions in Hive, which will guide you on exciting adventures on this worthwhile big data journey.
By the end of the book, you will be familiar with Hive and able to work effeciently to find solutions to big data problems
Table of Contents (12 chapters)
Preface
Free Chapter
Overview of Big Data and Hive
Setting Up the Hive Environment
Data Definition and Description
Data Correlation and Scope
Data Manipulation
Data Aggregation and Sampling
Performance Considerations
Extensibility Considerations
Security Considerations
Working with Other Tools
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