Any concept.
clear in 60 seconds.

Elasticsearch's function_score combines text relevance with business signals for better rankings.

Elasticsearch ranks search results using BM25 based on relevance scoring.

Elasticsearch rescoring improves search result rankings using a two-stage process.

BM25 and field boosting help Elasticsearch rank search results based on relevance.

SLIs measure service performance, SLOs set reliability targets, and SLAs are customer agreements.

Search engines collect, index, retrieve, and rank documents to provide relevant results.

Tokenization and analyzers help search engines process and match text effectively.

Elasticsearch Hybrid Search combines keyword and semantic searches for better results.

Stemming and normalization help search engines match various word forms for better results.

Elasticsearch uses semantic search to find relevant documents based on meaning, not just keywords.

Filters check conditions without affecting relevance, while queries do.

matchIndex tracks what each follower has, while commitIndex shows what is committed.