29 3.1.5. Hexadecimal Format for Integer Numbers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 3.2. Floating-Point Data Types. . . . . . . . . . . . . . . . . 30 3.2.1. Approximate Floating-Point Data Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 3.2.2. Decimal Floating-Point Types . . . . . . . . . . problems with legacy data when migrating a database from dialect 1 to 3. • In Dialect 3 databases, ◦ numbers (DECIMAL and NUMERIC data types) are stored internally as long fixed point values (scaled integers)

26 3.1.4. Hexadecimal Format for Integer Numbers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 3.2. Floating-Point Data Types. . . . . . . . . . . . . . . . problems with legacy data when migrating a database from dialect 1 to 3. • In Dialect 3 databases, ◦ numbers (DECIMAL and NUMERIC data types) are stored internally as long fixed point values (scaled integers) compact data storage of integer data for which only a narrow range of possible values is required. Numbers of the SMALLINT type are within the range from -2 16 to 2 16 - 1, that is, from -32,768 to 32

...............83 8.1.2. Arbitrary Precision Numbers..............................................................................83 8.1.3. Floating-Point Types........................................ differences ...............................................................................349 26.2.4. Floating-point differences...............................................................................349 with SQL capability. At the same time, we set the version numbering to start at 6.0, putting the numbers back into the sequence originally begun by the Berkeley POSTGRES project. The emphasis during development

...................79 8.1.2. Arbitrary Precision Numbers.......................................................................79 8.1.3. Floating-Point Types........................................... differences ........................................................................328 26.2.4. Floating-point differences........................................................................328 26.2.5 with SQL capability. At the same time, we set the version numbering to start at 6.0, putting the numbers back into the sequence originally begun by the Berkeley POSTGRES project. The emphasis during development

...............90 8.1.2. Arbitrary Precision Numbers..............................................................................90 8.1.3. Floating-Point Types........................................ differences ...............................................................................383 27.2.4. Floating-point differences...............................................................................383 with SQL capability. At the same time, we set the version numbering to start at 6.0, putting the numbers back into the sequence originally begun by the Berkeley POSTGRES project. The emphasis during development

DOMAIN dm_nums AS varchar(20) CHARACTER SET UTF8 COLLATE nums_coll; -- original (manufacturer) numbers CREATE TABLE wares(id int primary key, articul dm_nums ...); См. также: DROP Accepted = 1 UNION ALL SELECT number, name FROM SuspendedMembers WHERE Vindicated = 1 INSERT INTO numbers(num) WITH RECURSIVE r(n) AS ( SELECT 1 FROM rdb$database UNION ALL SELECT n+1 FROM r where рекурсивным CTE MERGE INTO numbers USING ( WITH RECURSIVE r(n) AS ( SELECT 1 FROM rdb$database UNION ALL SELECT n+1 FROM r WHERE n < 200 ) SELECT n FROM r ) t ON numbers.num = t.n WHEN NOT MATCHED

...............90 8.1.2. Arbitrary Precision Numbers..............................................................................90 8.1.3. Floating-Point Types........................................ differences ...............................................................................385 27.2.4. Floating-point differences...............................................................................385 with SQL capability. At the same time, we set the version numbering to start at 6.0, putting the numbers back into the sequence originally begun by the Berkeley POSTGRES project. The emphasis during development

...............105 8.1.2. Arbitrary Precision Numbers............................................................................105 8.1.3. Floating-Point Types........................................ differences ...............................................................................554 29.2.4. Floating-point differences...............................................................................555 ........................................................747 34.4.4. SQL Functions with Variable Numbers of Arguments...................................748 34.4.5. SQL Functions with Default Values for

...............93 8.1.2. Arbitrary Precision Numbers..............................................................................93 8.1.3. Floating-Point Types........................................ differences ...............................................................................414 28.2.4. Floating-point differences...............................................................................414 with SQL capability. At the same time, we set the version numbering to start at 6.0, putting the numbers back into the sequence originally begun by the Berkeley POSTGRES project. The emphasis during development

...................99 8.1.2. Arbitrary Precision Numbers.......................................................................99 8.1.3. Floating-Point Types........................................... differences ........................................................................521 29.2.4. Floating-point differences........................................................................521 29.2.5 Parameters ..................................................703 34.4.4. SQL Functions with Variable Numbers of Arguments............................704 34.4.5. SQL Functions with Default Values for Arguments