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Utilize the negative half of identity column data type

  • Mar 07 / 2012
  • 0
Data Modeling and Database Design, DBA best practices, dbDigger, Identity Columns, Performance Tunning and Optimization

Utilize the negative half of identity column data type

Identity columns are auto generated sequences used for ensuring row uniqueness at table level. Following data types of Numeric family may be used as data type of identity column.

  • int
  • bigint
  • smallint
  • tinyint
  • decimal/numeric

Above mentioned data types of numeric family may store negative values except the TINYINT. It is important to note that half of data types storage capacity of these data types is assigned to negative values. For example SMALLINT can have values from -32768 to 32767. It can hold -32768 to -1 negative values, a zero and 1 to 32767 positive values. Please also have a look at following table (Microsoft Technet) to get an idea about all numeric data types

Utilize the negative part of data type for identity columns

We may analyze that except the TINYINT data type, all other numeric data types have half capacity reserved for non negative values.

Point to Consider

Point to consider here is that identity column capacity should be fully utilized by including the negative part of data type also. Otherwise you are going to leave unused almost half of data type capacity. Very simple point is to give the lowest negative end of data type as SEED value of identity column. Consider the following demo

In above demo we used SMALLINT data type with seed and increment both 1, while creating the table. So inserting the values it failed for values more than 32767 and error was generated.

Error when identity column is saturated

Same may be verified by selecting the data from table

The identity column is saturated and while negative position of data type is there unused. Now following demo would utilize the negative portion also and would have double capacity of storage

This time insertion is successful with 34769 values. Can be verified by

Same is the case for int, bigint and decimal/numeric also. So use the identity column as valuable resource and fully utilize it to avoid early saturation.

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