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

Choose Elasticsearch for complex text searches, but use databases for structured queries.

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

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

An inverted index helps search engines quickly find documents containing specific terms.

Elasticsearch fuzzy search allows finding results even with typos in queries.

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

B-Trees help databases find data quickly without scanning every row.

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

Filters check conditions without affecting relevance, while queries do.

Elasticsearch distributes search queries across shards to find and retrieve results quickly.

A document in Elasticsearch isn't searchable right after it's saved due to the refresh process.

You can update Elasticsearch indices without downtime using alias switching.

Elasticsearch aliases allow zero-downtime switching between indices for applications.