HCatalog (see https://cwiki.apache.org/confluence/display/Hive/HCatalog) is a metadata management system for Hadoop data. It stores consistent schema information for Hadoop ecosystem tools, such as Pig, Hive, and MapReduce. By default, HCatalog supports data in the format of RCFile, CSV, JSON, SequenceFile, ORC file, and a customized format if InputFormat, OutputFormat, and SerDe are implemented. By using HCatalog, users are able to directly create, edit, and expose (via its REST API) metadata, which becomes effective immediately in all tools sharing the same piece of metadata. At first, HCatalog was a separate Apache project from Hive. Eventually, HCatalog became part of the Hive project in 2013 starting with Hive v0.11.0. HCatalog is built on top of the Hive metastore and incorporates support for HQL DDL. It provides read and write interfaces and HCatLoader and HCatStorer...
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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