Message-ID: <192768827.2047.1571797571444.JavaMail.daemon@e613c95ee270> Subject: Exported From Confluence MIME-Version: 1.0 Content-Type: multipart/related; boundary="----=_Part_2046_2127969694.1571797571444" ------=_Part_2046_2127969694.1571797571444 Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable Content-Location: file:///C:/exported.html RANK Function

RANK Function

Computes the rank of an ordered set of value within groups.= Tie values are assigned the same rank, and the next ranking is incremented= by the number of tie values.
• Rank values start at 1 and increment.

• Ranking order varies dependin= g on the data type of the source data. For more information, see Sort Order.

• You must use the = group and order parameters to def= ine the groups of records and the ordering column to which this transform i= s applied.

• This function works with the following transforms:
• This function assigns ranking values to match the total number of rows = in a group. For fewer discrete ranking values when ties are present, see&nb= sp;DENSERANK Function.

Basic Usage

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rank()

Ou= tput: Generates the new column, which contains the ranking of= mySales, grouped by the Salesman column.

Syntax

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rank() order: order_col group: group_col

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

For more information on syntax standards, see Language Documentation Syntax Notes<= /a>.

Examples=

Example - Rank Function= s

This example demonstrates the following two functions:

Source:

The following dataset contains lap times for three racers in a four-lap = race. Note that for some racers, there are tie values for lap times.

Runner Lap Time
Dave 1 72.2
Dave 2 73.31
Dave 3 72.2
Dave 4 70.85
Mark 1 71.73
Mark 2 71.73
Mark 3 72.99
Mark 4 70.63
Tom 1 74.43
Tom 2 70.71
Tom 3 71.02
Tom 4 72.98

Transformation:

You can apply the RANK() function to the Ti= me column, grouped by individual runner:

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=20 =20 =20 =20 =20 =20 =20 =20 =20 =20 =20 =20 =20 =20 =20 =20 =20 =20 =20
Transformation Name = Window RANK() Time Runner
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You can use the DENSERANK() function on the same colum= n, grouping by runner:

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=20 =20 =20 =20 =20 =20 =20 =20 =20 =20 =20 =20 =20 =20 =20 =20 =20 =20 =20
Transformation Name = Window DENSERANK() Runner Time
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Results:

After renaming the columns, you have the following output:

Runner Lap Time Rank Rank-Dense
Mark 4 70.63 1 1
Mark 1 71.73 2 2
Mark 2 71.73 2 2
Mark 3 72.99 4 3
Tom 2 70.71 1 1
Tom 3 71.02 2 2
Tom 4 72.98 3 3
Tom 1 74.43 4 4
Dave 4 70.85 1 1
Dave 1 72.2 2 2
Dave 3 72.2 2 2
Dave 2 73.31 4 3

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