Skip to main content

ROLLINGKTHLARGESTUNIQUE Function

Computes the rolling unique kth largest value forward or backward of the current row. Inputs can be Integer, Decimal, or Datetime.

For purposes of this calculation, two instances of the same value are treated at one value for k. So, if your dataset contains four rows with column values 10, 9, 9, and 8, then KTHLARGESTUNIQUE returns 9 for k=2 and 8 for k=3.

ROLLINGKTHLARGESTUNIQUE computes the KTHLARGESTUNIQUE value across a defined window of values within a column.

  • If an input value is missing or null, it is not factored in the computation. For example, for the first row in the dataset, the rolling calculation of previous values is undefined.

  • The row from which to extract a value is determined by the order in which the rows are organized based on the order parameter.

  • If you are working on a randomly generated sample of your dataset, the values that you see for this function might not correspond to the values that are generated on the full dataset during job execution.

  • Inputs:

    • Required column name

    • Required kth value, which is a positive integer

    • Two optional integer parameters that determine the window backward and forward of the current row. The default integer parameter values are -1 and 0, which computes the rolling function from the current row back to the first row of the dataset.

  • This function works with the Window transform. See Window Transform.

For more information on a non-rolling version of this function, see KTHLARGESTUNIQUE Function.

Wrangle vs. SQL: This function is part of Wrangle, a proprietary data transformation language. Wrangle is not SQL. For more information, see Wrangle Language.

Basic Usage

Column example:

rollingkthlargestunique(myCol, 2)

Output: Returns the rolling second largest unique value in the myCol column from the first row of the dataset to the current one.

Rows before example:

rollingkthlargestunique(myNumber, 2, 3)

Output: Returns the rolling second largest unique value of the current row and the two previous row values in the myNumber column.

Rows before and after example:

rollingkthlargestunique(myNumber, 4, 3, 2)

Output: Returns the rolling fourth largest unique value of the two previous row values, the current row value, and the two rows after the current one in the myNumber column.

Syntax and Arguments

rollingkthlargestunique(col_ref, rowsBefore_integer, rowsAfter_integer) order: order_col [group: group_col]

Argument

Required?

Data Type

Description

col_ref

Y

string

Name of column whose values are applied to the function

k_integer

Y

integer (positive)

The ranking of the unique value to extract from the source column

rowsBefore_integer

N

integer

Number of rows before the current one to include in the computation

rowsAfter_integer

N

integer

Number of rows after the current one to include in the computation

For more information on the order and group parameters, see Window Transform.

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

col_ref

Name of the column whose values are used to compute the function. Inputs must be Integer, Decimal, or Datetime values.

Nota

If the input is in Datetime type, the output is in unixtime format. You can wrap these outputs in the DATEFORMAT function to output the results in the appropriate Datetime format. See DATEFORMAT Function.

  • Multiple columns and wildcards are not supported.

Usage Notes:

Required?

Data Type

Example Value

Yes

String (column reference)

myColumn

k_integer

Integer representing the ranking of the unique value to extract from the source column. Duplicate values are treated as a single value for purposes of this function's calculation.

Nota

The value for k must be an integer between 1 and 1,000 inclusive.

  • k=1 represents the maximum value in the column.

  • If k is greater than or equal to the number of values in the column, the minimum value is returned.

  • Missing and null values are not factored into the ranking of k.

Usage Notes:

Required?

Data Type

Example Value

Yes

Integer (positive)

4

rowsBefore_integer, rowsAfter_integer

Integers representing the number of rows before or after the current one from which to compute the rolling function, including the current row. For example, if the first value is 5, the current row and the four rows after it are used in the computation. Negative values for rowsAfter_integer compute the rolling function from rows preceding the current one.

  • rowBefore=1 generates the current row value only.

  • rowBefore=-1 uses all rows preceding the current one.

  • If rowsAfter is not specified, then the value 0 is applied.

