Is there any way to use KQL to query a large local file (10k rows) such as Excel, CSV etc. alongside data hosted in Kusto (Azure Data Explorer)?

Here is my scenario: I extensively use KQL to explore data hosted in Kusto (Azure Data Explorer) clusters. Mostly these explorations are very dynamic and in one-off scenarios to investigate situations.

For some data, I just have Excel and CSV files that I want to join with Kusto data. I know I could do this with Pandas, but I'm specifically asking if there's any way to do it with KQL, preferably without setting up a cluster and ingesting the data into a Kusto table.

CodePudding user response：

There are a few ways this can be done, but there is one requirement which is that the data needs to be accessible from the Kusto cluster, for your scenario, the files need to be in Azure Storage. The lightest approach is using the externaldata operator, but you can also set up an external table.

Also please note that you can get your own free cluster to do this processing, to create it go to http://aka.ms/kustofree