Mongodb array query woes

You might be able to do the INSERT into Payemnts_To_Charges in one SQL statement, but I'm not sure it would be worth it. It seems like this would be easier to build, debug, and maintain in procedural code. Something like this:

CREATE TABLE Payments (PaymentId Number(10), Amount Number(6,2));
CREATE TABLE Charges  (ChargeID Number(10), Amount Number(6,2));
CREATE TABLE Payments_To_Charges 
   (PaymentID Number(10), ChargeID Number(10), Amount Number(6,2));

INSERT INTO Payments VALUES (1,4);
INSERT INTO Payments VALUES (2,4);

INSERT INTO Charges VALUES (1,2);
INSERT INTO Charges VALUES (2,5);
INSERT INTO Charges VALUES (3,6);
INSERT INTO Charges VALUES (4,4);
INSERT INTO Charges VALUES (5,10);

Declare
   vPaymentAmount Payments.Amount%Type;
   vAppliedAmount Payments_To_Charges.Amount%Type;
Begin
   For vPayment In (SELECT PaymentID, Amount FROM Payments) Loop
      vPaymentAmount := vPayment.Amount;      
      For vCharge In (
            SELECT ChargeID, Amount FROM
            (
               SELECT ChargeID, Amount - 
                  NVL((SELECT SUM(Amount) FROM Payments_To_Charges pc 
                       WHERE pc.ChargeID = c.ChargeID),0) Amount
               FROM Charges c            
            ) WHERE Amount > 0
         ) Loop
         vAppliedAmount := LEAST(vPaymentAmount, vCharge.Amount);
         INSERT INTO Payments_To_Charges (PaymentID, ChargeID, Amount)
            VALUES (vPayment.PaymentID, vCharge.ChargeID, vAppliedAmount);
         vPaymentAmount := vPaymentAmount - vAppliedAmount;
         If (vPaymentAmount = 0) Then
            Exit;
         End If;
      End Loop;
   End Loop;
End;
/

SELECT * FROM Payments_To_Charges;

Update:

remaining_balance is the issue. You can't reference the aliased value in the WHERE clause. You could either make the query a sub-query and add that condition on a higher level or change remaining_balance in the WHERE clause for (charges.amount - transactions.total_paid).

Some thoughts....

Typically one does not want to store pieces of tightly interrelated information in different systems. The chances of things getting out of sync is significant and now instead of one problem on your hands you have two. One thing you can do with Mongo though is use it to pipeline your data in or data out. My preference is to keep everything in PostgreSQL to the extent this is possible. However, I would note that doing so really requires expert knowledge of PostgreSQL programming and is not for shops unwilling to dedicate to using advanced features. I see a somewhat different set of options than you do. Since my preference is not something I see listed I will give it to you.

You can probably separate your metadata into common data, data required for classes, and document data. In this regard you would have a general catalog table with the basic common information plus one table per class. In this table you would have an hstore, json, or xml field which would store the rest of the data along with columns where you are storing data that must be constrained significantly. This would reduce what you need to put in these tables per class, but would allow you to leverage constraints however you like. The three options have different issues and are worth considering separately:

hstore is relatively limited but also used by a lot of people. It isn't extremely new but it only is a key/value store, and is incapable of nested data structures, unlike json and xml.

json is quite new and doesn't really do a lot right now. This doesn't mean you can't do a lot with it, but you aren't going to do a lot out of the box. If you do you can expect to do a significant amount of programming, probably in plv8js or, if you want to stick with older environments, plperlu or plpython. json is better supported in 9.3 though at least in current development snapshots, so when that version is released things will get better.

xml is the best supported of the three, with the most features, and the longest support history. Then again, it is XML.....

However if you do decide to go with Mongo and PostgreSQL together, note that PostgreSQL supports 2 phase commit meaning you can run the write operations, then issue PREPARE TRANSACTION and if this succeeds do your atomic writes in Mongo. If that succeeds you can then COMMIT in PostgreSQL.