Mirror of Apache Hive
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accumulo-handler HIVE-14460 : AccumuloCliDriver migration to junit4 (Zoltan Haindrich … Aug 13, 2016
ant HIVE-14444 Upgrade qtest execution framework to junit4 - migrate most… Aug 13, 2016
beeline HIVE-15022: Missing hs2-connection-timed-out in BeeLine.properties (P… Oct 19, 2016
bin HIVE-14672: Add timestamps to startup message in hive scripts (Naveen… Sep 1, 2016
checkstyle HIVE-6123 : Implement checkstyle in maven (Lars Francke via Ashutosh … Sep 1, 2014
cli HIVE-14739: Replace runnables directly added to runtime shutdown hook… Sep 13, 2016
common Revert "Revert "Revert "HIVE-11394: Enhance EXPLAIN display for vecto… Oct 17, 2016
conf HIVE-13798: Fix the unit test failure org.apache.hadoop.hive.cli.Test… Jun 1, 2016
contrib HIVE-14367 : Estimated size for constant nulls is 0 (Ashutosh Chauhan… Aug 1, 2016
data Revert "HIVE-12458: remove identity_udf.jar from source (Vaibhav Guma… Oct 14, 2016
dev-support Revert "HIVE-14835: Improve ptest2 build time (Prasanth Jayachandran … Sep 28, 2016
docs HIVE-12020: Revert log4j2 xml configuration to properties based confi… Dec 2, 2015
druid-handler HIVE-13316: Upgrade to Calcite 1.10 (Jesus Camacho Rodriguez, reviewe… Oct 18, 2016
findbugs HIVE-3099. add findbugs in build.xml (Ransom Hezhiqiang via egc) Jun 10, 2012
hbase-handler HIVE-14461. Move hbase_bulk to run via TestCliDriver. (Siddharth Seth… Sep 21, 2016
hcatalog HIVE-14891: Parallelize TestHCatStorer (Vaibhav Gumashta reviewed by … Oct 17, 2016
hplsql HIVE-14382: Improve the Functionality of Reverse FOR Statement (Akash… Aug 4, 2016
hwi HIVE-13919. Remove test TestHWISessionManager. (Siddharth Seth, revie… Jun 2, 2016
itests HIVE-12765: Support Intersect (distinct/all) Except (distinct/all) Mi… Oct 22, 2016
jdbc HIVE-14991: JDBC result set iterator has useless DEBUG log (Prasanth … Oct 17, 2016
lib HIVE-2761: Remove lib/javaewah-0.3.jar (ecapriolo via hashutosh) Feb 25, 2012
llap-client HIVE-14680 : retain consistent splits /during/ (as opposed to across)… Sep 19, 2016
llap-common HIVE-14624 : LLAP: Use FQDN when submitting work to LLAP (Sergey Shel… Sep 20, 2016
llap-ext-client HIVE-14624 : LLAP: Use FQDN when submitting work to LLAP (Sergey Shel… Sep 20, 2016
llap-server HIVE-14854. Add a core cluster type to QTestUtil. (Siddharth Seth, re… Sep 29, 2016
llap-tez HIVE-14624 : LLAP: Use FQDN when submitting work to LLAP (Sergey Shel… Sep 20, 2016
metastore HIVE-15010 Make LockComponent aware if it's part of dynamic partition… Oct 19, 2016
orc HIVE-14566: LLAP IO reads timestamp wrongly (Prasanth Jayachandran re… Aug 19, 2016
packaging HIVE-14217: Druid integration (Jesus Camacho Rodriguez, reviewed by A… Sep 8, 2016
ql HIVE-14580: Introduce || operator (Zoltan Haindrich reviewed by Pengc… Oct 22, 2016
serde HIVE-14680 : retain consistent splits /during/ (as opposed to across)… Sep 19, 2016
service-rpc HIVE-14276: Update protocol version in TOpenSessionReq and TOpenSessi… Aug 8, 2016
service HIVE-14927: Remove code duplication from tests in TestLdapAtnProvider… Oct 18, 2016
shims HIVE-14916. Reduce the memory requirements for Spark tests. (Dapeng S… Oct 14, 2016
spark-client HIVE-14822: Add support for credential provider for jobs launched fro… Oct 17, 2016
storage-api HIVE-14451: Vectorization: Add byRef mode for borrowed Strings in Vec… Sep 7, 2016
testutils HIVE-15009. ptest - avoid unnecessary cleanup from previous test runs… Oct 19, 2016
.arcconfig HIVE-2588 [jira] Update arcconfig to include commit listener Nov 17, 2011
.checkstyle HIVE-2930 [jira] Add license to the Hive files Apr 17, 2012
.gitattributes HIVE-7023 : Bucket mapjoin is broken when the number of small aliases… May 9, 2014
.gitignore HIVE-14373: Add integration tests for hive on S3 (Thomas Poepping and… Oct 13, 2016
.reviewboardrc HIVE-13642: Update GUESS_FIELDS option in .reviewboardrc to support c… May 10, 2016
.travis.yml HIVE-14585: Add travis.yml and update README to show build status (Pr… Aug 24, 2016
LICENSE HIVE-13467: Show llap info on hs2 ui when available (Gunther Hagleitn… Apr 23, 2016
README.md HIVE-14585: Add travis.yml and update README to show build status (Pr… Aug 24, 2016
errata.txt HIVE-14874: Master: Update errata.txt for the missing JIRA number in … Oct 2, 2016
pom.xml HIVE-15013. Config dir generated for tests should not be under the te… Oct 20, 2016


