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  • Book Overview & Buying Apache Hive Essentials
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Apache Hive Essentials

Apache Hive Essentials

By : Dayong Du
4.5 (4)
Buy this Book
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Apache Hive Essentials

Apache Hive Essentials

4.5 (4)
By: Dayong Du
Buy this Book

Overview of this book

If you are a data analyst, developer, or simply someone who wants to use Hive to explore and analyze data in Hadoop, this is the book for you. Whether you are new to big data or an expert, with this book, you will be able to master both the basic and the advanced features of Hive. Since Hive is an SQL-like language, some previous experience with the SQL language and databases is useful to have a better understanding of this book.
Table of Contents (12 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
Lock Free Chapter
1
1. Overview of Big Data and Hive
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1. Overview of Big Data and Hive
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A short history
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Introducing big data
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Relational and NoSQL database versus Hadoop
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Batch, real-time, and stream processing
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Overview of the Hadoop ecosystem
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Hive overview
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Summary
2
2. Setting Up the Hive Environment
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2. Setting Up the Hive Environment
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Installing Hive from Apache
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Installing Hive from vendor packages
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Starting Hive in the cloud
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Using the Hive command line and Beeline
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The Hive-integrated development environment
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Summary
3
3. Data Definition and Description
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3. Data Definition and Description
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Understanding Hive data types
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Data type conversions
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Hive Data Definition Language
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Hive database
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Hive internal and external tables
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Hive partitions
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Hive buckets
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Hive views
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Summary
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4. Data Selection and Scope
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4. Data Selection and Scope
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The SELECT statement
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The INNER JOIN statement
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The OUTER JOIN and CROSS JOIN statements
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Special JOIN – MAPJOIN
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Set operation – UNION ALL
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Summary
5
5. Data Manipulation
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5. Data Manipulation
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Data exchange – LOAD
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Data exchange – INSERT
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Data exchange – EXPORT and IMPORT
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ORDER and SORT
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Operators and functions
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Transactions
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Summary
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6. Data Aggregation and Sampling
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6. Data Aggregation and Sampling
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Basic aggregation – GROUP BY
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Advanced aggregation – GROUPING SETS
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Advanced aggregation – ROLLUP and CUBE
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Aggregation condition – HAVING
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Analytic functions
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Sampling
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Summary
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7. Performance Considerations
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7. Performance Considerations
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Performance utilities
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Design optimization
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Data file optimization
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Job and query optimization
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Summary
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8. Extensibility Considerations
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8. Extensibility Considerations
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User-defined functions
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Streaming
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SerDe
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Summary
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9. Security Considerations
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9. Security Considerations
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Authentication
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Authorization
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Encryption
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Summary
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10. Working with Other Tools
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10. Working with Other Tools
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JDBC / ODBC connector
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HBase
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Hue
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HCatalog
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ZooKeeper
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Oozie
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Hive roadmap
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Summary
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Index
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Index

Chapter 6. Data Aggregation and Sampling

This chapter is about how to aggregate and sample data in Hive. It firstly covers the usage of several aggregation functions, analytic functions working with GROUP BY and PARTITION BY, and windowing clauses. Then, it introduces different ways of sampling data in Hive.

In this chapter, we will cover the following topics:

  • Basic aggregation
  • Advanced aggregation
  • Aggregation condition
  • Analytic functions
  • Sampling
CONTINUE READING
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Tech Concepts
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Programming languages
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Apache Hive Essentials
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