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

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

Filters check conditions without affecting relevance, while queries do.

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

Elasticsearch offers three main autocomplete strategies, each with unique benefits and trade-offs.

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

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

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

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

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