Multiple Joins In CouchDB - join

Question

I am currently trying to figure out if CouchDB is suitable for my use-case and if so, how. I have a situation similar to the following:
First set of documents (let's call them companies):
{
"_id" : 1,
"name" : "Foo"
}
{
"_id" : 2,
"name" : "Bar"
}
{
"_id" : 3,
"name" : "Baz"
}
Second set of documents (let's call them projects):
{
"_id" : 4,
"name" : "FooProject1",
"company" : 1
}
{
"_id" : 5,
"name" : "FooProject2",
"company" : 1
}
...
{
"_id" : 100,
"name" : "BazProject2",
"company" : 3
}
Third set of documents (let's call them incidents):
{
"_id" : "300",
"project" : 4,
"description" : "...",
"cost" : 200
}
{
"_id" : "301",
"project" : 4,
"description" : "...",
"cost" : 400
}
{
"_id" : "302",
"project" : 4,
"description" : "...",
"cost" : 500
}
...
So in short every company has multiple projects, and every project can have multiple incidents. One reason I model the data is, that I come mainly from a SQL background, so the modelling may be completely unsuitable. The second reason is, that I would like to add new incidents very easily by just using the REST-API provided by couchdb. So the incidents have to be single documents.
However, I now would like to get a view that would allow me to calculate the total cost for each company. I can easily define a view using map-reduce and linked documents which get's me the total amount per project. However once I am at the project level I cannot get any further to the level of the company.
Is this possible at all using couchDb? This kind of summarising data sounds like a perfect use case for map-reduce. In SQL I would just do a three-table join, but it seems like in couchDb the best I can get is two-table joins.

Answer 1

As mentioned you cannot do joins in CouchDb but this isn't a limitation, this is an invitation to both think about your problems and approach them differently. The correct way to do this in CouchDb is to define data structures called for example : IncidentReference composed of :
The project id
And the company id
That way your data would look like :
{
"_id" : "301",
"project" : 4,
"description" : "...",
"cost" : 400,
"reference" : {
"projectId" : 1,
"companyId" : 2
}
}
This is just fine. Once you have that, you can play with Map/Reduce to achieve whatever you want easily. Generally speaking, you need to think about the way you are going to query your data.