Searchable snapshotsedit

Searchable snapshots let you reduce your operating costs by using snapshots for resiliency rather than maintaining replica shards within a cluster. When you mount an index from a snapshot as a searchable snapshot, Elasticsearch copies the index shards to local storage within the cluster. This ensures that search performance is comparable to searching any other index, and minimizes the need to access the snapshot repository. Should a node fail, shards of a searchable snapshot index are automatically recovered from the snapshot repository.

This can result in significant cost savings for less frequently searched data. With searchable snapshots, you no longer need an extra index shard copy to avoid data loss, potentially halving the node local storage capacity necessary for searching that data. Because searchable snapshots rely on the same snapshot mechanism you use for backups, they have a minimal impact on your snapshot repository storage costs.

Using searchable snapshotsedit

Searching a searchable snapshot index is the same as searching any other index. Search performance is comparable to regular indices because the shard data is copied onto nodes in the cluster when the searchable snapshot is mounted.

By default, searchable snapshot indices have no replicas. The underlying snapshot provides resilience and the query volume is expected to be low enough that a single shard copy will be sufficient. However, if you need to support a higher query volume, you can add replicas by adjusting the index.number_of_replicas index setting.

If a node fails and searchable snapshot shards need to be restored from the snapshot, there is a brief window of time while Elasticsearch allocates the shards to other nodes where the cluster health will not be green. Searches that hit these shards will fail or return partial results until the shards are reallocated to healthy nodes.

You typically manage searchable snapshots through ILM. The searchable snapshots action automatically converts a regular index into a searchable snapshot index when it reaches the cold phase. You can also make indices in existing snapshots searchable by manually mounting them as searchable snapshot indices with the mount snapshot API.

To mount an index from a snapshot that contains multiple indices, we recommend creating a clone of the snapshot that contains only the index you want to search, and mounting the clone. You should not delete a snapshot if it has any mounted indices, so creating a clone enables you to manage the lifecycle of the backup snapshot independently of any searchable snapshots.

You can control the allocation of the shards of searchable snapshot indices using the same mechanisms as for regular indices. For example, you could use Index-level shard allocation filtering to restrict searchable snapshot shards to a subset of your nodes.

We recommend that you force-merge indices to a single segment per shard before taking a snapshot that will be mounted as a searchable snapshot index. Each read from a snapshot repository takes time and costs money, and the fewer segments there are the fewer reads are needed to restore the snapshot.

Searchable snapshots are ideal for managing a large archive of historical data. Historical information is typically searched less frequently than recent data and therefore may not need replicas for their performance benefits.

For more complex or time-consuming searches, you can use Async search with searchable snapshots.

You can use any of the following repository types with searchable snapshots:

You can also use alternative implementations of these repository types, for instance Minio, as long as they are fully compatible.

How searchable snapshots workedit

When an index is mounted from a snapshot, Elasticsearch allocates its shards to data nodes within the cluster. The data nodes then automatically restore the shard data from the repository onto local storage. Once the restore process completes, these shards respond to searches using the data held in local storage and do not need to access the repository. This avoids incurring the cost or performance penalty associated with reading data from the repository.

If a node holding one of these shards fails, Elasticsearch automatically allocates it to another node, and that node restores the shard data from the repository. No replicas are needed, and no complicated monitoring or orchestration is necessary to restore lost shards.

Elasticsearch restores searchable snapshot shards in the background and you can search them even if they have not been fully restored. If a search hits a searchable snapshot shard before it has been fully restored, Elasticsearch eagerly retrieves the data needed for the search. If a shard is freshly allocated to a node and still warming up, some searches will be slower. However, searches typically access a very small fraction of the total shard data so the performance penalty is typically small.

Replicas of searchable snapshots shards are restored by copying data from the snapshot repository. In contrast, replicas of regular indices are restored by copying data from the primary.

Reliability of searchable snapshotsedit

The sole copy of the data in a searchable snapshot index is the underlying snapshot, stored in the repository. If the repository fails or corrupts the contents of the snapshot then the data is lost. Although Elasticsearch may have made copies of the data onto local storage, these copies may be incomplete and cannot be used to recover any data after a repository failure. You must make sure that your repository is reliable and protects against corruption of your data while it is at rest in the repository.

The blob storage offered by all major public cloud providers typically offers very good protection against data loss or corruption. If you manage your own repository storage then you are responsible for its reliability.