Chapter 3. Using Apache Hive

Hortonworks Data Platform deploys Apache Hive for your Hadoop cluster.

Hive is a data warehouse infrastructure built on top of Hadoop. It provides tools to enable easy data ETL, a mechanism to put structures on the data, and the capability for querying and analysis of large data sets stored in Hadoop files.

Hive defines a simple SQL-like query language, called QL, that enables users familiar with SQL to query the data. At the same time, this language also allows programmers who are familiar with the MapReduce framework to be able to plug in their custom mappers and reducers to perform more sophisticated analysis that may not be supported by the built-in capabilities of the language.

Hive Documentation

Documentation for Hive release 0.10.0 can be found in multiple places.

  1. The Hive wiki contains documentation organized in these sections:

    • General Information about Hive

    • User Documentation

    • Administrator Documentation

    • Resources for Contributors

  2. Supplementary documentation describes new features and bug fixes, including:

    • HiveServer2 JDBC

    • Decimal data type

    • Metastore server security

    • Secure cluster configuration (JDBC client setup)

  3. Javadocs describe the Hive API. The supplementary documentation includes a complete set of Javadocs for this release.

  4. Hive indexing was added in version 0.7.0; documentation and examples can be found here:

Hive JIRAs

Issue tracking for Hive bugs and improvements can be found here: Hive JIRAs.

Hive ODBC Driver

Hortonworks provides a Hive ODBC driver that allows you to connect popular Business Intelligence (BI) tools to query, analyze and visualize data stored within the Hortonworks Data Platform.

  • Download the Hortonworks Hive ODBC driver from here.

  • The instructions on installing and using this driver are available here.


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