In my previous posts I tried to transcribe the things that were not too obvious for me when I initially started working on Kusto Query Language. Continuing with the same thought, this time I’m going to share a few of the approaches that can be taken to aggregate the data. Let’s consider the below input data: let demoData = datatable(Environment: string, Version: int , BugCount: int ) [ "dev" ,1, 1, "test" ,1, 1, "prod" ,1, 1, "dev" ,2, 2, "test" ,2, 0, "dev" ,3, 2, "test" ,3, 0, "prod" ,2,2, ]; Description Get the average number of bugs falling under each category. Expected Output There are several approaches to achieve this. Approach 1 - Using Partition Operator Partition operator first partitions the input data with defined criteria and then combines all the results. demoData| partition by Environment (summarize ceiling(avg(BugCount)) by Environment); Appr
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