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jedarden 0de5f01d32 P2.2: Pluggable MergeStrategy trait + RRF scoring + full benchmark re-run
- Extract MergeStrategy trait with merge()/name() methods
- Implement RrfStrategy with configurable k (default 60)
- Refactor scatter_gather_search to accept &dyn MergeStrategy
- Add RRF simulation to benchmark script (simulate_distributed_search_rrf)
- Re-run full benchmark (3989 queries) with updated comparison reports
- Add topology unit tests (NodeId, NodeStatus, Node helpers)

Benchmark results:
  Score-based merge: avg tau = 0.798 (FAIL, common-term tau = 0.152)
  RRF merge:         avg tau = 0.134 (FAIL, rank-only loses score signal)

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-04-19 02:07:39 -04:00
.beads P1.5: Implement scatter module with covering-set construction + dispatch trait 2026-04-19 00:21:58 -04:00
.cargo P1.5: Implement scatter module with covering-set construction + dispatch trait 2026-04-19 00:20:29 -04:00
charts/miroir P3.5: Add values.schema.json constraint for replicas>1 requires Redis 2026-04-18 23:44:15 -04:00
crates P2.2: Pluggable MergeStrategy trait + RRF scoring + full benchmark re-run 2026-04-19 02:07:39 -04:00
docs P12.OP4: Add confidence intervals to score comparability benchmark 2026-04-19 00:07:42 -04:00
tests/benches/score-comparability P2.2: Pluggable MergeStrategy trait + RRF scoring + full benchmark re-run 2026-04-19 02:07:39 -04:00
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Cargo.lock P1: Finalize core routing — tighten uniformity bounds, fix warnings, update deps 2026-04-19 01:04:29 -04:00
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Miroir

Multi-node Index Replication Orchestrator, Integrated Rebalancing

Miroir is a RAID-like orchestration layer for Meilisearch. It stripes a large index across a fleet of small-RAM Meilisearch nodes with a configurable replication factor, fans out search queries across all shards, and rebalances shard assignments when nodes are added or removed — all using the Meilisearch Community Edition.

The Problem

Meilisearch loads its entire index into memory-mapped LMDB files. A large index that exceeds a single server's available RAM cannot run on that server. The Enterprise Edition's native sharding is gated behind a commercial license. Miroir solves this without it.

How It Works

Client
  │
  ▼
Miroir Orchestrator
  ├── Write path: hash(doc_id) → assign to shard → write to R replicas
  ├── Read path:  scatter query to all shards → gather → merge ranked results
  └── Rebalance: on node add/remove → recompute assignments → migrate minimum shards

Meilisearch Nodes (N instances, each holding a subset of shards)
  node-0   node-1   node-2   ...   node-N

Replication Factor

Analogous to software RAID — configurable per deployment:

RF Redundancy Node failures tolerated Capacity
1 None (stripe only) 0 100% of fleet
2 One replica 1 per shard group 50% of fleet
3 Two replicas 2 per shard group 33% of fleet

Key Components

  • Orchestrator — proxy that handles shard routing, scatter-gather, result merging, and topology management
  • Shard router — consistent hash function (Rendezvous/HRW) mapping document IDs to node assignments; minimal reshuffling on topology change
  • Rebalancer — on node add/remove, recomputes assignments and migrates only the shards that changed owners; surviving replicas serve reads during rebuild
  • Result merger — normalizes and merges ranked result sets from multiple shards into a single coherent response

Status

Design phase. See docs/ for architecture detail.