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| -Apache Hive @VERSION@ |
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| -================= |
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| - |
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| -Apache Hive is a data warehouse system for Hadoop that facilitates |
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| -easy data summarization, ad-hoc querying and analysis of large |
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| -datasets stored in Hadoop compatible file systems. Hive provides a |
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| -mechanism to put structure on this data and query the data using a |
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| -SQL-like language called HiveQL. At the same time this language also |
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| -allows traditional map/reduce programmers to plug in their custom |
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| -mappers and reducers when it is inconvenient or inefficient to express |
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| -this logic in HiveQL. |
| 1 | +Apache Hive (TM) @VERSION@ |
| 2 | +====================== |
| 3 | + |
| 4 | +The Apache Hive (TM) data warehouse software facilitates querying and |
| 5 | +managing large datasets residing in distributed storage. Built on top |
| 6 | +of Apache Hadoop (TM), it provides: |
| 7 | + |
| 8 | +* Tools to enable easy data extract/transform/load (ETL) |
| 9 | + |
| 10 | +* A mechanism to impose structure on a variety of data formats |
| 11 | + |
| 12 | +* Access to files stored either directly in Apache HDFS (TM) or in other |
| 13 | + data storage systems such as Apache HBase (TM) |
| 14 | + |
| 15 | +* Query execution via MapReduce |
| 16 | + |
| 17 | +Hive defines a simple SQL-like query language, called QL, that enables |
| 18 | +users familiar with SQL to query the data. At the same time, this |
| 19 | +language also allows programmers who are familiar with the MapReduce |
| 20 | +framework to be able to plug in their custom mappers and reducers to |
| 21 | +perform more sophisticated analysis that may not be supported by the |
| 22 | +built-in capabilities of the language. QL can also be extended with |
| 23 | +custom scalar functions (UDF's), aggregations (UDAF's), and table |
| 24 | +functions (UDTF's). |
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13 | 26 | Please note that Hadoop is a batch processing system and Hadoop jobs
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14 | 27 | tend to have high latency and incur substantial overheads in job
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