SQL syntax Language 

Type conversions

Implicit data type conversions are possible in SQL implementations. For example, if a smallint is compared to an int in T-SQL, the smallint is implicitly converted to int before the comparison proceeds. See BOL for details about implicit and explicit conversions in MS SQL Server.

Example. Find the average price of laptops with the prefix text "Average price = ".
If you run the query

SELECT 'Average price = ' + AVG(price) FROM laptop;

the following error message will be obtained:

Implicit conversion from data type varchar to money is not allowed. Use the CONVERT function to run this query.

This message implies that the system cannot accomplish implicit conversion of the character constant "Average price = " to data type money of the field price. In such cases, explicit type conversion can help. In so doing, as the above message says, you can use the CONVERT function. However this function is not based on the SQL-92 standard. Because of this, it is preferable to use the standard function CAST. So, we start with CAST.
If we rewrite above query as follows
SELECT 'Average price = ' + CAST(AVG(price) AS CHAR(15)) FROM laptop;

we get desired result:
Average price = 1410.44

We have used the expression for explicit type conversion CAST to bring the average value to the character view. The statement CAST has very simple syntax:

CAST(<expression> AS <data type>)

Firstly, it should be noted that some data type conversions are not supported. (SQL-92 Standard involves the table of allowed conversions). Secondly, NULL-value is converted into NULL-value also.
Let us consider another example: Define the average launching year from the Ships table. The query

SELECT AVG(launched) FROM ships;

gives 1926. In principle, it is correct, because a year is integer number. However arithmetic mean will be about 1926,2381. It should be noted that aggregate functions (except COUNT which always returns integer value) inherits the type of data to be processed. Because the launched field is integer-valued, we have gotten the average value without fractional part (not rounded off).
What must we do if the result ought to be obtained with two digits after decimal point? As mentioned above, applying the CAST statement to the average value gives no result. Indeed,
SELECT CAST(AVG(launched) AS NUMERIC(6,2)) FROM ships;

returns the value of 1926.00. Consequently, the CAST statement should be applied to the argument of the aggregate function:
SELECT AVG(CAST(launched AS NUMERIC(6,2))) FROM ships;

The result - 1926.238095 - is not exactly correct. This is because of implicit conversion that was accomplished when calculating the average value. Another step:

It is the correct result - 1926.24. However this solution looks too cumbersome. Let implicit conversion to work for us:
SELECT CAST(AVG(launched*1.0) AS NUMERIC(6,2)) FROM ships;

Thus, we use implicit conversion of the argument from integer to exact numeric type by multiplying it by real unity. After that, explicit conversion is applied to the result of the aggregate function.
The same conversions can be made with aid of the CONVERT function:
SELECT CONVERT(NUMERIC(6,2),AVG(launched*1.0)) FROM ships;

The CONVERT function has the following syntax:

CONVERT (<data type>[(<length>)], <expression> [, <style>])

The main distinction of the CONVERT function from the CAST statement is that the first allows formatting data (for example, temporal data of datetime type) when converting them to character data and specifying the format when converting character data to datetime. The values of integer optional argument style correspond to different formats. Let us consider the following example

SELECT CONVERT(char(25),CONVERT(datetime,'20030722'));

Here, the string representation of a date is converted to datetime following the reverse conversion to demonstrate the result of formatting. Since the style argument is omitted, default value is used (0 or 100). As a result, we obtain
Jul 22 2003 12:00AM

Below are some values of the style argument and corresponding results from the above example. Note, the style values greater than 100 give four-place year.
style format
1 07/22/03
11 03/07/22
3 22/07/03
121 2003-07-22 00:00:00.000

All possible values of the style argument are given in BOL.

CASE statement

Let the list of all the models of PC is required along with their prices. Besides that, if the model is not on sale (not in PC table), in the place of price must be the text "Not available".
The list of all the PC models with its prices we can obtain running the query:

SELECT DISTINCT product.model, price FROM product LEFT JOIN pc c
   ON product.model=c.model
   WHERE product.type='pc';

Missing prices will be replaced by NULL-values:
model price
1121 850
1232 350
1232 400
1232 600
1233 600
1233 950
1233 980
1260 350
2111 NULL
2112 NULL

The CASE statement helps us to get required text instead of NULL:
SELECT DISTINCT product.model,
   CASE WHEN price IS NULL THEN 'Not available' ELSE CAST(price AS CHAR(20)) END price
   FROM product LEFT JOIN pc c ON product.model=c.model
   WHERE product.type='pc'

Depending on defined conditions, the CASE statement returns one of the possible values. The condition in above example is the checking for NULL. If this condition is satisfied, the text "Not available" will be returned; otherwise (ELSE) it will be the price. One principal moment is here. As a table is always the result of the SELECT statement, all values from any column must be of the same data type (having regard to implicit type conversions). Then, we cannot combine character constant with a price (numeric type) within a single column. That is the reason why we use the type conversion to the price column to reduce its type to character. As a result, we get
model price
1121 850
1232 350
1232 400
1232 600
1233 600
1233 950
1233 980
1260 350
2111 Not available
2112 Not available

The CASE statement may be used in one of two syntax forms:

The first form
CASE <input expression>
   WHEN <when expression 1>
   THEN <return expression 1>
   WHEN <when expression N>
   THEN <return expression N>
[ELSE <return expression>]

Second form
   WHEN <predicate 1>
   THEN <return expression 1>
   WHEN <predicate N>
   THEN <return expression N>
[ELSE <return expression>]

All WHEN clauses must be in the same syntax form, i.e. first and second forms cannot be mixed. When using the first syntax form, the WHEN condition is satisfied as soon as the value of when expression will be equal to the value of input expression. When using the second syntax form, the WHEN condition is satisfied as soon as the predicate evaluates to TRUE. When satisfying condition, the CASE statement returns the return expression from the corresponding THEN clause. If no WHEN expression is satisfied, the return expression from the ELSE clause will be used. If no ELSE clause is specified, a NULL value will be returned. If more than one condition are satisfied, the first return expression from them will be returned.
The above example uses the second form of the CASE statement.
It should be noted that checking for NULL could also be made using the standard function COALESCE, which is simpler. This function has arbitrary number of arguments and returns the first not-NULL expression among them. In the case of two arguments, COALESCE(A, B) is equivalent to the following CASE statement:


When using the COALESCE function, the solution to the above example may be rewritten as follows
SELECT DISTINCT product.model,
   COALESCE(CAST(price as CHAR(20)),'Not available') price
   FROM product LEFT JOIN pc c ON product.model=c.model
   WHERE product.type='pc';

Usage of the first syntax form of the CASE statement can be demonstrated by the following example: Get all available PC models, their prices, and information about the most expensive and cheap models.
SELECT DISTINCT model, price,
   CASE price WHEN (SELECT MAX(price) FROM pc) THEN 'Most expensive'
   WHEN (SELECT MIN(price) FROM pc) THEN 'Most cheap'
   ELSE 'Mean price' END comment
   FROM pc ORDER BY price;

The result set
model price comment
1232 350 Most cheap
1260 350 Most cheap
1232 400 Mean price
1233 400 Mean price
1233 600 Mean price
1121 850 Mean price
1233 950 Mean price
1233 980 Most expensive

Suggested exercises: 31, 32, 47, 53, 54.

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