This functionality is in beta and is subject to change. The design and code is less mature than official GA features and is being provided as-is with no warranties. Beta features are not subject to the support SLA of official GA features.
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
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 they are reallocated.
You typically manage searchable snapshots through ILM. The
searchable snapshots action automatically converts
an index to a searchable snapshot when it reaches the
cold phase. You can also make
indices in existing snapshots searchable by manually mounting them as
searchable snapshots with the mount
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 cannot 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.
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.