Vespa Product Updates, August 2019: BM25 Rank Feature, Searchable Parent References, Tensor Summary Features, and Metrics Export
In the recent Vespa product update, we mentioned Large Machine Learning Models, Multithreaded Disk Index Fusion, Ideal State Optimizations, and Feeding Improvements. Largely developed by Yahoo engineers, Vespa is an open source big data processing and serving engine. It’s in use by many products, such as Yahoo News, Yahoo Sports, Yahoo Finance, and the Verizon Media Ad Platform. Thanks to feedback and contributions from the community, Vespa continues to grow.
This month, we’re excited to share the following feature updates with you:
BM25 Rank Feature
The BM25 rank feature implements the Okapi BM25 ranking function and is a great candidate to use in a first phase ranking function when you’re ranking text documents. Read more.
Searchable Reference Attribute
Tensor in Summary Features
To export metrics out of Vespa, you can now use the new node metric interface. Aliasing metric names is possible and metrics are assigned to a namespace. This simplifies integration with monitoring products like CloudWatch and Prometheus. Learn more about this update.