Qae2

Qae2, short for Query Analysis Engine 2, is a modular framework designed to optimize the execution of complex database queries. It is described in academic and industry research as a successor to earlier prototype work and as a platform that decouples query analysis from physical execution to enable cross-system optimization.

The architecture of Qae2 comprises three core components: a query analyzer, a cost-based planner, and an execution engine. The query analyzer parses SQL or other high-level query languages, applies semantic rewrites, and derives alternative logical plans. The planner evaluates these plans using statistics and cost models, producing an execution plan that balances factors such as I/O, CPU, memory, and parallelism. The execution engine carries out the plan, coordinating operators, data movement, and synchronization, with support for pluggable backends and data sources.

Qae2 emphasizes adaptive and rule-based optimization. It supports subquery unnesting, join reordering, common subexpression elimination, and materialized view integration, while allowing runtime feedback to refine estimates. It aims to work with both row-oriented and columnar stores and to leverage parallelism and data locality when available.

In practice, Qae2 has been explored primarily in research prototypes and in experimental deployments within data laboratories and vendor R&D programs. It has influenced ideas on modular query optimization, automatic plan generation, and cross-system cooperation, though it has not become a standard component of major commercial databases. Related concepts include adaptive query processing, cost-based optimization, and plan caching.