Search across clusters

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.

Cross-cluster search requires remote clusters.

Supported APIs

The following APIs support cross-cluster search:

• Search
• Multi search
• Search template
• Multi search template

Cross-cluster search examples

Remote cluster setup

To perform a cross-cluster search, you must have at least one remote cluster configured.

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

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", 
        "_type": "_doc",
        "_id": "0",
        "_score": 1,
        "_source": {
          "user": {
            "id": "kimchy"
          },
          "message": "GET /search HTTP/1.1 200 1070000",
          "http": {
            "response":
              {
                "status_code": 200
              }
          }
        }
      }
    ]
  }
}

Search multiple remote clusters

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", 
        "_type": "_doc",
        "_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", 
        "_type": "_doc",
        "_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", 
        "_type": "_doc",
        "_id": "0",
        "_score": 1,
        "_source": {
          "user": {
            "id": "kimchy"
          },
          "message": "GET /search HTTP/1.1 200 1070000",
          "http": {
            "response":
              {
                "status_code": 200
              }
          }
        }
      }
    ]
  }
}

Skip unavailable clusters

By default, a cross-cluster search returns an error if any cluster in the request is unavailable.

To skip an unavailable cluster during a cross-cluster search, set the skip_unavailable cluster setting to true.

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.

Selecting gateway and seed nodes in sniff mode

For remote clusters using the sniff connection mode, gateway and seed nodes need to be accessible from the local cluster via your network.

By default, any non-master-eligible node can act as a gateway node. If wanted, you can define the gateway nodes for a cluster by setting cluster.remote.node.attr.gateway to true.

For cross-cluster search, we recommend you use gateway nodes that are capable of serving as coordinating nodes for search requests. If wanted, the seed nodes for a cluster can be a subset of these gateway nodes.

Cross-cluster search in proxy mode

Proxy mode remote cluster connections support cross-cluster search. All remote connections connect to the configured proxy_address. Any desired connection routing to gateway or coordinating nodes must be implemented by the intermediate proxy at this configured address.

How cross-cluster search handles network delays

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.

Minimize network roundtrips

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.

   

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.

   

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

   

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

   

Don’t minimize network roundtrips

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.

   

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

   

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.

   

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.

   

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

   

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

   

Supported configurations

Generally, cross cluster search can search remote clusters that are one major version ahead or behind the coordinating node’s version. Cross cluster search can also search remote clusters that are being upgraded so long as both the “upgrade from” and “upgrade to” version are compatible with the gateway node.

For example, a coordinating node running Elasticsearch 5.6 can search a remote cluster running Elasticsearch 6.8, but that cluster can not be upgraded to 7.1. In this case you should first upgrade the coordinating node to 7.1 and then upgrade remote cluster.

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