Building a Tree and Running Recursive Queries in Kusto (Azure Data Explorer)
Kusto, Azure Data Explorer, is a powerful query language and data exploration tool. One of its strengths lies in its ability to handle complex data structures, including hierarchical relationships. This article explores how to build a tree structure from flat data and efficiently navigate it using Kusto's recursive query capabilities.
The Problem: Navigating a Hierarchical Structure
Imagine you have a table representing a file system hierarchy. Each entry contains a file or folder name and its parent folder. Your task is to build a complete tree representation of this structure and traverse it to find all files within a specific directory.
Scenario and Code Example
Let's say we have a table named FileSystem with the following data:
| Name | Parent |
|---|---|
| Root | NULL |
| FolderA | Root |
| FolderB | Root |
| File1 | FolderA |
| File2 | FolderA |
| File3 | FolderB |
The Parent column stores the name of the parent folder, with NULL indicating the root.
Here's a Kusto query to build the tree:
let FileSystem = datatable(Name:string, Parent:string) [
"Root", "",
"FolderA", "Root",
"FolderB", "Root",
"File1", "FolderA",
"File2", "FolderA",
"File3", "FolderB"
];
let RecursiveTree =
let RecursiveFunction = (Name:string)
{
let Children = FileSystem | where Parent == Name;
let ChildNodes = Children | extend Path = strcat(Name, "/", Name) | project Name, Parent, Path, Children = RecursiveFunction(Name) | as table;
let RootNode = if (isempty(Children)) then [Name, Parent, Name, []] else ChildNodes;
RootNode
};
RecursiveFunction("Root");
RecursiveTree
This query uses a recursive function RecursiveFunction to build the tree. It takes the name of a folder as input and:
- Finds children: Uses
whereclause to find all entries with the givenNameas theirParent. - Constructs child nodes: Extends the current node with a
Pathproperty, constructs a nested table with recursively calledRecursiveFunctionfor children, and projects the desired columns. - Handles base case: If there are no children (empty
Children), returns a single node with itsPath. Otherwise, returns theChildNodestable.
Finally, the RecursiveTree variable holds the complete tree structure.
Analysis and Insights
- Performance: Recursive queries can be computationally expensive, especially for large datasets. Kusto optimizes these queries, but for performance-critical scenarios, consider alternative data structures or indexing techniques.
- Clarity: The code provides a clear example of a recursive solution for building a tree. Using named variables (
FileSystem,RecursiveFunction) and nested table construction enhances readability. - Flexibility: The
RecursiveTreevariable can be further manipulated with other Kusto operators. You can filter, search, or even modify the tree structure as needed.
Additional Value
To demonstrate the benefits of this approach, let's see how we can use the generated tree to find all files within a specific directory:
let Tree = /* RecursiveTree query from above */;
let TargetDirectory = "FolderA";
Tree | where Path contains TargetDirectory | extend Files = array_filter(Children, (c) => !isempty(c.Children)) | project Name, Files
This query finds all nodes within the tree that contain "FolderA" in their Path. It then extracts all child nodes that have no further children (files) and presents them as a list under the respective directory.
References and Resources
- Kusto Language Reference: https://docs.microsoft.com/en-us/azure/data-explorer/kusto/query/
- Kusto Recursive Functions: https://docs.microsoft.com/en-us/azure/data-explorer/kusto/query/functions/recursive
This article provides a comprehensive guide to building a tree and running recursive queries in Kusto. By understanding these concepts, you can effectively navigate and analyze hierarchical data structures using the power of Kusto's query language.
