Search across clusters

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Cross-cluster search lets you run a single search request against one or more remote clusters. For example, you can use a cross-cluster search to filter and analyze log data stored on clusters in different data centers.

Supported APIs

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The following APIs support cross-cluster search:

  • Search
  • Async search
  • Multi search
  • Search template
  • Multi search template
  • Field capabilities
  • [preview] This functionality is in technical preview and may be changed or removed in a future release. Elastic will work to fix any issues, but features in technical preview are not subject to the support SLA of official GA features. EQL search
  • [preview] This functionality is in technical preview and may be changed or removed in a future release. Elastic will work to fix any issues, but features in technical preview are not subject to the support SLA of official GA features. SQL search
  • [preview] This functionality is in technical preview and may be changed or removed in a future release. Elastic will work to fix any issues, but features in technical preview are not subject to the support SLA of official GA features. Vector tile search

Prerequisites

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  • If you use sniff mode, the local coordinating node must be able to connect to seed and gateway nodes on the remote cluster.

    We recommend using gateway nodes capable of serving as coordinating nodes. The seed nodes can be a subset of these gateway nodes.

Cross-cluster search examples

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Remote cluster setup

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The following cluster update settings API request adds three remote clusters: cluster_one, cluster_two, and cluster_three.

PUT _cluster/settings
{
  "persistent": {
    "cluster": {
      "remote": {
        "cluster_one": {
          "seeds": [
            "127.0.0.1:9300"
          ]
        },
        "cluster_two": {
          "seeds": [
            "127.0.0.1:9301"
          ]
        },
        "cluster_three": {
          "seeds": [
            "127.0.0.1:9302"
          ]
        }
      }
    }
  }
}

Search a single remote cluster

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In the search request, you specify data streams and indices on a remote cluster as <remote_cluster_name>:<target>.

The following search API request searches the my-index-000001 index on a single remote cluster, cluster_one.

GET /cluster_one:my-index-000001/_search
{
  "query": {
    "match": {
      "user.id": "kimchy"
    }
  },
  "_source": ["user.id", "message", "http.response.status_code"]
}

The API returns the following response:

{
  "took": 150,
  "timed_out": false,
  "_shards": {
    "total": 1,
    "successful": 1,
    "failed": 0,
    "skipped": 0
  },
  "_clusters": {
    "total": 1,
    "successful": 1,
    "skipped": 0
  },
  "hits": {
    "total" : {
        "value": 1,
        "relation": "eq"
    },
    "max_score": 1,
    "hits": [
      {
        "_index": "cluster_one:my-index-000001", 
        "_id": "0",
        "_score": 1,
        "_source": {
          "user": {
            "id": "kimchy"
          },
          "message": "GET /search HTTP/1.1 200 1070000",
          "http": {
            "response":
              {
                "status_code": 200
              }
          }
        }
      }
    ]
  }
}

The search response body includes the name of the remote cluster in the _index parameter.

Search multiple remote clusters

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The following search API request searches the my-index-000001 index on three clusters:

  • Your local cluster
  • Two remote clusters, cluster_one and cluster_two
GET /my-index-000001,cluster_one:my-index-000001,cluster_two:my-index-000001/_search
{
  "query": {
    "match": {
      "user.id": "kimchy"
    }
  },
  "_source": ["user.id", "message", "http.response.status_code"]
}

The API returns the following response:

{
  "took": 150,
  "timed_out": false,
  "num_reduce_phases": 4,
  "_shards": {
    "total": 3,
    "successful": 3,
    "failed": 0,
    "skipped": 0
  },
  "_clusters": {
    "total": 3,
    "successful": 3,
    "skipped": 0
  },
  "hits": {
    "total" : {
        "value": 3,
        "relation": "eq"
    },
    "max_score": 1,
    "hits": [
      {
        "_index": "my-index-000001", 
        "_id": "0",
        "_score": 2,
        "_source": {
          "user": {
            "id": "kimchy"
          },
          "message": "GET /search HTTP/1.1 200 1070000",
          "http": {
            "response":
              {
                "status_code": 200
              }
          }
        }
      },
      {
        "_index": "cluster_one:my-index-000001", 
        "_id": "0",
        "_score": 1,
        "_source": {
          "user": {
            "id": "kimchy"
          },
          "message": "GET /search HTTP/1.1 200 1070000",
          "http": {
            "response":
              {
                "status_code": 200
              }
          }
        }
      },
      {
        "_index": "cluster_two:my-index-000001", 
        "_id": "0",
        "_score": 1,
        "_source": {
          "user": {
            "id": "kimchy"
          },
          "message": "GET /search HTTP/1.1 200 1070000",
          "http": {
            "response":
              {
                "status_code": 200
              }
          }
        }
      }
    ]
  }
}

This document’s _index parameter doesn’t include a cluster name. This means the document came from the local cluster.

This document came from cluster_one.

This document came from cluster_two.

Optional remote clusters

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By default, a cross-cluster search fails if a remote cluster in the request returns an error or is unavailable. Use the skip_unavailable cluster setting to mark a specific remote cluster as optional for cross-cluster search.

If skip_unavailable is true, a cross-cluster search:

  • Skips the remote cluster if its nodes are unavailable during the search. The response’s _cluster.skipped value contains a count of any skipped clusters.
  • Ignores errors returned by the remote cluster, such as errors related to unavailable shards or indices. This can include errors related to search parameters such as allow_no_indices and ignore_unavailable.
  • Ignores the allow_partial_search_results parameter and the related search.default_allow_partial_results cluster setting when searching the remote cluster. This means searches on the remote cluster may return partial results.

The following cluster update settings API request changes cluster_two's skip_unavailable setting to true.

