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Apache Hive Essentials

You're reading from Apache Hive Essentials Essential techniques to help you process, and get unique insights from, big data

Product type Paperback

Published in Jun 2018

Publisher Packt

ISBN-13 9781788995092

Length 210 pages

Edition 2nd Edition

Languages

Java

Tools

Hive

Concepts

Big Data

Author (1):

Dayong Du

View More author details

Table of Contents (18) Chapters

Title Page

Copyright and Credits

Dedication

Packt Upsell

Contributors

Preface

1. Overview of Big Data and Hive FREE CHAPTER

2. Setting Up the Hive Environment

3. Data Definition and Description

4. Data Correlation and Scope

5. Data Manipulation

6. Data Aggregation and Sampling

7. Performance Considerations

8. Extensibility Considerations

9. Security Considerations

10. Working with Other Tools

1. Other Books You May Enjoy

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Index

Transactions and locks

ACID (Atomicity, Consistency, Isolation, and Durability) is a long-expected Hive feature, and builds a foundation for relational databases; it has been available since Hive v0.14.0.Full ACID support in Hive is implemented through row-level transactions and locks. This makes it possible for Hive to deal with use cases such as concurrent read/write, data cleaning, data modification, complex ETL/SCD (Slow Changing Dimensions), streaming data ingest, bulk data merge, and so on. In this section, we'll introduce them in more detail.

Transactions

For now, all transactions in HQL are auto-committed without supporting BEGIN, COMMIT, and ROLLBACK, like as with relational databases. Also, the table that has a transaction feature enabled has to be a bucket table with the ORC file format. The following configuration parameters must be set appropriately in hive-site.xml or beeline connection string to turn on transaction support:

> SET hive.support.concurrency = true;
> SET hive...

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Authors (1)

Dayong Du

Dayong Du

Dayong Du has all his career dedicated to enterprise data and analytics for more than 10 years, especially on enterprise use case with open source big data technology, such as Hadoop, Hive, HBase, Spark, etc. Dayong is a big data practitioner as well as author and coach. He has published the 1st and 2nd edition of Apache Hive Essential and coached lots of people who are interested to learn and use big data technology. In addition, he is a seasonal blogger, contributor, and advisor for big data start-ups, co-founder of Toronto big data professional association.

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