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Apache Hive Essentials. - Second Edition

You're reading from  Apache Hive Essentials. - Second Edition

Product type Book
Published in Jun 2018
Publisher Packt
ISBN-13 9781788995092
Pages 210 pages
Edition 2nd Edition
Languages
Author (1):
Dayong Du Dayong Du
Profile icon Dayong Du

Table of Contents (12) Chapters

Preface 1. Overview of Big Data and Hive 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 11. Other Books You May Enjoy

Spark

As a general-purpose data engine, Apache Spark can integrate with Hive closely. Spark SQL has supported a subset of HQL and can leverage the Hive metastore to write or query data in Hive. This approach is also called Spark over Hive. To configure Spark, use Hive the metastore, you only need to copy the hive-site.xml to the ${SPARK_HOME}/conf directory. After that, running the spark-sql command will enter the Spark SQL interactive environment, where you can write SQL to query Hive tables.

On the other hand, Hive over Spark is a similar approach, but lets Hive use Spark as an alternative engine. In this case, users still stay in Hive and write HQL, but run over the Spark engine transparently. Hive over Spark requires the Yarn FairScheduler and set hive.execution.engine=spark. For more details, refer to https://cwiki.apache.org/confluence/display/Hive/Hive+on+Spark%3A+Getting...

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