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Hashing and Indexing

Scenario​

Imagine a rule engine that processes transactions and applies various rules based on transaction properties like type and amount.

Rules​

  • Rule 1: If the transaction is a "refund" and the amount is greater than $1000, flag for review.
  • Rule 2: If the transaction is a "purchase" and the amount is less than $50, apply a discount.
  • Rule 3: If the transaction is an "international transfer", perform currency conversion.

Using HashSet and Indexing for Efficient Rule Processing​

To efficiently process these rules, you can index them based on the transaction type. A HashSet or similar data structure can be used for quick lookups.

Implementation​

Index Creation​

  • Create a mapping of transaction types to rules
  • For each transaction type, you maintain a HashSet of rules applicable to that type

Rule Matching​

  • When a transaction comes in, you first determine its type.
  • Then, look up the set of rules associated with this type.
  • Iterate through this set and apply each rule to the transaction.

Example Code Structure​

class Rule {
    String type;
    Predicate<Transaction> condition;
    Action action;
}

Map<String, HashSet<Rule>> ruleIndex = new HashMap<>();

// Populate the index
ruleIndex.put("refund", new HashSet<>(Arrays.asList(rule1)));
ruleIndex.put("purchase", new HashSet<>(Arrays.asList(rule2)));
ruleIndex.put("international transfer", new HashSet<>(Arrays.asList(rule3)));

// Function to process a transaction
void processTransaction(Transaction transaction) {
    String type = transaction.getType();
    HashSet<Rule> applicableRules = ruleIndex.get(type);

    if (applicableRules != null) {
        for (Rule rule : applicableRules) {
            if (rule.condition.test(transaction)) {
                rule.action.execute(transaction);
            }
        }
    }
}

Explanation​

  • Data Structures: The ruleIndex is a HashMap where each key is a transaction type, and the value is a HashSet of rules. This structure allows for quick retrieval of rules based on transaction type.
  • Process Flow: When a transaction needs to be processed, the engine quickly identifies the subset of rules that apply to that transaction’s type, thus avoiding the need to evaluate every rule against every transaction.

Conclusion​

In rule engines, this approach of using hash-based structures and indexing significantly improves efficiency, especially when dealing with a large number of rules. It ensures that only a relevant subset of rules is considered for each transaction, reducing the computational overhead.