PUT _cluster/settings
{
  "persistent": {
    "cluster.remote.cluster_two.skip_unavailable": true
  }
}

If cluster_two is disconnected or unavailable during a cross-cluster search, Elasticsearch won’t include matching documents from that cluster in the final results.

How cross-cluster search handles network delays

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Because cross-cluster search involves sending requests to remote clusters, any network delays can impact search speed. To avoid slow searches, cross-cluster search offers two options for handling network delays:

Minimize network roundtrips

By default, Elasticsearch reduces the number of network roundtrips between remote clusters. This reduces the impact of network delays on search speed. However, Elasticsearch can’t reduce network roundtrips for large search requests, such as those including a scroll or inner hits.

See Minimize network roundtrips to learn how this option works.

Don’t minimize network roundtrips

For search requests that include a scroll or inner hits, Elasticsearch sends multiple outgoing and ingoing requests to each remote cluster. You can also choose this option by setting the ccs_minimize_roundtrips parameter to false. While typically slower, this approach may work well for networks with low latency.

See Don’t minimize network roundtrips to learn how this option works.

The vector tile search API always minimizes network roundtrips and doesn’t include the ccs_minimize_roundtrips parameter.

Minimize network roundtrips

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Here’s how cross-cluster search works when you minimize network roundtrips.

  1. You send a cross-cluster search request to your local cluster. A coordinating node in that cluster receives and parses the request.

    ccs min roundtrip client request

  2. The coordinating node sends a single search request to each cluster, including the local cluster. Each cluster performs the search request independently, applying its own cluster-level settings to the request.

    ccs min roundtrip cluster search

  3. Each remote cluster sends its search results back to the coordinating node.

    ccs min roundtrip cluster results

  4. After collecting results from each cluster, the coordinating node returns the final results in the cross-cluster search response.

    ccs min roundtrip client response

Don’t minimize network roundtrips

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Here’s how cross-cluster search works when you don’t minimize network roundtrips.

  1. You send a cross-cluster search request to your local cluster. A coordinating node in that cluster receives and parses the request.

    ccs min roundtrip client request

  2. The coordinating node sends a search shards API request to each remote cluster.

    ccs min roundtrip cluster search

  3. Each remote cluster sends its response back to the coordinating node. This response contains information about the indices and shards the cross-cluster search request will be executed on.

    ccs min roundtrip cluster results

  4. The coordinating node sends a search request to each shard, including those in its own cluster. Each shard performs the search request independently.

    When network roundtrips aren’t minimized, the search is executed as if all data were in the coordinating node’s cluster. We recommend updating cluster-level settings that limit searches, such as action.search.shard_count.limit, pre_filter_shard_size, and max_concurrent_shard_requests, to account for this. If these limits are too low, the search may be rejected.

    ccs dont min roundtrip shard search

  5. Each shard sends its search results back to the coordinating node.

    ccs dont min roundtrip shard results

  6. After collecting results from each cluster, the coordinating node returns the final results in the cross-cluster search response.

    ccs min roundtrip client response

Supported cross-cluster search configurations

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In 8.0+, Elastic supports searches from a local cluster to a remote cluster running:

  • The previous minor version.
  • The same version.
  • A newer minor version in the same major version.

Elastic also supports searches from a local cluster running the last minor version of a major version to a remote cluster running any minor version in the following major version. For example, a local 7.17 cluster can search any remote 8.x cluster.

Remote cluster version

Local cluster version

6.8

7.1–7.16

7.17

8.0

8.1

8.2

8.3

8.4

8.5

6.8

Yes

Yes

Yes

No

No

No

No

No

No

7.1–7.16

Yes

Yes

Yes

No

No

No

No

No

No

7.17

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

8.0

No

No

Yes

Yes

Yes

Yes

Yes

Yes

Yes

8.1

No

No

No

Yes

Yes

Yes

Yes

Yes

Yes

8.2

No

No

No

No

Yes

Yes

Yes

Yes

Yes

8.3

No

No

No

No

No

Yes

Yes

Yes

Yes

8.4

No

No

No

No

No

No

Yes

Yes

Yes

8.5

No

No

No

No

No

No

No

Yes

Yes

For the EQL search API, the local and remote clusters must use the same Elasticsearch version.

For example, a local 8.0 cluster can search a remote 7.17 or any remote 8.x cluster. However, a search from a local 8.0 cluster to a remote 7.16 or 6.8 cluster is not supported.

Only features that exist across all searched clusters are supported. Using a feature with a remote cluster where the feature is not supported will result in undefined behavior.

A cross-cluster search using an unsupported configuration may still work. However, such searches aren’t tested by Elastic, and their behavior isn’t guaranteed.

Ensure cross-cluster search support

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The simplest way to ensure your clusters support cross-cluster search is to keep each cluster on the same version of Elasticsearch. If you need to maintain clusters with different versions, you can:

  • Maintain a dedicated cluster for cross-cluster search. Keep this cluster on the earliest version needed to search the other clusters. For example, if you have 7.17 and 8.x clusters, you can maintain a dedicated 7.17 cluster to use as the local cluster for cross-cluster search.
  • Keep each cluster no more than one minor version apart. This lets you use any cluster as the local cluster when running a cross-cluster search.

Cross-cluster search during an upgrade

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You can still search a remote cluster while performing a rolling upgrade on the local cluster. However, the local coordinating node’s "upgrade from" and "upgrade to" version must be compatible with the remote cluster’s gateway node.

Running multiple versions of Elasticsearch in the same cluster beyond the duration of an upgrade is not supported.

For more information about upgrades, see Upgrading Elasticsearch.