controller: sketch planner and agent config - #96
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SketchParams is now a tagged enum with per-sketch-type variants:
- DDSketch { relative_accuracy, quantiles }
- KLL { k, quantiles }
- HLL { precision }
- CountSketch { epsilon, delta }
- CountMinSketch { rows, cols, metric_name }
Each variant carries only its relevant fields — no more bag of
unrelated defaults. DEFAULT_QUANTILE_GRID constant replaces the
hardcoded vec![…] in default_sketch_params_with_quantiles.
Also fixes 3 test failures from the PR #96 rebase: KLL/HLL processor
key casing, all_sketch_types test table, transmit_sketch default.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
zzylol
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SketchParams is now a tagged enum with per-sketch-type variants:
- DDSketch { relative_accuracy, quantiles }
- KLL { k, quantiles }
- HLL { precision }
- CountSketch { epsilon, delta }
- CountMinSketch { rows, cols, metric_name }
Each variant carries only its relevant fields — no more bag of
unrelated defaults. DEFAULT_QUANTILE_GRID constant replaces the
hardcoded vec![…] in default_sketch_params_with_quantiles.
Also fixes 3 test failures from the PR #96 rebase: KLL/HLL processor
key casing, all_sketch_types test table, transmit_sketch default.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
SketchParams is now a tagged enum with per-sketch-type variants:
- DDSketch { relative_accuracy, quantiles }
- KLL { k, quantiles }
- HLL { precision }
- CountSketch { epsilon, delta }
- CountMinSketch { rows, cols, metric_name }
Each variant carries only its relevant fields — no more bag of
unrelated defaults. DEFAULT_QUANTILE_GRID constant replaces the
hardcoded vec![…] in default_sketch_params_with_quantiles.
Also fixes 3 test failures from the PR #96 rebase: KLL/HLL processor
key casing, all_sketch_types test table, transmit_sketch default.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
All sketch parameter defaults are now loaded from a YAML config file at startup via CONTROLLER_SKETCH_DEFAULTS env var (falls back to compiled-in defaults when the file is absent or malformed). Configurable parameters: - quantile_grid: fallback quantile φ values - ddsketch.relative_accuracy - kll.min_k - hll.precision_coarse, precision_fine, precision_threshold - count_sketch.epsilon, count_sketch.delta - count_min_sketch.rows, cols, metric_name SketchDefaults struct flows: main.rs → CostModelPlanner → RulesPlanner → build_sketch_params(). The old DEFAULT_CS_EPSILON / DEFAULT_CS_DELTA / DEFAULT_QUANTILE_GRID constants are replaced by the struct's Default impl. Includes sketch_defaults.yaml example with all compiled-in defaults. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
…ch Go factories SketchType::Display now outputs the exact component type strings that the Go processor factories register (HLL, KLL, countmin) — eliminating the separate collector_processor_component_id() function. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
zzylol
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Rebased on latest main. Dropped stale controller changes (already on main via PRs #96, #116, #117, #119). Only benchmark tooling remains: - replay.py: replay DEBS dataset through OTel collector - run.py: orchestrate benchmark runs - scrape.py: collect Prometheus metrics during run - analyze.py: parse benchmark results - compare.py: compare sketch results to ground truth - summarize.py: generate summary tables - ground_truth/: ground truth computation for accuracy checking Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
zzylol
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Apr 4, 2026
Rebased on latest main. Dropped stale controller changes (already on main via PRs #96, #116, #117, #119). Only benchmark tooling remains: - replay.py: replay DEBS dataset through OTel collector - run.py: orchestrate benchmark runs - scrape.py: collect Prometheus metrics during run - analyze.py: parse benchmark results - compare.py: compare sketch results to ground truth - summarize.py: generate summary tables - ground_truth/: ground truth computation for accuracy checking Co-authored-by: zz_y <zeyingz@umd.edu> Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
SieDeta
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Apr 17, 2026
* controller: sketch planner and agent config
* refactor: SketchParams flat struct → per-type enum
SketchParams is now a tagged enum with per-sketch-type variants:
- DDSketch { relative_accuracy, quantiles }
- KLL { k, quantiles }
- HLL { precision }
- CountSketch { epsilon, delta }
- CountMinSketch { rows, cols, metric_name }
Each variant carries only its relevant fields — no more bag of
unrelated defaults. DEFAULT_QUANTILE_GRID constant replaces the
hardcoded vec![…] in default_sketch_params_with_quantiles.
Also fixes 3 test failures from the PR #96 rebase: KLL/HLL processor
key casing, all_sketch_types test table, transmit_sketch default.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* feat: YAML-configurable sketch defaults (SketchDefaults)
All sketch parameter defaults are now loaded from a YAML config file
at startup via CONTROLLER_SKETCH_DEFAULTS env var (falls back to
compiled-in defaults when the file is absent or malformed).
Configurable parameters:
- quantile_grid: fallback quantile φ values
- ddsketch.relative_accuracy
- kll.min_k
- hll.precision_coarse, precision_fine, precision_threshold
- count_sketch.epsilon, count_sketch.delta
- count_min_sketch.rows, cols, metric_name
SketchDefaults struct flows: main.rs → CostModelPlanner →
RulesPlanner → build_sketch_params(). The old DEFAULT_CS_EPSILON /
DEFAULT_CS_DELTA / DEFAULT_QUANTILE_GRID constants are replaced by
the struct's Default impl.
Includes sketch_defaults.yaml example with all compiled-in defaults.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* refactor: remove collector_processor_component_id, fix Display to match Go factories
SketchType::Display now outputs the exact component type strings that
the Go processor factories register (HLL, KLL, countmin) — eliminating
the separate collector_processor_component_id() function.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
---------
Co-authored-by: zz_y <zeyingz@umd.edu>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
SieDeta
pushed a commit
that referenced
this pull request
Apr 17, 2026
Rebased on latest main. Dropped stale controller changes (already on main via PRs #96, #116, #117, #119). Only benchmark tooling remains: - replay.py: replay DEBS dataset through OTel collector - run.py: orchestrate benchmark runs - scrape.py: collect Prometheus metrics during run - analyze.py: parse benchmark results - compare.py: compare sketch results to ground truth - summarize.py: generate summary tables - ground_truth/: ground truth computation for accuracy checking Co-authored-by: zz_y <zeyingz@umd.edu> Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Summary
Controller changes so the planner and OpAMP agent can emit collector configs that match DEBS benchmark workloads: sketch family selection, parameters, optional
sketch_type_override, and delta-related fields where applicable.Files
controller/src/config/agent.rs— Maps internalSketchTypeto collector component identifiers in generated YAML; delta transmission / threshold blocks for supported sketches; HLL and KLL handling (e.g. KLL delta validation, HLL precision notes).controller/src/planner/rules.rs— Chooses sketch type from workload hints (e.g. quantile vs cardinality vs frequency priority); default parameters for DDSketch, KLL, HLL precision bands, CountSketch / CountMinSketch rows, columns, epsilon/delta; window vs batch strategy from latency SLA.controller/src/types.rs—sketch_type_overrideon workloads; extendedSketchParams(CountSketch epsilon/delta, CountMinmetric_name);AgentCollectorConfigfields for delta transmission aligned with the cost model path.Context
Stacked on
debs_benchmarking(docs + download script). Downstream PR addsdatasets_eval/debs/benchmark/and exercisesPOST /api/v1/planwithmetric_name,aggregations, andtime_window: "5m"as described inDEBS_2022/03_benchmark_methodology.md.Testing
Run existing controller unit tests after merge; no change to HTTP API shape beyond richer config payloads where sketches apply.