  • If a group parameter is applied, then these parameter values should be no more than the maximum number of rows in the groups.

Usage Notes:

Required?

Data Type

Example Value

No

Integer

4

Examples

Suggerimento

For additional examples, see Common Tasks.

Example - ROLLINGKTHLARGEST functions

This example describes how to use rolling kthlargest functions for calculating ranking of values within a defined window of rows.

Functions:

Item

Description

ROLLINGKTHLARGEST Function

Computes the rolling kth largest value forward or backward of the current row. Inputs can be Integer, Decimal, or Datetime.

ROLLINGKTHLARGESTUNIQUE Function

Computes the rolling unique kth largest value forward or backward of the current row. Inputs can be Integer, Decimal, or Datetime.

ROWNUMBER Function

Generates a new column containing the row number as sorted by the order parameter and optionally grouped by the group parameter.

The following dataset contains daily counts of server restarts across three servers over the preceding week. High server restart counts can indicate poor server health. In this example, you are interested in knowing for each server the rolling highest and second highest count of restarts per server over the previous week.

Source:

Date

Server

Restarts

2/21/18

s01

4

2/21/18

s02

0

2/21/18

s03

0

2/22/18

s01

4

2/22/18

s02

1

2/22/18

s03

2

2/23/18

s01

2

2/23/18

s02

3

2/23/18

s03

4

2/24/18

s01

1

2/24/18

s02

0

2/24/18

s03

2

2/25/18

s01

5

2/25/18

s02

0

2/25/18

s03

4

2/26/18

s01

1

2/26/18

s02

2

2/26/18

s03

1

2/27/18

s01

1

2/27/18

s02

2

2/27/18

s03

2

Transformation:

First, you want to maintain the row information as a separate column. Since data is ordered already by the Date column, you can use the following:

Transformation Name

New formula

Parameter: Formula type

Single row formula

Parameter: Formula

ROWNUMBER()

Parameter: New column name

'entryId'

Use the following function to compute the rolling kth largest value of server restarts per server over the previous week. In this case, you can use the ROLLINGKTHLARGEST function, setting k=1. Uniqueness doesn't matter for calculating the highest value:

Transformation Name

New formula

Parameter: Formula type

Multiple row formula

Parameter: Formula

rollingkthlargest(Restarts, 1, 6, 0)

Parameter: Sort Rows by

Server

Parameter: Group Rows by

Server

Parameter: New column name

'rollingkthlargest_1'

Use the following function to compute the rolling second highest value. In this case, you can use ROLLINGKTHLARGESTUNIQUE:

Transformation Name

New formula

Parameter: Formula type

Multiple row formula

Parameter: Formula

rollingkthlargestunique(Restarts, 2, 6, 0)

Parameter: Sort Rows by

Server

Parameter: Group Rows by

Server

Parameter: New column name

'rollingKthLargestUnique_2'

Results:

entryId

Date

Server

Restarts

rollingKthLargestUnique_2

rollingkthlargest_Restarts

3

2/21/18

s02

0

0

0

6

2/22/18

s02

1

0

1

9

2/23/18

s02

3

1

3

12

2/24/18

s02

0

1

3

15

2/25/18

s02

0

1

3

18

2/26/18

s02

2

2

3

21

2/27/18

s02

2

2

3

4

2/21/18

s03

0

0

0

7

2/22/18

s03

2

0

2

10

2/23/18

s03

4

2

4

13

2/24/18

s03

2

2

4

16

2/25/18

s03

4

2

4

19

2/26/18

s03

1

2

4

22

2/27/18

s03

2

2

4

2

2/21/18

s01

4

4

4

5

2/22/18

s01

4

4

4

8

2/23/18

s01

2

2

4

11

2/24/18

s01

1

2

4

14

2/25/18

s01

5

4

5

17

2/26/18

s01

1

4

5

20

2/27/18

s01

1

4

5

In questa sezione: