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

Functions:

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:

DateServerRestarts
2/21/18s014
2/21/18s020
2/21/18s030
2/22/18s014
2/22/18s021
2/22/18s032
2/23/18s012
2/23/18s023
2/23/18s034
2/24/18s011
2/24/18s020
2/24/18s032
2/25/18s015
2/25/18s020
2/25/18s034
2/26/18s011
2/26/18s022
2/26/18s031
2/27/18s011
2/27/18s022
2/27/18s032


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:

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:

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

Results:

entryIdDateServerRestartsrollingKthLargestUnique_2rollingkthlargest_Restarts
32/21/18s02000
62/22/18s02101
92/23/18s02313
122/24/18s02013
152/25/18s02013
182/26/18s02223
212/27/18s02223
42/21/18s03000
72/22/18s03202
102/23/18s03424
132/24/18s03224
162/25/18s03424
192/26/18s03124
222/27/18s03224
22/21/18s01444
52/22/18s01444
82/23/18s01224
112/24/18s01124
142/25/18s01545
172/26/18s01145
202/27/18s01145