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In the parlance of relational databases, any restriction imposed on the format, range, content, or dependency of a data structure is known as a constraint. Firebird provides several ways to implement constraints, including both formal, standards-defined integrity and referential constraints and user-defined CHECK constraints. Constraints are visible to all transactions that access the database and are automatically enforced by the server. They vary in their scope of action. Some, such as NOT NULL, are applied directly to a single column (column constraints) while others, such as PRIMARY KEY and some CHECK constraints, take effect at the table level (table constraints). The FOREIGN KEY constraint has table-to-table scope. Constraints exist in their own right as objects in a Firebird database. Each constraint is uniquely represented in the metadata, with the rules and dependencies of each being defined through regular relationships between the system tables.

project. For instance, you can add these commands to the postbuild step:

9

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Even values within the available precision of the floating-point number may not always store an exact representation A value such as 193 or even 123 may be represented in storage as a value that is very close to the specific number It is close enough that, when the floating-point number is rounded for output, it will display the value expected and, when it is used in calculations, the result is a very close approximation to the expected result The effect is that, when you perform some calculation that should result in the value 123, it may only be a very close approximation to 123 Exact comparisons (equality, greater than, less than, and so on) between two floating-point numbers, or between a floating-point number and zero, or a floating-point number and a fixed type, thus cannot be depended on to produce the expected results.

Summary

For this reason, do not consider using floating-point columns in keys or applying uniqueness constraints to them They will not work predictably for foreign key relationships or joins For comparisons, test floating-point values as being BETWEEN some acceptable range rather than testing for an exact match The same advice applies when testing for 0 choose a range appropriate to the magnitude and signing of your data that is between zero and a near-zero value, or between two suitable near-zero values9 In a dialect 1 database, the need to store numeric data values having a wider range than the limits of a 32-bit integer may force the choice of a DOUBLE PRECISION type Dialect 1 limitations also require the use of floating-point numbers for all reals if the database is going to be accessed by an embedded (ESQL) application.

Firebird provides two floating-point or approximate numeric data types, FLOAT and DOUBLE PRECISION, differing only in the limit of precision..

gacutil /i $(TargetFileName) regsvcs $(TargetFileName)

FLOAT is a 32-bit floating-point data type with a limit of approximately 7 digits of precision assume 6 digits for reliability. A 10-digit number 25.33333312 inserted into a FLOAT column is stored as 25.33333. The range is from 3.402 1038 to 3.402 1038. The smallest positive number it can store is 1.175 10 38.

PHP supports two implementations of regular expressions POSIX and PCRE. PCREs support more character classes and special features such as nongreedy matching and look-arounds. Regular expressions allow you to do much more than simple searching and replacing within strings. Using regular expressions in PHP you can find strings according to specific , rules, validate user input, process files such as CSV and tab-delimited files, and make complicated replacements in text. Combined with the other capabilities in PHP the possibilities are , nearly endless. For more about using regular expressions, see Regular Expression Recipes: A ProblemSolution Approach (Apress, 2005) and Regular Expression Recipes for Windows Developers: A Problem-Solution Approach (Apress, 2005).

DOUBLE PRECISION is a 64-bit floating-point data type with a limit of approximately 15 digits of precision. The range is from 308 1.797 10308 to 1.797 10308. The smallest positive number it can store is 2.225 10 308.

When a dyadic operation (addition, subtraction, multiplication, division) involves an exact numeric operand and a floating-point operand, the result will be a DOUBLE PRECISION type.

The next statement creates a column, PERCENT_CHANGE, using a DOUBLE PRECISION type:

These commands make use of the built-in $(TargetFileName) macro provided by Visual Studio .NET. Visual Studio also provides a number of other macros. To help keep the registry clean of unused typelibs, it s also a good idea to unregister the previous version of the assembly in the prebuild step of the project by adding the /u flag like this:

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