THIS IS A TEST INSTANCE. ALL YOUR CHANGES WILL BE LOST!!!!
Apache Hive
The
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{tm}[Apache Hive|http://hive.apache.org]{tm} |
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warehouse
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software
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facilitates
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querying
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and
...
managing
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large
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datasets
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residing
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in
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distributed
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storage.
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Built
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on
...
top
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of
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{tm}[Apache Hadoop|http://hadoop.apache.org]{tm} |
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it
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provides
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- Tools
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- to
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- enable
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- easy
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- data
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- extract/transform/load
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- (ETL)
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- A
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- mechanism
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- to
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- impose
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- structure
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- on
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- a
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- variety
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- of
...
- data
...
- formats
...
- Access
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- to
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- files
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- stored
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- either
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- directly
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- in
Wiki Markup {tm}Apache HDFS{tm}
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or
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- in
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- other
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- data
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- storage
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- systems
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- such
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- as
Wiki Markup {tm}Apache HBase{tm}
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- Query
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- execution
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- via
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- MapReduce
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Hive
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defines
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a
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simple
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SQL-like
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query
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language,
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called
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QL,
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that
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enables
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users
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familiar
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with
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SQL
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to
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query
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the
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data.
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At
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the
...
same
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time,
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this
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language
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also
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allows
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programmers
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who
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are
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familiar
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with
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the
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MapReduce
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framework
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to
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be
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able
...
to
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plug
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in
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their
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custom
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mappers
...
and
...
reducers
...
to
...
perform
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more
...
sophisticated
...
analysis
...
that
...
may
...
not
...
be
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supported
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by
...
the
...
built-in
...
capabilities
...
of
...
the
...
language.
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QL
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can
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also
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be
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extended
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with
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custom
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scalar
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functions
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(UDF's),
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aggregations
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(UDAF's),
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and
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table
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functions
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(UDTF's).
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Hive
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does
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not
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mandate
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read
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or
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written
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data
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be
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in
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the
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"Hive
...
format"---there
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is
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no
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such
...
thing.
...
Hive
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works
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equally
...
well
...
on
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Thrift,
...
control
...
delimited,
...
or
...
your
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specialized
...
data
...
formats.
...
Please
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see
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...
...
and
...
...
in
...
the
...
...
...
for
...
details.
...
Hive
...
is
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not
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designed
...
for
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OLTP
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workloads
...
and
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does
...
not
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offer
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real-time
...
queries
...
or
...
row-level
...
updates.
...
It
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is
...
best
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used
...
for
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batch
...
jobs
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over
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large
...
sets
...
of
...
append-only
...
data
...
(like
...
web
...
logs).
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What
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Hive
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values
...
most
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are
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scalability
...
(scale
...
out
...
with
...
more
...
machines
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added
...
dynamically
...
to
...
the
...
Hadoop
...
cluster),
...
extensibility
...
(with
...
MapReduce
...
framework
...
and
...
UDF/UDAF/UDTF),
...
fault-tolerance,
...
and
...
loose-coupling
...
with
...
its
...
input
...
formats.
...
Components
...
of
...
Hive
...
include
...
HCatalog
...
and
...
WebHCat.
...
...
is
...
a
...
component
...
of
...
Hive.
...
It
...
is
...
a
...
table
...
and
...
storage
...
management
...
layer
...
for
...
Hadoop
...
that
...
enables
...
users
...
with
...
different
...
data
...
processing
...
tools
...
—
...
including
...
Pig
...
and
...
MapReduce
...
—
...
to
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more
...
easily
...
read
...
and
...
write
...
data
...
on
...
the
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grid.
...
WebHCat provides a service that you can use to run Hadoop MapReduce (or YARN), Pig, Hive jobs or perform Hive metadata operations using a HTTP (REST style) interface.
General Information about Hive
- Getting Started
- Presentations and Papers about Hive
- A List of Sites and Applications Powered by Hive
- Third-party Applications, Libraries, and Projects related to Hive
- FAQ
- hive-users Mailing List
- Hive IRC Channel:
#hiveon irc.freenode.net - About This Wiki
User Documentation
- Hive Tutorial
- HiveQL Language Manual (Queries, DML, DDL, CLI, etc.)
- Hive Operators and Functions
- Hive Web Interface
- Hive Client (JDBC, ODBC, Thrift, etc.)
- HiveServer2 Client
- Hive Change Log
- Avro SerDe
Administrator Documentation
- Installing Hive
- Configuring Hive
- Setting Up Metastore
- Setting Up Hive Web Interface
- Setting Up Hive Server (JDBC, ODBC, Thrift, HiveServer2)
- Hive on Amazon Web Services
- Hive on Amazon Elastic MapReduce
HCatalog and WebHCat Documentation
Resources for Contributors
- Hive Developer FAQ
- How to Contribute
- Hive Contributors Meetings
- Hive Developer Guide
- Plugin Developer Kit
- Unit Test Parallel Execution
- Hive PTest2 Infrastructure
- Hive PreCommit Patch Testing
- Hive Performance
- Hive Architecture Overview
- Hive Design Docs
- Roadmap/Call to Add More Features
- Full-Text Search over All Hive Resources
- How to edit the website
- Becoming a Committer
- How to Commit
- How to Release
- Build Status on Jenkins (Formerly Hudson)
- Project Bylaws
For more information, please see the official Hive website.
Apache Hive, Apache Hadoop, Apache HBase, Apache HDFS, Apache, the Apache feather logo, and the Apache Hive project logo are trademarks of The Apache Software Foundation.