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Working with Functions and Value Expressions
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The GROUP BY clause creates three groups, one for each artist that meets the search condition defined in the WHERE clause. Of these three groups, only one is made up of duplicate values: Joni Mitchell. Because there are two Joni Mitchell rows in the ARTIST_CDS table, there are two NUMBER_SOLD values: 45 and 34. As you can see, the highest value is 45, which is the value that s included in the query results for the Joni Mitchell group. If the MIN function had been used in the SELECT statement, the 34 value would have been returned. As for the other two artist groups, because there is only one value for each of them, the same value is returned regardless of whether the MAX or the MIN function is used.
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Using the SUM Function
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Unlike the MIN and MAX functions, which select the lowest and highest values from a column, the SUM function adds column values together. This is particularly handy when you want to find the totals for grouped data (although the SUM function, like any other set function, treats the entire table as a single group if data hasn t been explicitly grouped together). To better understand the SUM function, let s take the last example we looked at and modify it slightly:
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SELECT FROM WHERE GROUP ARTIST_NAME, SUM(NUMBER_SOLD) AS TOTAL_SOLD ARTIST_CDS NUMBER_SOLD > 30 BY ARTIST_NAME;
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As you saw before, the WHERE clause returns only those rows with a NUMBER_SOLD value greater than 30. These rows are then grouped together according to the ARTIST_NAME values. Once they re grouped together, the total amount for each artist group is returned in the query results:
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ARTIST_NAME ------------Bing Crosby Joni Mitchell Patsy Cline TOTAL_SOLD ---------34 79 54
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Notice that the query results include the same three groups that were returned in the previous example. The only difference is that the TOTAL_SOLD value in the Joni Mitchell row is 79, as opposed to 45 or 34. The SUM function adds these two values together and returns a value of 79. Because the other two groups are each made up of only one entry, their TOTAL_SOLD values are the same as their NUMBER_SOLD values in the ARTIST_CDS table. You do not have to use a GROUP BY clause in a SELECT statement that uses a SUM function. You can create a SELECT statement as simple as the following:
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SELECT SUM(NUMBER_SOLD) AS TOTAL_SOLD FROM ARTIST_CDS;
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This statement merely adds together all the values in the NUMBER_SOLD column and returns a value of 292. By itself, this is not always the most helpful information, which is why using the function along with a GROUP BY clause is far more effective.
Using the AVG Function
As you probably realize, the AVG function merely averages the values in a specified column. Like the SUM function, it is most effective when used along with a GROUP BY clause, although it can be used without the clause, as shown in the following example:
SELECT AVG(NUMBER_SOLD) AS AVG_SOLD FROM ARTIST_CDS;
This statement returns a value of 29, which is based on the NUMBER_SOLD values in the ARTIST_CDS table. This means that, for all the CDs listed in the table, an average of 29 for each one has been sold. Although you might find this information helpful, it might be more useful to you if you were to create a statement that groups data together:
SELECT FROM WHERE GROUP ARTIST_NAME, AVG(NUMBER_SOLD) AS AVG_SOLD ARTIST_CDS NUMBER_SOLD > 30 BY ARTIST_NAME;
If you execute this statement, you will receive the following query results:
ARTIST_NAME ------------Bing Crosby Joni Mitchell Patsy Cline AVG_SOLD -------34 39 54
As in the previous examples, three groups are created, and for each group, an average is calculated based on the values in the NUMBER_SOLD column. For the Joni Mitchell row, this average is based on the NUMBER_SOLD values of 45 and 34. For the other two rows, the average is the same as the NUMBER_SOLD value because there is only one row for each artist.
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