Finding and Processing 6GB Typesense Book Search Data

Christopher had trouble importing 2.1M documents into Typesense due to memory errors. Jason clarified the system requirements, explaining the correlation between RAM and dataset size, and ways to tackle the issue. They both also discussed database-like query options.

kopach experienced slow indexing and crashes with Typesense. The community suggested to use batch import and check the server's resources. Improvements were made but additional support was needed for special characters and multi-search queries.

Ethan questioned about dataset size limits and data types for Typesense. Jason clarified that as long as the dataset fits the RAM, Typesense works, also adding that Typesense supports only JSONL.

Miguel experienced performance issues when using Typesense for large datasets. Jason suggested performance improvements made to Typesense since then and directed them to specific server-side parameters for better handling. Miguel agreed to try again.

A asked about Typesense's storage type and configuration possibilities. Jason shared that they use SSDs and suggested NVMe SSDs for high-availability instances. They discussed server resources needed for specific user cases and briefly touched on DDoS protection via Cloudflare.