Cache Management | Performance Tuning | Elasticsearch Tutorial

Introduction

Cache management plays a crucial role in enhancing the performance of Elasticsearch. By effectively managing caches, you can significantly reduce the latency and increase the throughput of your Elasticsearch queries. This tutorial will guide you through the basics of cache management in Elasticsearch, including the types of caches available, configuration options, and examples of how to use them.

Types of Caches in Elasticsearch

Elasticsearch uses several types of caches to improve query performance:

Node Query Cache: Caches the results of queries for faster retrieval.
Field Data Cache: Caches field data used for sorting and aggregations.
Shard Request Cache: Caches the results of search requests at the shard level.

Configuring Cache Settings

Elasticsearch allows you to configure cache settings to optimize performance based on your specific use case. Below are some common settings you can configure:

Node Query Cache

To enable or disable the node query cache, you can update the Elasticsearch configuration file:

# Enable Node Query Cache
indices.queries.cache.enabled: true

Field Data Cache

Field data cache settings can be configured to control memory usage and eviction policies:

# Set Field Data Cache Size
indices.fielddata.cache.size: 40%

Shard Request Cache

To configure shard request cache settings, you can use the following configuration:

# Enable Shard Request Cache
indices.requests.cache.enable: true

Using Caches in Queries

You can control cache usage in your queries by specifying cache-related parameters. Below are examples of how to use these parameters:

Using the Query Cache

To use the query cache in a search request, set the request_cache parameter to true:

POST /my_index/_search
{
  "query": {
    "match": {
      "message": "Elasticsearch"
    }
  },
  "request_cache": true
}

Clearing Caches

You may need to clear caches to free up memory or after making significant changes to your data. Use the following API to clear caches:

POST /_cache/clear
{
  "query": true,
  "fielddata": true,
  "request": true
}

Monitoring Cache Usage

Monitoring cache usage helps you understand the effectiveness of your cache settings and make necessary adjustments. Use the following APIs to monitor cache usage:

Query Cache Statistics

Retrieve query cache statistics using the following API:

GET /_stats/query_cache

Field Data Cache Statistics

Retrieve field data cache statistics using the following API:

GET /_stats/fielddata

Request Cache Statistics

Retrieve request cache statistics using the following API:

GET /_stats/request_cache

{ "_shards": { "total": 1, "successful": 1, "failed": 0 }, "_all": { "primaries": { "request_cache": { "memory_size_in_bytes": 0, "evictions": 0, "hit_count": 0, "miss_count": 0 } }, "total": { "request_cache": { "memory_size_in_bytes": 0, "evictions": 0, "hit_count": 0, "miss_count": 0 } } } }

Conclusion

Effective cache management is essential for optimizing the performance of Elasticsearch. By understanding the different types of caches available and how to configure and monitor them, you can ensure that your Elasticsearch cluster delivers fast and efficient query responses.

Cache Management in Elasticsearch