Break Up the Pipeline Structure to Reach a Nearly Optimal End-to-End Latency

Query optimization is still problematic in the commercial database system because database optimizers sometimes choose a bad execution plan with a several-fold difference in latency from the optimal one. In this paper, we design a new dynamic optimization strategy called Blala, which takes advantage of runtime statistics. Integrating Blala into PostgreSQL, we have a 2x speedup for total end-to-end latency on Join Order Benchmark and achieve near-optimal latency by comparing with the optimal execution plan. Our finding reveals that breaking up the static pipeline between database optimizer and executor can benefit the query processing and greatly reduce end-to-end latency.