Apache Hive

The Apache Hive data warehouse software facilitates querying and managing large datasets residing in distributed storage. Built on top of Apache Hadoop, Hive provides:

• Tools to enable easy data extract/transform/load (ETL) operations
• A mechanism to impose structure on a variety of data formats
• Access to files stored either directly in Apache HDFS or in other data storage systems such as Apache HBase
• Query execution via MapReduce

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. QL can also be extended with custom scalar functions (UDFs), aggregations (UDAFs), and table functions (UDTFs).

Please note that Hadoop is a batch processing system and Hadoop jobs tend to have high latency and incur substantial overheads in job submission and scheduling. Consequently the average latency for Hive queries is generally very high (minutes) even when data sets involved are very small (say a few hundred megabytes). As a result it cannot be compared with systems such as Oracle where analyses are conducted on a significantly smaller amount of data but the analyses proceed much more iteratively with the response times between iterations being less than a few minutes. Hive aims to provide acceptable (but not optimal) latency for interactive data browsing, queries over small data sets or test queries.

Hive is not designed for online transaction processing and does not support real-time queries or row level insert/updates. It is best used for batch jobs over large sets of immutable data (like web logs). What Hive values most are scalability (scale out with more machines added dynamically to the Hadoop cluster), extensibility (with MapReduce framework and UDF/UDAF/UDTF), fault-tolerance, and loose-coupling with its input formats.

General Info

For the latest information about Hive, please visit our website.

Getting Started

Run the following commands to download and build Apache Hive:

$ mkdir mapr-hive-0.9.0
$ cd mapr-hive-0.9.0
$ git clone git://github.com/mapr/hive.git .
$ git checkout branch-0.9-mapr
$ ant maven-build

To install in the local Maven repository on the local filesystem, ${HOME}/.m2:

$ ant maven-publish -Dmvn.publish.repo=local

To install/deploy the jars in a remote staging area:

$ export MAPR_RELEASES_REPO=<URL:/path/to/staging/area/>
$ ant maven-publish -Dmvn.publish.repo=staging

To install/deploy the jars in a remote SNAPSHOT repository:

$ export MAPR_SNAPSHOTS_REPO=<URL:/path/to/snapshots/>
$ ant maven-publish

To generate a tarball:

$ ant tar -Ddist.dir=build

The tarball is located in the /build directory as hive-0.9.0.tar.gz.

• A quick tutorial can be found at Getting Started.
• A longer tutorial that covers more features of HiveQL is available at Hive Tutorial.
• For more information about HiveQL, see the HiveQL Language Manual.

Requirements

• Java 1.6
• Hadoop 0.20.x (x >= 1)

Hive Modules

Hive consists of the following modules:

• hive-anttasks
• hive-builtins
• hive-cli
• hive-common
• hive-contrib
• hive-exec
• hive-hbase-handler
• hive-hwi
• hive-jdbc
• hive-metastore
• hive-pdk
• hive-serde
• hive-service
• hive-shims

Using Hive artifacts with MapR patches in your Maven Project

Add the following dependency to your project's pom.xml file, replacing module name with the desired module from the above list. If in doubt, add the following dependency for each of the above modules.

	<dependency>
		<groupId>com.mapr.hive</groupId>
		<artifactId>[module name]</artifactId>
		<version>${mapr.hive.version}</version>
	</dependency>

Upgrading from older versions of Hive

• Hive includes changes to the MetaStore schema. If you are upgrading from an earlier version of Hive it is imperative that you upgrade the MetaStore schema by running the appropriate schema upgrade scripts located in the /scripts/metastore/upgrade directory.

  We have provided upgrade scripts for Derby and MySQL databases. If you are using a different database for your MetaStore you will need to provide your own upgrade script.

• Hive includes new configuration properties. If you are upgrading from an earlier version of Hive it is imperative that you replace all of the old copies of the hive-default.xml configuration file with the new version located in the /conf directory.

Useful mailing lists

• [email protected] - To discuss and ask usage questions. Send an empty email to [email protected] in order to subscribe to this mailing list.
• [email protected] - For discussions about code, design and features. Send an empty email to [email protected] in order to subscribe to this mailing list.
• [email protected] - In order to monitor commits to the source repository. Send an empty email to [email protected] in order to subscribe to this mailing list.