# 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 | Layer | Page | What it’s for | | --- | --- | --- | | ⭐ Proof | [WFGY Recognition Map](/recognition/README.md) | External citations, integrations, and ecosystem proof | | ⚙️ Engine | [WFGY 1.0](/legacy/README.md) | Original PDF tension engine and early logic sketch (legacy reference) | | ⚙️ Engine | [WFGY 2.0](/core/README.md) | Production tension kernel for RAG and agent systems | | ⚙️ Engine | [WFGY 3.0](/TensionUniverse/EventHorizon/README.md) | TXT based Singularity tension engine (131 S class set) | | 🗺️ Map | [Problem Map 1.0](/ProblemMap/README.md) | Flagship 16 problem RAG failure taxonomy and fix map | | 🗺️ Map | [Problem Map 2.0](/ProblemMap/wfgy-rag-16-problem-map-global-debug-card.md) | Global Debug Card for RAG and agent pipeline diagnosis | | 🗺️ Map | [Problem Map 3.0](/ProblemMap/wfgy-ai-problem-map-troubleshooting-atlas.md) | Global AI troubleshooting atlas and failure pattern map | | 🧰 App | [TXT OS](/OS/README.md) | .txt semantic OS with fast bootstrap | | 🧰 App | [Blah Blah Blah](/OS/BlahBlahBlah/README.md) | Abstract and paradox Q&A built on TXT OS | | 🧰 App | [Blur Blur Blur](/OS/BlurBlurBlur/README.md) | Text to image generation with semantic control | | 🏡 Onboarding | [Starter Village](/StarterVillage/README.md) | Guided entry point for new users | If this repository helped, starring it improves discovery so more builders can find the docs and tools. [![GitHub Repo stars](https://img.shields.io/github/stars/onestardao/WFGY?style=social)](https://github.com/onestardao/WFGY)