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  • Committer: Lee Bieber
  • Date: 2011-01-08 01:57:02 UTC
  • mfrom: (1994.4.21 drizzle)
  • mto: This revision was merged to the branch mainline in revision 2063.
  • Revision ID: kalebral@gmail.com-20110108015702-d9mc4jwppb9vej94
Merge Marisa - latest doc updates, fix sphinx warnings

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Group By
 
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========
 
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The GROUP BY clause is used to extract only those records that fulfill a specified criterion.
 
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SQL GROUP BY Syntax ::
 
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        SELECT column_name, aggregate_function(column_name)
 
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        FROM table_name
 
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        WHERE column_name operator value
 
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        GROUP BY column_name
 
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**GROUP BY Clause Example**
 
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The "Activities" table:
 
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+---------+--------------+--------------+-------------+----------+
 
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|Id       |ActivityDate  |ActivityType  |ActivityCost | userID   |
 
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+=========+==============+==============+=============+==========+
 
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| 1       |2011-01-02    | Sport        |45           |131       |
 
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+---------+--------------+--------------+-------------+----------+
 
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| 2       |2011-01-02    | Art          |10           |256       |
 
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+---------+--------------+--------------+-------------+----------+
 
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| 3       |2011-01-02    | Music        |25           |022       |
 
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+---------+--------------+--------------+-------------+----------+
 
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| 4       |2011-01-02    | Food         |125          |022       |
 
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+---------+--------------+--------------+-------------+----------+
 
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| 5       |2011-01-03    | Music        |40           |131       |
 
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+---------+--------------+--------------+-------------+----------+
 
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| 6       |2011-01-03    | Food         |20           |175       |
 
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+---------+--------------+--------------+-------------+----------+
 
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Running the following simple query::
 
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        SELECT userID
 
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        FROM activities
 
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        GROUP BY userID;
 
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Returns:
 
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+---------+
 
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| userID  |
 
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+=========+
 
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| 131     |
 
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+---------+
 
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| 256     |
 
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+---------+
 
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| 022     |
 
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+---------+
 
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| 175     |
 
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+---------+
 
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(This shows that GROUP BY accepts a column_name and consolidates like customer values.)
 
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However, GROUP BY is much more powerful when used with an aggregate function. Let's say you want to find the total amount spent by each unique User.
 
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You could use the following SQL statement: ::
 
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        SELECT userID,SUM(ActivityCost) AS "Activity Total"
 
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        FROM Activities
 
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        GROUP BY userID;
 
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The result-set will look like this:
 
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======    ==============
 
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userID    Activity Total
 
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======    ==============
 
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131       85             
 
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256       10             
 
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022       150            
 
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175       20             
 
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======    ==============
 
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With the aggregate SUM() function, SQL can calculate how much each unique user has spent on activities over time.
 
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We can also use the GROUP BY statement on more than one column, like this: ::
 
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        SELECT userID,ActivityDate,SUM(ActivityCost) 
 
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        FROM Activities
 
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        GROUP BY userID,ActivityDate;
 
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