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Module query Future

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Query Module - Future Enhancements

Scope

  • Reliability and performance hardening of parser, optimizer, execution, and federation paths.
  • Safety and governance improvements for multi-model query processing.
  • Operational hardening for long-running and distributed query workloads.

Design Constraints

  • Query execution must remain fail-safe under malformed input and partial dependency failures (Target: ongoing)
  • Resource limits must be enforced deterministically without data corruption (Target: Q4 2026)
  • Optimization and JIT paths must preserve semantic equivalence to interpreter execution (Target: ongoing)
  • Federation must maintain bounded memory and timeout behavior under degraded peers (Target: Q4 2026)
  • Public query APIs and compatibility layers remain additive-only in active major versions (Target: ongoing)

Required Interfaces

Interface Consumer Notes
AQLParser query frontends parsing safety and bounded depth behavior
QueryOptimizer planner statistics-aware plan generation with stable fallbacks
QueryEngine execute entry points server/runtime access checks and resource limit enforcement
QueryFederation / CrossClusterFederation distributed execution bounded fan-out and partial-failure handling
VectorizedExecutionEngine analytical execution paths predictable memory and throughput envelopes
QueryCompiler hot-query optimization correctness-preserving JIT fallback behavior

Implementation Notes

Safety and Validation Hardening

Priority: High Target: Q3-Q4 2026

  • Continue parser/translator edge-case hardening and maintain bounded-depth guarantees.
  • Keep execute entry-point access checks and validation behavior consistent.
  • Strengthen error-path observability without exposing sensitive internals.

Optimizer and Runtime Hardening

Priority: High Target: Q4 2026

  • Improve resilience of plan selection under partial/stale stats.
  • Expand deterministic regression coverage for rewrite, adaptive, and runtime re-optimization paths.
  • Tighten JIT/interpreter equivalence and fallback telemetry.

Federation Hardening

Priority: Medium Target: Q4 2026

  • Expand degraded-peer handling (timeouts, partial results, retries) with bounded resource usage.
  • Validate shard routing and pruning behavior under failure injection.
  • Harden protocol and payload guards for cross-cluster calls.

Advanced Query Feature Hardening

Priority: Medium Target: Q1 2027

  • Mature approximate query processing for broader production scenarios.
  • Strengthen ML-assisted optimization with strict fallback contracts.
  • Expand continuous-query backpressure and persistence safety guarantees.

Test Strategy

  • Focused security/reliability regressions for parser, translator, and execute paths.
  • Federation and cross-cluster fault-injection matrix with bounded-memory assertions.
  • Performance regressions for vectorized execution, optimizer latency, and JIT hot paths.
  • Equivalence tests comparing optimized/JIT outputs with interpreter baseline.

Performance Targets

  • Maintain stable planner and execution latency envelopes under representative workloads.
  • Keep vectorized/federated regressions inside release budget thresholds.
  • Keep optimization overhead bounded under high query concurrency.

Security / Reliability

  • Fail closed on invalid critical query state and unsafe execution preconditions.
  • Preserve deterministic cancellation/timeout behavior.
  • Prevent unbounded growth in long-running and distributed execution paths.

Risk Backlog

Risk 1: Optimizer drift under stale statistics

Severity: High Signal: Plan quality degrades under changing data distributions. Mitigation: stronger fallback rules, regression packs, and telemetry gates.

Risk 2: Federation degradation under unstable peers

Severity: Medium Signal: Partial failures cause latency spikes or memory pressure. Mitigation: tighter timeouts, bounded accumulation, and retry policy hardening.

Risk 3: Long-running query resource pressure

Severity: Medium Signal: sustained streaming/continuous workloads push queue and memory limits. Mitigation: backpressure controls, bounded queues, and persistence safeguards.

Adoption Scenarios

Scenario A: Safety-first lane

  • Prioritize parser/execute-path safety and access-control invariants.
  • Promote only with full regression pass for critical safety controls.

Scenario B: Performance-first lane

  • Prioritize optimizer/vectorized/JIT throughput and latency hardening.
  • Promote only with benchmark and equivalence gate pass.

Scenario C: Federation-first lane

  • Prioritize distributed query resilience and bounded-failure behavior.
  • Promote only with fault-injection gate pass.

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