Your Search Service as a Composable Function #bbuzz
summary
A Scala-based proxy models the search pipeline as a composition of a Reader monad and Future to keep server state minimal and treat requests as pure functions. It orchestrates backends—Solr, Elasticsearch, a key-value store (Arizona), and ML inference services—by converting queries into an intermediate boolean-retrieval tree, querying appropriate services (including an online learned ranker), and combining or retrying results to return ranked search results.
AI-written summary · about
chapters (8)
- 0:00Introduction
- 5:49Functional programming
- 10:15Search building blocks
- 15:50Service composition
- 23:07Modeling and ranking
- 28:06Query pipeline optimization
- 33:10Testing and deployment
- 37:15Live demo & Q&A
related talks
24mExtending OpenSearch: A Practical Guide To Building Custom Plugins
41mImplementing Piped Processing Language in OpenSearch Via Apache Calcite
38mMonolith vs. Microservices
01h 04mDDDamn good!
30mBlink: Improvements to Flink & its application in Alibaba Search
14mJourney of Building a Scalable, Domain-Agnostic Order Management System
16mSponsored Keynote: OpenSearch at Atlassian Scale
29mApplying (D)DDD and CQ(R)S to Cloud Architectures