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Release 5.0.1


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Extracts a non-null and non-missing value from a specified column. If all values are missing or null, the function returns a null value.This function is intended to be used as part an aggregation to return any single value. When run at scale, there is some randomness to the value that is returned from the aggregated groupings, although randomness in not guaranteed.

In a flat aggregation, in which no aggregate function is applied, it selects the first value that it can retrieve from a column, which is the first value. This function has limited value outside of an aggregation. See Pivot Transform.

Input column might be of Integer, Decimal, String, Object, or Array type. 

Basic Usage

pivot value:ANY(myRating) group:postal_code limit: 1

Output: Generates a two-column table containing the unique values from the postal_code column and a single value from the myRating column for the postal_code value. The limit parameter defines the maximum number of output columns.

Syntax and Arguments

pivot value:ANY(function_col_ref) [group:group_col_ref] [limit:limit_count]

ArgumentRequired?Data TypeDescription
function_col_refYstringName of column to which to apply the function

For more information on syntax standards, see Language Documentation Syntax Notes.

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

function_col_ref

Name of the column from which to extract a value based on the grouping.

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

Usage Notes:

Required?Data TypeExample Value
YesString (column reference)myValues


Examples


Tip: For additional examples, see Common Tasks.

Example - Aggregating on one customer per month

You want to do some sampling of customer orders on a monthly basis. For your sample, you want to select the sum of orders for one customer each month. 

Source:

Here are the orders for 1Q 2015:

OrderIdDateCustIdQty
10011/8/15C000112
10022/12/15C000265
10031/16/15C000423
10041/31/15C000292
10052/2/15C000556
10063/2/15C000683
10073/16/15C000562
10082/21/15C000243
10093/28/15C000186

Transform:

To aggregate this date by month, you must extract the month value from the Date column:

derive type:single value: DATEFORMAT(Date, 'MMM') as:'month_Date'

You should now have a new column with three-letter month abbreviations. You can use the following aggregation to gather the sum of one customer's orders for each month:

pivot value: ANY(CustId),SUM(Qty) group: month_Date limit:1

Results: 

month_Dateany_CustIdsum_Qty
JanC0001127
FebC0002164
MarC0006211

See Also for ANY Function:

 

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