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

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

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

Elasticsearch ranks search results using BM25 based on relevance scoring.

Elasticsearch offers two pagination methods: from & size for shallow pages and search_after for deep pages.

Elasticsearch aggregations help analyze data by grouping, calculating, and estimating values.

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

Deep pagination in Elasticsearch can slow down searches significantly, but there are efficient methods to handle it.

Elasticsearch aggregations help summarize data using metrics for calculations and buckets for grouping.

Optimizing Elasticsearch involves using filters, caching, and measuring performance.