Debugging Missing Results in a Multistage Search Pipeline
A reader searches a library catalog for a book the library definitely owns. The request succeeds, latency looks normal, and the results page is full of plausible alternatives. The expected book is missing.
The ranking model is the obvious suspect. But tweaking scores cannot help if the book never reaches the model. It might be absent from the serving index. Retrieval might cut it off at a candidate limit. A filter might reject it on a technicality. Or the page might lose it during assembly. Each explanation needs different evidence and a different fix.
The argument of this piece: before you tune anything, find the first stage where your candidate stopped progressing. Everything else follows from that.
A good score in a report can be misleading here. A book that would have ranked first still cannot appear if it was never in the ranking input. Counterfactual scores do not describe...
Copyright of this story solely belongs to hackernoon.com. To see the full text click HERE
