v4.20.5
atlasia-ma/MoulSotv4.20.5Sep 15, 2026by swilly22
Upgrading?
AI Summary
This release addresses critical bugs in graph traversal and index population. It resolves an under-counting issue with parallel edges in `count(*)` queries and fixes a potential crash or data loss scenario in index population involving unsynced delta matrices.
Key Highlights
- Fixed `count(*)` to correctly handle parallel edges by detecting star aggregations.
- Resolved index population issues where rows could be skipped or the process could hang on unsynced delta matrices.
- Improved performance by releasing the read lock between edge batches.
- Ensured plan-cache safety for the new reference-map builder logic.
Full Release Notes
🐛 Bug fixes `count(*)` under-counted parallel edges `MATCH (a)-[e]->(b) RETURN count(*)` returned 1 instead of 3 for three parallel edges. Because `count(*)` references no entity, the edge alias was left unreferenced, the algebraic expression dropped the edge, and the traversal emitted a single record per (src, dest) pair — collapsing parallel edges and under-counting. The reference-map builder now detects a star aggregation and keeps the pattern's named entities referenced so their multiplicity is preserved (scoped to user aliases and * projections only; plan-cache safe). - PR: #2660 Index population could skip rows or hang on unsynced delta matrices When a label or relation matrix held unsynced delta-plus entries, index population resumed batched scans at [last_row, MAX) while the iterators drained the main matrix before yielding delta-plus — permanently skipping delta-plus rows below the resume point (nodes), and spinning forever re-scanning the same range (edges, once a masking tautology was removed). Population now merges the main matrix and delta-plus in strict row-major order, making batch resume safe. Also releases the read lock between edge batches (~1.5s write stall on 1M edges → ~5ms). - PR: #2812 - Fixes: #2811
Related Repositories
rasbt/LLMs-from-scratch★ 107,082
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
lyogavin/airllm★ 40,233
AirLLM 2.8T LLM inference with single 4GB GPU
NirDiamant/RAG_Techniques★ 29,962
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
microsoft/OmniParser★ 25,539
A simple screen parsing tool towards pure vision based GUI agent
karpathy/nn-zero-to-hero★ 24,908
Neural Networks: Zero to Hero