How Can I Query In-Memory Java Objects Efficiently Using SQL-Like Queries?

Querying Object Collections in Java Like SQL or Criteria Queries

Q: Querying In-Memory Object Collections with SQL-Like Queries

Imagine you have a sizeable collection of in-memory objects. To efficiently retrieve specific objects matching complex criteria, filtering is a common approach. However, as the collection grows or the number of criteria increases, this method's time complexity degrades.

A: Indexing and Set Theory for Efficient Queries

Instead of filtering, consider using indexing and set theory for enhanced query performance.

Indexing Objects

Create indexes on object fields that will be used in queries. An index maps field values to sets of objects. For example, if you have Car objects with a color field, an index on Car.color would enable retrieving blue cars in O(1) time:

'blue' -> {Car{name=blue_car_1, color='blue'}, Car{name=blue_car_2, color='blue'}}

Standing Query Index

Alternatively, use a standing query index. Register queries with an intelligent collection. As objects are added or removed, the collection automatically tests each object against the registered queries and maintains sets of objects matching each query. This enables O(1) retrieval of objects matching any query.

CQEngine: A NoSQL Query Engine for Java Collections

CQEngine implements these ideas and provides a SQL-like query syntax for Java collections without iteration overhead. It supports advanced features like query caching and temporal queries.

Conclusion

By leveraging indexing and set theory, you can query in-memory object collections with SQL-like queries with superior performance compared to filtering, especially for large collections and complex queries.

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