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From: Apache Wiki <wikidiffs@apache.org>
To: core-commits@hadoop.apache.org
Date: Thu, 02 Apr 2009 00:37:29 -0000
Message-ID: <20090402003729.2823.88439@aurora.apache.org>
Subject: [Hadoop Wiki] Trivial Update of "Hive/Tutorial" by NeilConway

Dear Wiki user,

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The following page has been changed by NeilConway:
http://wiki.apache.org/hadoop/Hive/Tutorial

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  = Concepts =
  == What is Hive ==
- Hive is the next generation infrastructure made with the goal of providing tools to enable easy data summarization, adhoc querying and analysis of detail data. In addition it also provides a simple query language called QL which is based on SQL and which enables users familiar with SQL to do adhoc querying, summarization and data analysis. At the same time, this language also allows traditional map/reduce programmers to be able to plug in their custom mappers and reducers to do more sophisticated analysis which may not be supported by the built in capabilities of the language. 
+ Hive is the next generation infrastructure made with the goal of providing tools to enable easy data summarization, adhoc querying and analysis of detail data. In addition it also provides a simple query language called QL which is based on SQL and which enables users familiar with SQL to do ad-hoc querying, summarization and data analysis. At the same time, this language also allows traditional map/reduce programmers to be able to plug in their custom mappers and reducers to do more sophisticated analysis which may not be supported by the built in capabilities of the language. 
  
  == What is NOT Hive ==
- Hive is based on hadoop which is a batch processing system. Accordingly, this system does not and cannot promise low latencies on queries. The paradigm here is strictly of submitting jobs and being notified when the jobs are completed as opposed to real time queries. As a result it should not be compared with systems like Oracle where analysis is done on a significantly smaller amount of data but the analysis proceeds much more iteratively with the response times between iterations being less than a few minutes. For Hive queries response times for even the smallest jobs can be of the order of 5-10 minutes and for larger jobs this may even run into hours.
+ Hive is based on Hadoop, which is a batch processing system. Accordingly, this system does not and cannot promise low latencies on queries. The paradigm here is strictly of submitting jobs and being notified when the jobs are completed as opposed to real time queries. As a result it should not be compared with systems like Oracle where analysis is done on a significantly smaller amount of data but the analysis proceeds much more iteratively with the response times between iterations being less than a few minutes. For Hive queries response times for even the smallest jobs can be of the order of 5-10 minutes and for larger jobs this may even run into hours.
  
  In the following sections we provide a tutorial on the capabilities of the system. We start by describing the concepts of data types, tables and partitions (which are very similar to what you would find in a traditional relational database) and then illustrate the capabilities of the language with the help of some examples