EmbeddingGemma 2: an open, lightweight multimodal embedding model
deepmind.google·6d ago
AI Engineering
Lobsters·Jul 22·5 min read
Unranked, systemd, crawls
TL;DR
A new indexing system for wide domains has significantly improved web crawling efficiency, cutting crawl times in half and reducing operational costs. The migration to systemd from Docker Compose has resolved several issues in production.
✦ Why It Matters
Consider migrating to systemd for improved performance and reduced operational headaches in your own projects.
Key Takeaways
- Migrate to systemd for improved stability and performance.
- Implement unranked queries to reduce execution time significantly.
- Create dedicated partitions for specific types of crawls.
- Optimize resource allocation by freeing up threads for complex queries.
How It Works
The transition to systemd allows for better management of services and resources, particularly in a NUMA architecture. By using systemd's capabilities, such as health checks and automatic restarts, the search engine can maintain stability while efficiently handling multiple processes.
The unranked query endpoint simplifies the query execution pipeline, focusing on term intersections without unnecessary ranking, which drastically reduces processing time.