Recursively query for all linked documents in CosmosDB - azure-cosmosdb

Question

We've built a Document schema where job documents are uniquely identified by an Id property, and represent their link to a parent by a ParentJobId property.
For example:
{
"Type": "Request",
"StateName": "Success",
"id": "4365b7ec-6eee-468a-94f6-ab65d6434611",
"ParentJobId": null
},
{
"Type": "Machine",
"StateName": "ChildJobFailed",
"id": "27040208-add5-97e4-6bd2-d991de73c9b5",
"ParentJobId": "4365b7ec-6eee-468a-94f6-ab65d6434611"
},
{
"Type": "Application",
"StateName": "Error",
"id": "7ef36990-c321-81dd-a0c7-3b04fd64c86f",
"ParentJobId": "27040208-add5-97e4-6bd2-d991de73c9b5"
}
How can I query for all documents that are related to the root parent job?

Answer 1

There is no way in CosmosDB to do that in a single query. You could, of course recursively walk the tree with multiple round trips. You could even do it in one round trip to a stored procedure that you wrote that did multiple requests.
However, I've found that the best way to model hierarchies (trees) for fast retrieval in NoSQL databases is as an array containing a materialized path. Look at this example:
documents = [
{id: 'A', hierarchy: [1, 2, 3]},
{id: 'B', hierarchy: [1, 2, 4]},
{id: 'C', hierarchy: [5]},
{id: 'D', hierarchy: [1, 6]},
]
"A" is "in" Project 3 whose parent is Project 2, whose parent is Project 1. "B" is "in" Project 4 whose parent is Project 2 which still has Project 1 as its parent. Project 5 is another root Project like Project 1; and "D" is "in" Project 6 which is a child of project 1.
Now send in a query like this:
SELECT * FROM c WHERE ARRAY_CONTAINS(c.hierarchy, 1)
It will return documents A, B, and D. Try:
SELECT * FROM c WHERE ARRAY_CONTAINS(c.hierarchy, 2)
It will just return documents A, and B.
One word of caution though, I don't know how performant this approach is in DocumentDB which I don't think allows indexes on array fields. Maybe one of the DocumentDB product managers that monitor Stack Overflow can chime in on this.
This approach is commonly used with NoSQL databases like CouchDB and MongoDB (combining materialized path and array of ancestors) and even SQL databases supporting array types like Postgres.