Apache Hive (TM)

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The Apache Hive (TM) data warehouse software facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Built on top of Apache Hadoop (TM), it provides:

  • Tools to enable easy access to data via SQL, thus enabling data warehousing tasks such as extract/transform/load (ETL), reporting, and data analysis

  • A mechanism to impose structure on a variety of data formats

  • Access to files stored either directly in Apache HDFS (TM) or in other data storage systems such as Apache HBase (TM)

  • Query execution using Apache Hadoop MapReduce, Apache Tez or Apache Spark frameworks.

Hive provides standard SQL functionality, including many of the later 2003 and 2011 features for analytics. These include OLAP functions, subqueries, common table expressions, and more. Hive's SQL can also be extended with user code via user defined functions (UDFs), user defined aggregates (UDAFs), and user defined table functions (UDTFs).

Hive users have a choice of 3 runtimes when executing SQL queries. Users can choose between Apache Hadoop MapReduce, Apache Tez or Apache Spark frameworks as their execution backend. MapReduce is a mature framework that is proven at large scales. However, MapReduce is a purely batch framework, and queries using it may experience higher latencies (tens of seconds), even over small datasets. Apache Tez is designed for interactive query, and has substantially reduced overheads versus MapReduce. Apache Spark is a cluster computing framework that's built outside of MapReduce, but on top of HDFS, with a notion of composable and transformable distributed collection of items called Resilient Distributed Dataset (RDD) which allows processing and analysis without traditional intermediate stages that MapReduce introduces.

Users are free to switch back and forth between these frameworks at any time. In each case, Hive is best suited for use cases where the amount of data processed is large enough to require a distributed system.

Hive is not designed for online transaction processing. It is best used for traditional data warehousing tasks. Hive is designed to maximize scalability (scale out with more machines added dynamically to the Hadoop cluster), performance, extensibility, fault-tolerance, and loose-coupling with its input formats.

General Info

For the latest information about Hive, please visit out website at:


Getting Started


  • Java 1.7 or 1.8

  • Hadoop 1.x, 2.x (2.x required for Hive 2.x)

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 MySQL, PostgreSQL, Oracle, Microsoft SQL Server, and Derby databases. If you are using a different database for your MetaStore you will need to provide your own upgrade script.

Useful mailing lists

  1. user@hive.apache.org - To discuss and ask usage questions. Send an empty email to user-subscribe@hive.apache.org in order to subscribe to this mailing list.

  2. dev@hive.apache.org - For discussions about code, design and features. Send an empty email to dev-subscribe@hive.apache.org in order to subscribe to this mailing list.

  3. commits@hive.apache.org - In order to monitor commits to the source repository. Send an empty email to commits-subscribe@hive.apache.org in order to subscribe to this mailing list.