Selecting indexing algorithms for automated embedding database generation

Abstract

An online system uses benchmarking tests to identify indexing algorithms for an embedding database. To perform these benchmarking tests, the online system receives a set of parameters for configuring an embedding database. For example, the parameters may include a performance parameter and a latency parameter. The online system generates algorithm scores for a set of candidate indexing algorithms based on the parameters. Specifically, the online system tests each of the candidate indexing algorithms by generating a testing database based on a subset of the entries for the full database and by performing benchmarking tests on the testing database. The online system uses these tests to compute performance metrics for each candidate indexing algorithm and uses those performance metrics to compute an algorithm score for each indexing algorithm. The online system uses the computed algorithm scores to select an indexing algorithm for the embedding database.