ALGORITHM ARTICLE
Deterministic Hadoop/Spark experiment planner
Problem. Partition reproducible cases and reconcile repeated evidence across workers.
Core idea. Stable case IDs and content hashes keep distribution separate from solver semantics.
Procedure
- Validate deterministic cases.
- Write stable JSON Lines partitions.
- Aggregate outcomes and compare repetition hashes.
Certificate. Case-set SHA-256, partition ledger and repetition match.
Data structures and API
from optfin_orlab import HadoopBenchmarkPlanner
planner = HadoopBenchmarkPlanner()Complexity. O(c log c) orchestration around solver cost
Limits. Distribution is not itself an optimality proof or speedup guarantee.
OPTFIN AUDIT CHECKS
What has to reconcile before this method is trusted.
- DefinitionProblem, objective, inputs and output are explicit.
- Data structureThe public API and canonical source path are identified.
- CorrectnessCase-set SHA-256, partition ledger and repetition match.
- ComplexityO(c log c) orchestration around solver cost
- Operational limitDistribution is not itself an optimality proof or speedup guarantee.
- ReproductionSource, executable test and evidence route remain linked.
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