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Elasticsearch mapping defines how fields are indexed and searched, with dynamic and explicit options.

You can update Elasticsearch indices without downtime using alias switching.

Elasticsearch index templates automatically apply settings to new indices based on patterns.

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

Elasticsearch uses shards for data distribution and replicas for redundancy.

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

The dual-write trap in Elasticsearch can cause data inconsistency during reindexing.

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

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

Elasticsearch ILM automates data management through defined lifecycle phases.

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

Kafka's assign() method allows manual control of partition assignments for consumers.

Elasticsearch ILM automates index management to reduce storage costs and meet data needs.