Use case for financial data

Question

Hi All,
I've a question about potential use case for Oracle spatial. Data structures are following:
Clients
Account (have a dimension of balance, can be zero or above zero)
Client to account relationship
E.g.
Client C1 is a borrower to Account A1 (balance = 0)
Client C1 is a co borrower to Account A2 (balance > 0)
Client C2 is a co borrower to Account A1 (balance > 0)
Client C3 is a co borrower to Account A3 (balance > 0)
Currently, database is modeled as a set of three tables, e.g.
Client
ID
DATA
Account
ID
DATA
BALANCE
CLIENT_TO_ACCOUNT
CLIENT_ID
RELATIONSHIP (E.g borrower)
ACCOUNT_ID
Business limitations:
We are not interested in independent graphs for which all accounts have balance = 0 (let's call it inactive graph), however we might need occasionally query it
Users are interested in vertices/edges with account which have balance = 0, but linked (up to level N) to active account for analysis purposes
There is no well defined root (e.g. there can be 2 or more clients which are co borrowers to same account)
99% of queries will be against active graphs
Graphs are mutable, e.g. new relationships (edges) may be created/deleted during the day
Users are potentially interested in free navigation in whole independent graph, starting from root.
Root is determined by certain business rule
Need to process active graphs daily as bulk
Problems which I am trying to solve:
Limit the amount of data which may need to be processed - based on the analysis of current system, we only need 5% of data + some delta for 99% processing
Make sure performance does not degrade with time as we get more historical (processed data) - we can not deleted accounts with balance = 0 as potentially new relationship may arrive with new accounts with balance > 0
Current solution that I am thinking of :
Artificially partition the data universe as active and inactive graphs. All indexes would be local to two partitions.
E.g.
GROUP
GROUP_ID PK
ACTIVE_FLAG (partition key)
CLIENT
GROUP_ID (PARTITION BY FK TO GROUP)
ACCOUT
GROUP_ID (PARTITION BY FK TO GROUP)
CLIENT_TO_ACCOUNT
GROUP_ID (PARTITION BY FK TO GROUP)
The issues I am seeing right now:
1. Graphs(groups) may be potentially unlimited, so I will need a artificially limit the size using some dividing algorithms - leading to
2. Graphs(groups) may need to be joined or divided
3. Graphs(groups) will have to be activated/deactivated - e.g. moved to different partitions.
4. Data loading, activation/deactivation algorithms are not simple
So I am thinking about Oracle Spatial (Network) to model this problem.
Questions:
1) Can I model this problem using Oracle Spatial?
2) Will I gain any performance improvement?
3) Is there any explanation or white paper on how to do this for this particular type of problem?
4) Will the solution based on Oracle Spatial solve the problems outlined above?
5) Will my solution (without using Oracle spatial) work at all? Or there are some fundamental issues..
Thanks you!

Answer 1

Either add a LOV to the JobID attribute definition in the VO (if the JobID will be editable) or simply add the job description to the select statement (join to the job table) as a reference attribute