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 a...
This blog is all about my technical learnings pertaining to LLM, OpenAI, Azure OpenAI, C#, Azure, Python, AI, ML, Visual Studio Code and many more.