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  • Book Overview & Buying Apache Hive Essentials
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Apache Hive Essentials

Apache Hive Essentials

By : Dayong Du
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Apache Hive Essentials

Apache Hive Essentials

4 (2)
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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Who this book is for
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What this book covers
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To get the most out of this book
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Get in touch
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1
Overview of Big Data and Hive
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Overview of Big Data and Hive
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A short history
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Introducing big data
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The relational and NoSQL databases 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
Setting Up the Hive Environment
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Setting Up the Hive Environment
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Installing Hive from Apache
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Installing Hive from vendors
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Using Hive in the cloud
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Using the Hive command
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Using the Hive IDE
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Summary
3
Data Definition and Description
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Data Definition and Description
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Understanding data types
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Data type conversions
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Data Definition Language
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Database
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Tables
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Partitions
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Buckets
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Views
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Summary
4
Data Correlation and Scope
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Data Correlation and Scope
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Project data with SELECT
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Filtering data with conditions
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Linking data with JOIN
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Combining data with UNION
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Summary
5
Data Manipulation
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Data Manipulation
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Data exchanging with LOAD
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Data exchange with INSERT
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Data exchange with [EX|IM]PORT
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Data sorting
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Functions
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Transactions and locks
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Summary
6
Data Aggregation and Sampling
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Data Aggregation and Sampling
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Basic aggregation
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Enhanced aggregation
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Aggregation condition
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Window functions
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Sampling
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Summary
7
Performance Considerations
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Performance Considerations
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Performance utilities
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Design optimization
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Data optimization
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Job optimization
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Summary
8
Extensibility Considerations
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Extensibility Considerations
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User-defined functions
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HPL/SQL
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Streaming
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SerDe
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Summary
9
Security Considerations
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Security Considerations
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Authentication
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Authorization
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Mask and encryption
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Summary
10
Working with Other Tools
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Working with Other Tools
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The JDBC/ODBC connector
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NoSQL
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The Hue/Ambari Hive view
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HCatalog
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Oozie
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Spark
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Hivemall
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Summary
11
Other Books You May Enjoy
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Other Books You May Enjoy
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Leave a review - let other readers know what you think

Data exchange – EXPORT and IMPORT

When working with Hive, sometimes we need to migrate data among different environments. Or we may need to back up some data. Since Hive 0.8.0, EXPORT and IMPORT statements are available to support the import and export of data in HDFS for data migration or backup/restore purposes.

The EXPORT statement will export both data and metadata from a table or partition. Metadata is exported in a file called _metadata. Data is exported in a subdirectory called data:

jdbc:hive2://> EXPORT TABLE employee TO '/user/dayongd/output3';
No rows affected (0.19 seconds)

After EXPORT, we can manually copy the exported files to other Hive instances or use Hadoop distcp commands to copy to other HDFS clusters. Then, we can import the data in the following manner:

  • Import data to a table with the same name. It throws an error if the table exists:

    jdbc:hive2://> IMPORT FROM '/user/dayongd/output3';
Error: Error while compiling statement: FAILED: SemanticException [Error 10119...
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Apache Hive Essentials
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