elasticsearch

An unassigned shard in Elasticsearch is typically caused by node failures, insufficient disk space, or shard count limits. You can diagnose the exact reason using the cluster allocation explain API and resolve it via node recovery or configuration adjustments.

Build complex search queries in Elasticsearch by combining `bool`, `match`, and `term` clauses within the Query DSL. This approach allows you to construct precise filtering and relevance scoring logic for your search-driven applications.

Manage data retention in Elasticsearch by configuring Index Lifecycle Management (ILM) policies. ILM automates the rolling, shrinking, and deletion of indices based on age or size, ensuring efficient long-term data management for log analytics.

Design explicit index mappings in Elasticsearch by defining field types and analyzers prior to data ingestion. This optimizes search performance and enables features like search-as-you-type by preventing dynamic mapping conflicts.

Aggregations in Elasticsearch work by grouping data into buckets and calculating metrics like counts or averages. You can use `terms`, `date_histogram`, and `pipeline` aggregations to build powerful data summaries directly within your search queries.

Use Elasticsearch aliases for zero-downtime reindexing by pointing an alias to a new index once the reindexing process completes. This allows seamless transitions without updating application query logic or interrupting search availability.