RethinkDB: How to do recursive joins on three tables? - rethinkdb

Question

I am developing a platform with JSON API using Python Flask. In some cases I need to join three tables. How to join tables with a array of IDs gave me some guidance but I need a solution beyond it.
Let's assume we have three tables for a messaging app.
Accounts
Conversations
Messages
Message Readers
Accounts table snippet
{
"id": "account111",
"name": "John Doe",
},
Conversations table snippet
{
"id": "conversation111",
"to": ["account111", "account222", "account333"], // accounts who are participating the conversation
"subject": "RethinkDB",
}
Messages table snippet
{
"id": "message111",
"text": "I love how RethinkDB does joins.",
"from": "account111", // accounts who is the author of the message
"conversation": "conversation111"
}
Message Readers table snippet
{
"id": "messagereader111",
"message": "message111",
"reader": "account111",
}
My question is "What's the magic query to get the document below when I receive a get request on an account document with id="account111"?"
{
"id": "account111",
"name": John Doe,
"conversations": [ // 2) Join account table with conversations
{
"id": "conversation111",
"name": "RethinkDB",
"to": [ // 3) Join conversations table with accounts
{
"id": "account111",
"name": "John Doe",
},
{
"id": "account222",
"name": "Bobby Zoya",
},
{
"id": "account333",
"name": "Maya Bee",
},
]
"messages": [ // 4) Join conversations with messages
{
"id": "message111",
"text": "I love how RethinkDB does joins.",
"from": { // 5) Join messages with accounts
"id": "account111",
"name": "John Doe",
},
"message_readers": [
{
"name": "John Doe",
"id": "account111",
}
],
},
],
},
],
}
Any guidance or advice would be fantastic. JavaScript or Python code would be awesome.

Answer 1

I had a hard time understanding what you want (you have multiple documents with the id 111), but I think this is the query you are looking for
Python query:
r.table("accounts").map(lambda account:
account.merge({
"conversations": r.table("conversations").filter(lambda conversation:
conversation["to"].contains(account["id"])).coerce_to("array").map(lambda conversation:
conversation.merge({
"to": conversation["to"].map(lambda account:
r.table("accounts").get(account)).pluck(["id", "name",]).coerce_to("array"),
"messages": r.table("messages").filter(lambda message:
message["conversation"] == conversation["id"]).coerce_to("array").map(lambda message:
message.merge({
"from": r.table("accounts").get(message["from"]).pluck(["id", "name",]),
"readers": r.table("message_readers").filter(lambda message_reader:
message["id"] == message_reader["message"]).coerce_to("array").order_by(r.desc("created_on")),
})).order_by(r.desc("created_on"))
})).order_by(r.desc("modified_on"))
})).order_by("id").run(db_connection)