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Extracts the set of unique values from a column into an array stored in a new column. This function is typically part of an aggregation.

Tip: To generate unique values for the generated array, apply the ARRAYUNIQUE function in the next step after this one. See ARRAYUNIQUE Function.

Input column can be of any type.

By default, the list is limited to 1000 values. To change the maximum number of values, specify a value for the limit parameter.
This function is intended to be used as part of an aggregation to return the unique set of values by group. See Pivot Transform.

For a version of this function computed over a rolling window of rows, see ROLLINGLIST Function.

unique(Name, 500)

Output: Returns the unique values for Name in an array of all values (up to a count of 500).

unique(function_col_ref, [limit_int]) [ group:group_col_ref] [limit:limit_count]

Argument	Required?	Data Type	Description
function_col_ref	Y	string	Name of column to which to apply the function
limit_int	N	integer (positive)	Maximum number of unique values to extract into the list array. From `1` to `1000`.

For more information on the group and limit parameters, see Pivot Transform.

function_col_ref

Name of the column from which to extract the list of unique values based on the grouping.

Literal values are not supported as inputs.
Multiple columns and wildcards are not supported.

Required?	Data Type	Example Value
Yes	String (column reference)	`myValues`

limit_int

Non-negative integer that defines the maximum number of unique values to extract into the list array.

NOTE: If specified, this value must between 1 and 1000, inclusive.

NOTE: Do not use the limiting argument in a unique function call on a flat aggregate, in which all values in a column have been inserted into a single cell. In this case, you might be able to use the limit argument if you also specify a group parameter. Misuse of the unique function can cause the application to crash.

Required?	Data Type	Example Value
No	Integer	`50`

function_col_ref

limit_int

Example - Colors sold this month