Numeric data types¶

NUMBER¶

Numbers up to 38 digits, with an optional precision and scale:

Precision:

Total number of digits allowed.

Scale:

Number of digits allowed to the right of the decimal point.

By default, precision is 38 and scale is 0 (i.e. NUMBER(38, 0)). Note that precision limits the range of values that can be inserted into (or cast to) columns of a given type. For example, the value 999 fits into NUMBER(38,0) but not into NUMBER(2,0).

The maximum scale (number of digits to the right of the decimal point) is 37. Numbers that have fewer than 38 significant digits, but whose least significant digit is past the 37th decimal place, for example 0.0000000000000000000000000000000000000012 (1.2e-39), cannot be represented without losing some digits of precision.

Snowflake also supports the FLOAT data type, which allows a wider range of values, although with less precision.

DECIMAL , DEC , NUMERIC¶

Synonymous with NUMBER.

INT , INTEGER , BIGINT , SMALLINT , TINYINT , BYTEINT¶

Synonymous with NUMBER, except that precision and scale cannot be specified (i.e. always defaults to NUMBER(38, 0)). Therefore, for all INTEGER data types, the range of values is all integer values from -99999999999999999999999999999999999999 to +99999999999999999999999999999999999999 (inclusive).

The various names (TINYINT, etc.) are to simplify porting from other systems and to suggest the expected range of values for a column of the specified type.

Impact of precision and scale on storage size¶

Precision (total number of digits) does not impact storage. In other words, the storage requirements for the same number in columns with different precisions, such as NUMBER(2,0) and NUMBER(38,0), are the same. For each micro-partition, Snowflake determines the minimum and maximum values for a given column and uses that information to determine the storage size for all values for that column in the partition. For example:

• If a column contains only values between -128 and +127, then each of the values consumes 1 byte (uncompressed).

• If the largest value in the column is 10000000, then each of the values consumes 4 bytes (uncompressed).

However, scale (number of digits following the decimal point) does have an impact on storage. For example, the same value stored in a column of type NUMBER(10,5) consumes more space than NUMBER(5,0). Also, processing values with a larger scale could be slightly slower and consume more memory.

To save space, Snowflake compresses values before writing them to storage. The amount of compression depends on the data values and other factors.

Examples of fixed-point data types in a table¶

CREATE OR REPLACE TABLE test_fixed(num NUMBER,
                                    num10 NUMBER(10,1),
                                    dec DECIMAL(20,2),
                                    numeric NUMERIC(30,3),
                                    int INT,
                                    integer INTEGER
                                    );

DESC TABLE test_fixed;

+---------+--------------+--------+-------+---------+-------------+------------+-------+------------+---------+
| name    | type         | kind   | null? | default | primary key | unique key | check | expression | comment |
|---------+--------------+--------+-------+---------+-------------+------------+-------+------------+---------|
| NUM     | NUMBER(38,0) | COLUMN | Y     | NULL    | N           | N          | NULL  | NULL       | NULL    |
| NUM10   | NUMBER(10,1) | COLUMN | Y     | NULL    | N           | N          | NULL  | NULL       | NULL    |
| DEC     | NUMBER(20,2) | COLUMN | Y     | NULL    | N           | N          | NULL  | NULL       | NULL    |
| NUMERIC | NUMBER(30,3) | COLUMN | Y     | NULL    | N           | N          | NULL  | NULL       | NULL    |
| INT     | NUMBER(38,0) | COLUMN | Y     | NULL    | N           | N          | NULL  | NULL       | NULL    |
| INTEGER | NUMBER(38,0) | COLUMN | Y     | NULL    | N           | N          | NULL  | NULL       | NULL    |
+---------+--------------+--------+-------+---------+-------------+------------+-------+------------+---------+

FLOAT , FLOAT4 , FLOAT8¶

The names FLOAT, FLOAT4, and FLOAT8 are for compatibility with other systems; Snowflake treats all three as 64-bit floating-point numbers.

DOUBLE , DOUBLE PRECISION , REAL¶

Synonymous with FLOAT.

Examples of floating-point data types in a table¶

CREATE OR REPLACE TABLE test_float(d DOUBLE,
                                   f FLOAT,
                                   dp DOUBLE PRECISION,
                                   r REAL
                                   );

DESC TABLE test_float;

+---------+--------------+--------+-------+---------+-------------+------------+-------+------------+---------+
| name    | type         | kind   | null? | default | primary key | unique key | check | expression | comment |
|---------+--------------+--------+-------+---------+-------------+------------+-------+------------+---------|
| D       | FLOAT        | COLUMN | Y     | NULL    | N           | N          | NULL  | NULL       | NULL    |
| F       | FLOAT        | COLUMN | Y     | NULL    | N           | N          | NULL  | NULL       | NULL    |
| DP      | FLOAT        | COLUMN | Y     | NULL    | N           | N          | NULL  | NULL       | NULL    |
| R       | FLOAT        | COLUMN | Y     | NULL    | N           | N          | NULL  | NULL       | NULL    |
+---------+--------------+--------+-------+---------+-------------+------------+-------+------------+---------+