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NULL Values and Column Functions
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The SUM(), AVG(), MIN(), MAX(), and COUNT() column functions each take a column of data values as their argument and produce a single data value as a result. What happens if one or more of the data values in the column is a NULL value The ANSI/ISO SQL standard specifies that NULL values in the column are ignored by the column functions. This query shows how the COUNT() column function ignores any NULL values in a column: SELECT COUNT(*), COUNT(SALES), COUNT(QUOTA) FROM SALESREPS COUNT(*) COUNT(SALES) COUNT(QUOTA) --------- ------------ ------------
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The SALESREPS table contains ten rows, so COUNT(*) returns a count of ten. The SALES column contains ten non-NULL values, so the function COUNT(SALES) also returns a count of ten. The QUOTA column is NULL for the newest salesperson. The COUNT(QUOTA) function ignores this NULL value and returns a count of nine. Because of these anomalies, the COUNT(*) function is almost always used instead of the COUNT() function, unless you specifically want to exclude NULL values in a particular column from the total. Ignoring NULL values has little impact on the MIN() and MAX() column functions. However, it can cause subtle problems for the SUM() and AVG() column functions, as illustrated by this query: SELECT SUM(SALES), SUM(QUOTA), (SUM(SALES) SUM(QUOTA)), SUM(SALES-QUOTA) FROM SALESREPS SUM(SALES) SUM(QUOTA) SUM(SALES-QUOTA) -------------- ------------------$2,893,532.00 $2,700,000.00 $117,547.00 You would expect the two expressions: (SUM(SALES) SUM(QUOTA)) and SUM(SALES-QUOTA) (SUM(SALES)-SUM(QUOTA)) ----------------------$193,532.00 ---------
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in the select list to produce identical results, but the example shows that they do not. The salesperson with a NULL value in the QUOTA column is again the reason. The expression: SUM(SALES) totals the sales for all ten salespeople, while the expression: SUM(QUOTA) totals only the nine non-NULL quota values. The expression: SUM(SALES) SUM(QUOTA) computes the difference of these two amounts. However, the column function: SUM(SALES QUOTA) has a non-NULL argument value for only nine of the ten salespeople. In the row with a NULL quota value, the subtraction produces a NULL, which is ignored by the SUM() function. Thus, the sales for the salesperson without a quota, which are included in the previous calculation, are excluded from this calculation. Which is the "correct" answer Both are! The first expression calculates exactly what it says: "the sum of SALES, less the sum of QUOTA." The second expression also calculates exactly what it says: "the sum of (SALES QUOTA)." When NULL values occur, however, the two calculations are not quite the same.
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The ANSI/ISO standard specifies these precise rules for handling NULL values in column functions: If any of the data values in a column are NULL, they are ignored for the purpose of computing the column function's value. If every data item in the column is NULL, then the SUM(), AVG(), MIN(), and MAX() column functions return a NULL value; the COUNT() function returns a value of zero. If no data items are in the column (that is, the column is empty), then the SUM(), AVG(), MIN(), and MAX() column functions return a NULL value; the COUNT() function returns a value of zero. The COUNT(*) counts rows and does not depend on the presence or absence of NULL values in a column. If there are no rows, it returns a value of zero. Although the standard is very clear in this area, commercial SQL products may produce results different from the standard, especially if all of the data values in a column are NULL or when a column function is applied to an empty table. Before assuming the behavior specified by the standard, you should test your particular DBMS.
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Duplicate Row Elimination (DISTINCT)
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Recall from 6 that you can specify the DISTINCT keyword at the beginning of the select list to eliminate duplicate rows of query results. You can also ask SQL to eliminate duplicate values from a column before applying a column function to it. To eliminate duplicate values, the keyword DISTINCT is included before the column function argument, immediately after the opening parenthesis. Here are two queries that illustrate duplicate row elimination for column functions: How many different titles are held by salespeople SELECT COUNT(DISTINCT TITLE) FROM SALESREPS COUNT(DISTINCT TITLE) ---------------------3 How many sales offices have salespeople who are over quota SELECT COUNT(DISTINCT REP_OFFICE) FROM SALESREPS WHERE SALES > QUOTA COUNT(DISTINCT REP_OFFICE) --------------------------4 The SQL1 standard specified that when the DISTINCT keyword is used, the argument to the column function must be a simple column name; it cannot be an expression. The standard allows the DISTINCT keyword for the SUM() and AVG() column functions. The standard does not permit use of the DISTINCT keyword with the MIN() and MAX() column functions because it has no impact on their results, but many SQL
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implementations allow it anyway. The standard also requires the DISTINCT keyword for the COUNT() column function, but many SQL implementations permit the use of the COUNT() function without it. DISTINCT cannot be specified for the COUNT(*) function, because it doesn't deal with a column of data values at all it simply counts rows. The SQL2 standard relaxed these restrictions, allowing DISTINCT to be applied for any of the column functions and permitting expressions as arguments for any of the functions as well. In addition, the DISTINCT keyword can be specified only once in a query. If it appears in the argument of one column function, it can't appear in any others. If it is specified before the select list, it can't appear in any column functions. The only exception is that DISTINCT may be specified a second time inside a subquery (contained within the query). Subqueries are described in 9.
Grouped Queries (GROUP BY Clause)
The summary queries described thus far are like the totals at the bottom of a report. They condense all of the detailed data in the report into a single, summary row of data. Just as subtotals are useful in printed reports, it's often convenient to summarize query results at a "subtotal" level. The GROUP BY clause of the SELECT statement provides this capability. The function of the GROUP BY clause is most easily understood by example. Consider these two queries: What is the average order size SELECT AVG(AMOUNT) FROM ORDERS AVG(AMOUNT) -----------$8,256.37 What is the average order size for each salesperson SELECT REP, AVG(AMOUNT) FROM ORDERS GROUP BY REP REP AVG(AMOUNT) ---- ----------101 $8,876.00 102 $5,694.00 103 $1,350.00 105 $7,865.40 106 $16,479.00 107 $11,477.33 108 $8,376.14 109 $3,552.50 110 $11,566.00 The first query is a simple summary query like the previous examples in this chapter. The second query produces several summary rows one row for each group, summarizing the orders taken by a single salesperson. Figure 8-3 shows how the second query works.
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Conceptually, SQL carries out the query as follows:
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