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Latest commit 8729966 May 3, 2016 @ekoifman ekoifman HIVE-13646 make hive.optimize.sort.dynamic.partition compatible with …
…ACID tables (Eugene Koifman, reviewed by Wei Zheng)
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accumulo-handler HIVE-12302: Use KryoPool instead of thread-local caching (Prasanth Ja… Dec 8, 2015
ant HIVE-13111: Fix timestamp / interval_day_time wrong results with HIVE… Mar 28, 2016
beeline HIVE-13645 : Beeline needs null-guard around hiveVars and hiveConfVar… May 2, 2016
bin HIVE-13440 : remove hiveserver1 scripts and thrift generated files (B… Apr 27, 2016
checkstyle HIVE-6123 : Implement checkstyle in maven (Lars Francke via Ashutosh … Sep 1, 2014
cli HIVE-13485 : Session id appended to thread name multiple times. (Vikr… May 1, 2016
common HIVE-13178: Enhance ORC Schema Evolution to handle more standard data… May 3, 2016
conf HIVE-11878: ClassNotFoundException can possibly occur if multiple jar… Dec 10, 2015
contrib HIVE-12653 : The property "serialization.encoding" in the class "org.… Mar 25, 2016
data HIVE-12878: Support Vectorization for TEXTFILE and other formats (Mat… May 2, 2016
dev-support HIVE-13654: Add JAVA8_URL to jenkins-submit-build.sh Apr 29, 2016
docs HIVE-12020: Revert log4j2 xml configuration to properties based confi… Dec 2, 2015
findbugs HIVE-3099. add findbugs in build.xml (Ransom Hezhiqiang via egc) Jun 10, 2012
hbase-handler HIVE-13527: Using deprecated APIs in HBase client causes zookeeper co… Apr 23, 2016
hcatalog HIVE-13552 : Templeton job does not write out log files on Interrupte… May 1, 2016
hplsql HIVE-13367: Extending HPLSQL parser (Dmitry Tolpeko reviewed by Alan … Mar 30, 2016
hwi Preparing for 2.1.0 development Dec 2, 2015
itests HIVE-4924: JDBC: Support query timeout for jdbc (Vaibhav Gumashta rev… May 3, 2016
jdbc HIVE-4924: JDBC: Support query timeout for jdbc (Vaibhav Gumashta rev… May 3, 2016
lib HIVE-2761: Remove lib/javaewah-0.3.jar (ecapriolo via hashutosh) Feb 25, 2012
llap-client HIVE-13447 : LLAP: check ZK acls for registry and fail if they are to… Apr 29, 2016
llap-common HIVE-13442 : LLAP: refactor submit API to be amenable to signing (Ser… May 3, 2016
llap-server HIVE-13442 : LLAP: refactor submit API to be amenable to signing (Ser… May 3, 2016
llap-tez HIVE-13442 : LLAP: refactor submit API to be amenable to signing (Ser… May 3, 2016
metastore HIVE-13213 make DbLockManger work for non-acid resources (Eugene Koif… May 3, 2016
orc HIVE-12159: Create vectorized readers for the complex types (Owen O'M… Apr 26, 2016
packaging HIVE-13643. Various enhancements / fixes to llap cli tools. (Siddhart… May 2, 2016
ql HIVE-13646 make hive.optimize.sort.dynamic.partition compatible with … May 3, 2016
serde HIVE-12878: Support Vectorization for TEXTFILE and other formats (Mat… May 2, 2016
service-rpc HIVE-4924: JDBC: Support query timeout for jdbc (Vaibhav Gumashta rev… May 3, 2016
service HIVE-4924: JDBC: Support query timeout for jdbc (Vaibhav Gumashta rev… May 3, 2016
shims HIVE-13661: [Refactor] Move common FS operations out of shim layer (A… May 2, 2016
spark-client HIVE-12650: Improve error messages for Hive on Spark in case the clus… Apr 1, 2016
storage-api HIVE-12159: Create vectorized readers for the complex types (Owen O'M… Apr 26, 2016
testutils HIVE-13603. Fix ptest unit tests broken by HIVE13505. (Siddharth Seth… Apr 28, 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-10165 Improve hive-hcatalog-streaming extensibility and support … Jun 30, 2015
.reviewboardrc Preparing for 1.3.0 development Apr 25, 2015
LICENSE HIVE-13467: Show llap info on hs2 ui when available (Gunther Hagleitn… Apr 22, 2016
NOTICE HIVE-11748: HivePreparedStatement's setTimestamp() does not quote val… Sep 23, 2015
README.txt HIVE-10676 : Update Hive's README to mention spark, and to remove jdk… May 11, 2015
RELEASE_NOTES.txt Updating release notes to reflect 1.2.1 Jun 19, 2015
errata.txt HIVE-12826: Vectorization: fix VectorUDAF* suspect isNull checks (err… Jan 18, 2016
pom.xml HIVE-13537. Update slf4j version to 1.7.10. (Siddharth Seth, reviewed… Apr 28, 2016

README.txt

Apache Hive (TM) @VERSION@
======================

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

* Tools to enable easy data extract/transform/load (ETL)

* 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 implements a dialect of SQL (Hive QL) that focuses on analytics
and presents a rich set of SQL semantics including OLAP functions,
subqueries, common table expressions and more. Hive allows SQL
developers or users with SQL tools to easily query, analyze and
process data stored in Hadoop.
Hive also allows programmers familiar with the MapReduce framework
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 (UDF's), aggregations (UDAF's), and table
functions (UDTF's).

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 and does
not support 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 out website at:

  http://hive.apache.org/


Getting Started
===============

- Installation Instructions and a quick tutorial:
  https://cwiki.apache.org/confluence/display/Hive/GettingStarted

- A longer tutorial that covers more features of HiveQL:
  https://cwiki.apache.org/confluence/display/Hive/Tutorial

- The HiveQL Language Manual:
  https://cwiki.apache.org/confluence/display/Hive/LanguageManual


Requirements
============

- Java 1.7

- Hadoop 1.x, 2.x


Upgrading from older versions of Hive
=====================================

- Hive @VERSION@ 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.
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