9c7d5ab9ee
Extends SqliteTaskStore with full CRUD operations for: - Table 8: canaries (upsert, get, list, delete) - Table 9: canary_runs (insert with auto-prune to run_history_limit) - Table 10: cdc_cursors (upsert, get, list by sink) - Table 11: tenant_map (insert, get by BLOB key, delete) - Table 12: rollover_policies (upsert, get, list, delete) - Table 13: search_ui_config (upsert, get, delete) - Table 14: admin_sessions (insert, get, revoke, delete_expired) Key implementation details: - prune_tasks uses subquery for LIMIT support (SQLite doesn't support LIMIT in DELETE) - canary_runs auto-prune keeps only N most recent runs per canary_id - tenant_map.api_key_hash is a 32-byte BLOB (raw sha256) - admin_sessions has expires_at index for lazy eviction - All bool fields stored as INTEGER (0/1) with conversion on read/write Adds 12 comprehensive unit tests covering: - CRUD round-trip for each table - Auto-prune logic for canary_runs - Nullable fields (tenant_map.group_id, admin_sessions.user_agent/source_ip) - Composite PK behavior (cdc_cursors, canary_runs) - prune_tasks batch deletion with status filter Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |
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| tests/benches/score-comparability | ||
| .editorconfig | ||
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| .needle-predispatch-sha | ||
| Cargo.lock | ||
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| CHANGELOG.md | ||
| clippy.toml | ||
| LICENSE | ||
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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.