performance-improvements

Reduce query latency and improve indexing throughput by measuring real workloads, profiling hot paths, and applying targeted optimizations with strict baselining and before/after measurements.

Profiling memory usage and hot paths for production-like workloads requires capturing baseline latency, throughput, and memory metrics, then applying changes one at a time with regression coverage to ensure durability.

Yes, optimize indexing speed while preserving durability by ensuring WAL, manifest, and fsync semantics remain intact during targeted optimizations and regression coverage.

Set up controlled profiling by defining workload baselines on representative benchmarks, capturing real workload metrics, and enforcing one-change-at-a-time experimentation with strict baseline measurements.

Query latency regresses when multiple changes are applied simultaneously without baselining; enforce one-change-at-a-time experimentation with before/after measurements to isolate the impact of each optimization.