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Selecting the Numeric Type

Other versions: 7.31 | 7.40 | 7.54


Several numeric types with various properties and value ranges are available in ABAP, which you can use for storing numbers and for calculations:

  • Signed 4-byte and 8-byte integers (type i). There are also 1-byte and 2-byte integers with the internal types b and s. However, these data objects cannot be generated based on a predefined ABAP type. Instead, the predefined ABAP Dictionary types INT1 and INT2 are required.
  • Packed numbers in BCD format (binary coded decimals, type p)
  • Binary floating point numbers (type f)
  • Decimal floating point numbers (types decfloat16, decfloat34)

The decimal floating point numbers meet the requirements for highly exact processing of decimal numbers in a large value ranges, where the data types p and f only cover a single aspect each.


Select suitable numeric types for numbers and calculations

Select a numeric type to suit the values that you want to map, in order to achieve the highest possible speed and accuracy. Here is a general rule of thumb:

  • i
  • p for fixed point numbers
  • decfloat16 or decfloat34 for floating point numbers
  • f in exceptional cases only


The calculation speed and accuracy are generally contradictory requirements and depend on the data type of the objects to be processed. Therefore, when selecting the numeric type, you must weigh up these two requirements. These considerations must also include the value range to be mapped:

  • If the values to be mapped are integers, type i must usually be used. This guarantees the highest possible calculation speed. Examples of these integers include counters, indexes, offsets and time intervals. If the values to be mapped exceed the value range of type i, you can use type p without decimal places instead. The calculation speed is slower, but decimal places are still mapped accurately (except for rounding errors). If this value range is still not sufficient, you can use a floating point type (decfloat16 and decfloat34) instead.
  • If you have to map nonintegral values that have a fixed number of decimal places, you can use type p. However, calculations with type p are executed in the ABAP kernel and not by the hardware. Examples of non-integral values include lengths, weights, or monetary amounts. If this value range is still not sufficient, you can use a decimal floating point type (decfloat16 and decfloat34) instead. The binary floating point type f is less suitable because it cannot map all decimal fractions. This is a further impediment for calculation accuracy (in addition to the unavoidable rounding errors).
  • For nonintegral values with a variable number of decimal places or a large value range, you should use the decimal floating point types decfloat16 or decfloat34. Decfloat34 has a larger number of decimal places and a larger value range. However, this also leads to increased memory consumption.

Thanks to the hardware support available on all platforms, binary floating point type f allows fast calculations. However, it is inferior to the new decimal floating point types due to the following reasons:

  • Type f can only accuately map fractions with the power of two in the denominator (1/2, 1/4, 1/8, etc.) and totals. Other values are rounded according to this mapping. This rounding process does not correspond to the decimal rounding process (and usually does not meet the expectations of the developer or user). For example, the value 0.815 is approximated internally as 8.1499999999999995E-01. This means when the value is rounded to two decimal places, 0.81 is returned instead of the expected value 0.82.
  • Yery large numbers can no longer be exactly mapped (working in line with IEEE 754), if the difference between the largest and smallest exponent is larger than 52 (in the total of powers of two). For example, 1E+23 is mapped as 9.9999999999999992E+22.s
  • A number of type f cannot be rounded to a specific number of decimal places, if the result needs to be assigned to another number of type f.
  • Divisions by powers of 10, which often occur when converting metric units, for example, are not exact. 8.0500000000000005E-01 is returned for 805/1000, for example.
  • Simple calculations often produce unexpected results. 123456.15 - 123455 returns 1,1499999999941792, for example.
  • The conversion of binary floating point numbers to other number formats is not clearly defined in line with IEEE 754. Consequently, when data is stored in the database, the rounding behavior depends on the platform and how numbers of type f are mapped in the database.
  • The decimal floating point types decfloat16 and decfloat34 do not have these problems. Both have a larger value range than type f, and decfloat34 has 34 decimal places instead of 16 decimal places. However, the following restrictions apply:
  • Currently, calculations with decimal floating point types are generally even slower than calculations with the type f (the speed is comparable to calculations with the type p). Until now, only IBM's Power6 architecture provided hardware support for floating point calcuations of this type in accordance with IEEE-754-2008. On other platforms, calculations with decimal floating point numbers have to be performed on the software side in the ABAP kernel, in a similar way to calculations with the type p.
  • Decimal floating point types are not yet supported by associated data types on all database platforms. As an interim solution, ABAP Dictionary provides a set of predefined data types DF16_..., DF34_..., based on existing types (DEC and RAW). In most cases, the benefits of the decimal floating point types compensate for the current slow calculation speed. However, you might still need to use type f, if you have stringent requirements for performance and less stringent requirements for calculation accuracy. Remember that the speed advantage currently possible for calculations with f, may be outweighed by the fact that conversions from f to other numeric types are relatively slow.


For programs that are currently created with decimal floating point types, the performance is increased as soon as the processor architecture supports decimal floating point calculations and the ABAP runtime environment starts using this hardware support. Calculations with decimal floating point numbers then become faster than calculations with packed numbers.

Bad example

The following source code shows a declaration of a binary floating point number. The start value 0.815 is assigned. The true start value, however, is 8.1499999999999995E-01.

DATA number TYPE f VALUE '0.815'.

Good example

The following source code shows a declaration of a decimal floating point number. The start value 0.815 is assigned. The true start value is actually 8.15E-01.

DATA number TYPE decfloat34 VALUE '0.815'