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Add cache plugin and tiered cache documentation (#6708)
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* Adding documentation for cache plugin and tiered cache

Signed-off-by: Sagar Upadhyaya <sagar.upadhyaya.121@gmail.com>

* Adding tiered cache github link and fixing typos

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* Refactor tiered cache doc

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* Doc review

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* Review comments

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* Add plugin instructions

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* Renamed topic to caching

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* Apply suggestions from code review

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* Update _search-plugins/caching/index.md

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* Update _search-plugins/caching/index.md

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---------

Signed-off-by: Sagar Upadhyaya <sagar.upadhyaya.121@gmail.com>
Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>
Signed-off-by: kolchfa-aws <105444904+kolchfa-aws@users.noreply.github.com>
Co-authored-by: Fanit Kolchina <kolchfa@amazon.com>
Co-authored-by: kolchfa-aws <105444904+kolchfa-aws@users.noreply.github.com>
Co-authored-by: Nathan Bower <nbower@amazon.com>
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32 changes: 32 additions & 0 deletions _search-plugins/caching/index.md
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---
layout: default
title: Caching
parent: Improving search performance
has_children: true
nav_order: 100
---

# Caching

OpenSearch relies heavily on different on-heap cache types to accelerate data retrieval, providing significant improvement in search latencies. However, cache size is limited by the amount of memory available on a node. If you are processing a larger dataset that can potentially be cached, the cache size limit causes a lot of cache evictions and misses. The increasing number of evictions impacts performance because OpenSearch needs to process the query again, causing high resource consumption.

Prior to version 2.13, OpenSearch supported the following on-heap cache types:

- **Request cache**: Caches the local results on each shard. This allows frequently used (and potentially resource-heavy) search requests to return results almost instantly.
- **Query cache**: The shard-level query cache caches common data from similar queries. The query cache is more granular than the request cache and can cache data that is reused in different queries.
- **Field data cache**: The field data cache contains field data and global ordinals, which are both used to support aggregations on certain field types.

## Additional cache stores
**Introduced 2.13**
{: .label .label-purple }

This is an experimental feature and is not recommended for use in a production environment. For updates on the progress of the feature or if you want to leave feedback, see the associated [GitHub issue](https://github.com/opensearch-project/OpenSearch/issues/10024).
{: .warning}

In addition to existing OpenSearch custom on-heap cache stores, cache plugins provide the following cache stores:

- **Disk cache**: This cache stores the precomputed result of a query on disk. You can use a disk cache to cache much larger datasets, provided that the disk latencies are acceptable.
- **Tiered cache**: This is a multi-level cache, in which each tier has its own characteristics and performance levels. For example, a tiered cache can contain on-heap and disk tiers. By combining different tiers, you can achieve a balance between cache performance and size. To learn more, see [Tiered cache]({{site.url}}{{site.baseurl}}/search-plugins/caching/tiered-cache/).

In OpenSearch 2.13, the request cache is integrated with cache plugins. You can use a tiered or disk cache as a request-level cache.
{: .note}
82 changes: 82 additions & 0 deletions _search-plugins/caching/tiered-cache.md
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---
layout: default
title: Tiered cache
parent: Caching
grand_parent: Improving search performance
nav_order: 10
---

# Tiered cache

This is an experimental feature and is not recommended for use in a production environment. For updates on the progress of the feature or if you want to leave feedback, see the associated [GitHub issue](https://github.com/opensearch-project/OpenSearch/issues/10024).
{: .warning}

A tiered cache is a multi-level cache, in which each tier has its own characteristics and performance levels. By combining different tiers, you can achieve a balance between cache performance and size.

## Types of tiered caches

OpenSearch 2.13 provides an implementation of _tiered spillover cache_. This implementation spills the evicted items from upper to lower tiers. The upper tier is smaller in size but offers better latency, like the on-heap tier. The lower tier is larger in size but is slower in terms of latency compared to the upper tier. A disk cache is an example of a lower tier. OpenSearch 2.13 offers on-heap and disk tiers.

## Enabling a tiered cache

To enable a tiered cache, configure the following setting:

```yaml
opensearch.experimental.feature.pluggable.caching.enabled: true
```
{% include copy.html %}
For more information about ways to enable experimental features, see [Experimental feature flags]({{site.url}}{{site.baseurl}}/install-and-configure/configuring-opensearch/experimental/).
## Installing required plugins
A tiered cache provides a way to plug in any disk or on-heap tier implementation. You can install the plugins you intend to use in the tiered cache. As of OpenSearch 2.13, the available cache plugin is the `cache-ehcache` plugin. This plugin provides a disk cache implementation to use within a tiered cache as a disk tier.

A tiered cache will fail to initialize if the `cache-ehcache` plugin is not installed or disk cache properties are not set.
{: .warning}

## Tiered cache settings

In OpenSearch 2.13, a request cache can use a tiered cache. To begin, configure the following settings in the `opensearch.yml` file.

### Cache store name

Set the cache store name to `tiered_spillover` to use the OpenSearch-provided tiered spillover cache implementation:

```yaml
indices.request.cache.store.name: tiered_spillover: true
```
{% include copy.html %}

### Setting on-heap and disk store tiers

The `opensearch_onheap` setting is the built-in on-heap cache available in OpenSearch. The `ehcache_disk` setting is the disk cache implementation from [Ehcache](https://www.ehcache.org/). This requires installing the `cache-ehcache` plugin:

```yaml
indices.request.cache.tiered_spillover.onheap.store.name: opensearch_onheap
indices.request.cache.tiered_spillover.disk.store.name: ehcache_disk
```
{% include copy.html %}

For more information about installing non-bundled plugins, see [Additional plugins]({{site.url}}{{site.baseurl}}/install-and-configure/plugins/#additional-plugins).

### Configuring on-heap and disk stores

The following table lists the cache store settings for the `opensearch_onheap` store.

Setting | Default | Description
:--- | :--- | :---
`indices.request.cache.opensearch_onheap.size` | 1% of the heap | The size of the on-heap cache. Optional.
`indices.request.cache.opensearch_onheap.expire` | `MAX_VALUE` (disabled) | Specify a time-to-live (TTL) for the cached results. Optional.

The following table lists the disk cache store settings for the `ehcache_disk` store.

Setting | Default | Description
:--- | :--- | :---
`indices.request.cache.ehcache_disk.max_size_in_bytes` | `1073741824` (1 GB) | Defines the size of the disk cache. Optional.
`indices.request.cache.ehcache_disk.storage.path` | `""` | Defines the storage path for the disk cache. Required.
`indices.request.cache.ehcache_disk.expire_after_access` | `MAX_VALUE` (disabled) | Specify a time-to-live (TTL) for the cached results. Optional.
`indices.request.cache.ehcache_disk.alias` | `ehcacheDiskCache#INDICES_REQUEST_CACHE` (this is an example of request cache) | Specify an alias for the disk cache. Optional.
`indices.request.cache.ehcache_disk.segments` | `16` | Defines the number of segments the disk cache is separated into. Used for concurrency. Optional.
`indices.request.cache.ehcache_disk.concurrency` | `1` | Defines the number of distinct write queues created for the disk store, where a group of segments share a write queue. Optional.

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