Managing Caches
Elasticsearch uses two main types of cache: field data and query cache.
1. Field Data Cache: Converts fields for searching values (e.g., HTTP status codes) and is stored in HEAP memory. To avoid excessive memory consumption:
- Limit usage with ‘indices.fielddata.cache.size’.
- Use doc values where possible, though they are not supported for text fields.
2. Query Cache: Stores frequently accessed query results. Like field data, limit this cache with indices.queries.cache.size to avoid memory overuse.
By carefully managing these caches, you can ensure efficient memory usage and maintain high performance.
Elasticsearch Performance Tuning
As your Elasticsearch cluster grows and your usage evolves, you might notice a decline in performance. This can stem from various factors, including changes in data volume, query complexity, and how the cluster is utilized. To maintain optimal performance, it’s crucial to set up monitoring and alerting systems that can preemptively highlight issues, allowing you to manage maintenance effectively.
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