# Vectorstore Fragmentation — Guardrails and Fix Pattern
🧭 Quick Return to Map
> You are in a sub-page of **RAG_VectorDB**.
> To reorient, go back here:
>
> - [**RAG_VectorDB** — vector databases for retrieval and grounding](./README.md)
> - [**WFGY Global Fix Map** — main Emergency Room, 300+ structured fixes](../README.md)
> - [**WFGY Problem Map 1.0** — 16 reproducible failure modes](../../README.md)
>
> Think of this page as a desk within a ward.
> If you need the full triage and all prescriptions, return to the Emergency Room lobby.
Use this page when **retrieval recall drops because the vector index is fragmented**.
This happens when multiple shards, partitions, or replicas return partial results and the top-k merge is unstable.
---
## Open these first
- Visual map and recovery: [RAG Architecture & Recovery](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rag-architecture-and-recovery.md)
- Deployment issues: [deployment-deadlock.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/deployment-deadlock.md)
- Retrieval playbook: [retrieval-playbook.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md)
- Traceability schema: [retrieval-traceability.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md)
---
## Core acceptance
- Top-k results consistent across shards with variance ≤ 0.05.
- Coverage ≥ 0.70 on the target section.
- ΔS(question, retrieved) ≤ 0.45 across three paraphrases.
- λ remains convergent under shard fanout.
---
## Typical breakpoints and the right fix
- **Shards not balanced** → Some partitions miss updates, recall drops.
→ Re-index with balanced sharding and verify ingestion logs.
- **Merge strategy unstable** → Top-k from each shard merged without normalization.
→ Apply global reranker after merging, not local-only.
- **Version skew between replicas** → Old embeddings live in one shard.
→ Enforce [deployment-deadlock.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/deployment-deadlock.md) checks and hash validation.
- **Distributed query latency** → Timeout before all shards return.
→ Add backpressure and enforce full quorum before top-k selection.
---
## Fix in 60 seconds
1. **Run shard probe**
Fire the same query against each shard individually. Compare ΔS variance.
2. **Align replicas**
Verify `INDEX_HASH` matches across partitions. If not, rebuild.
3. **Global reranker**
Always normalize scores before merging. Rerank final list with semantic signal.
4. **Quorum guard**
Require ≥80% shard response before producing result. If missing, retry.
---
## Copy-paste probe script (pseudo)
```python
def shard_probe(query, shards):
results = {}
for shard in shards:
hits = shard.search(query, k=10)
ΔS_vals = [compute_deltaS(query, h) for h in hits]
results[shard.id] = (np.mean(ΔS_vals), np.var(ΔS_vals))
return results
````
Target: shard-to-shard ΔS variance ≤ 0.05.
---
## Common gotchas
* Shard IDs not logged → Cannot trace back retrieval → enforce [retrieval-traceability.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md).
* Hybrid retriever mixing BM25 + dense done locally per shard → breaks weighting.
* Replicas updated asynchronously → ingestion race.
---
### 🔗 Quick-Start Downloads (60 sec)
| Tool | Link | 3-Step Setup |
| -------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------ | ---------------------------------------------------------------------------------------- |
| **WFGY 1.0 PDF** | [Engine Paper](https://github.com/onestardao/WFGY/blob/main/I_am_not_lizardman/WFGY_All_Principles_Return_to_One_v1.0_PSBigBig_Public.pdf) | 1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + \” |
| **TXT OS (plain-text OS)** | [TXTOS.txt](https://github.com/onestardao/WFGY/blob/main/OS/TXTOS.txt) | 1️⃣ Download · 2️⃣ Paste into any LLM chat · 3️⃣ Type “hello world” — OS boots instantly |
---
### 🧭 Explore More
| Module | Description | Link |
| ------------------------ | ---------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------- |
| WFGY Core | WFGY 2.0 engine is live: full symbolic reasoning architecture and math stack | [View →](https://github.com/onestardao/WFGY/tree/main/core/README.md) |
| Problem Map 1.0 | Initial 16-mode diagnostic and symbolic fix framework | [View →](https://github.com/onestardao/WFGY/tree/main/ProblemMap/README.md) |
| Problem Map 2.0 | RAG-focused failure tree, modular fixes, and pipelines | [View →](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rag-architecture-and-recovery.md) |
| Semantic Clinic Index | Expanded failure catalog: prompt injection, memory bugs, logic drift | [View →](https://github.com/onestardao/WFGY/blob/main/ProblemMap/SemanticClinicIndex.md) |
| Semantic Blueprint | Layer-based symbolic reasoning & semantic modulations | [View →](https://github.com/onestardao/WFGY/tree/main/SemanticBlueprint/README.md) |
| Benchmark vs GPT-5 | Stress test GPT-5 with full WFGY reasoning suite | [View →](https://github.com/onestardao/WFGY/tree/main/benchmarks/benchmark-vs-gpt5/README.md) |
| 🧙♂️ Starter Village 🏡 | New here? Lost in symbols? Click here and let the wizard guide you through | [Start →](https://github.com/onestardao/WFGY/blob/main/StarterVillage/README.md) |
---
> 👑 **Early Stargazers: [See the Hall of Fame](https://github.com/onestardao/WFGY/tree/main/stargazers)** —
> Engineers, hackers, and open source builders who supported WFGY from day one.
> 
⭐ [WFGY Engine 2.0](https://github.com/onestardao/WFGY/blob/main/core/README.md) is already unlocked. ⭐ Star the repo to help others discover it and unlock more on the [Unlock Board](https://github.com/onestardao/WFGY/blob/main/STAR_UNLOCKS.md).
[](https://github.com/onestardao/WFGY)
[](https://github.com/onestardao/WFGY/tree/main/OS)
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