Reputation: 13814
I have documents that look like this:
[
{
"id": "e1bb9b05-11f2-459e-37d3-9bf9fed56c96",
"name": "bulbasaur",
"type": [
{
"slot": 2,
"type": {
"url": "https://pokeapi.co/api/v2/type/4/",
"name": "poison"
}
},
{
"slot": 1,
"type": {
"url": "https://pokeapi.co/api/v2/type/12/",
"name": "grass"
}
}
]
}
]
The following query is about as close as I can get, but not quite the output I'm hoping for.
Query
SELECT
c.id, c.name, t.type.name as type
FROM
c
JOIN
t IN c.types
WHERE
c.name = "bulbasaur"
Result
[
{
"id": "e1bb9b05-11f2-459e-37d3-9bf9fed56c96",
"name": "bulbasaur",
"type": "poison"
},
{
"id": "e1bb9b05-11f2-459e-37d3-9bf9fed56c96",
"name": "bulbasaur",
"type": "grass"
}
]
Hoping for
[
{
"id": "e1bb9b05-11f2-459e-37d3-9bf9fed56c96",
"name": "bulbasaur",
"types": ["poison", "grass"]
}
]
Is this possible with a DocumentDB query?
Upvotes: 0
Views: 583
Reputation: 8003
This requires use of DocumentDB UDFs, which can extend query functionality with custom transformations. For example, register this:
function unwindTypeArray(value) {
var result = { id: value.id, name: value.name, types: []};
for (var idx in value.type) {
console.log(idx);
var name = value.type[idx].type.name;
result.types.push(name);
}
return result;
}
Then call it inside a query like:
SELECT udf.unwindTypeArray(c) FROM c WHERE c.name = "bulbasaur"
Upvotes: 1