Get shard allocation information

GET /_cat/allocation/{node_id}

Get a snapshot of the number of shards allocated to each data node and their disk space.

IMPORTANT: CAT APIs are only intended for human consumption using the command line or Kibana console. They are not intended for use by applications.

Path parameters

  • node_id string | array[string] Required

    A comma-separated list of node identifiers or names used to limit the returned information.

Query parameters

  • bytes string

    The unit used to display byte values.

    Values are b, kb, mb, gb, tb, or pb.

  • h string | array[string]

    List of columns to appear in the response. Supports simple wildcards.

  • s string | array[string]

    List of columns that determine how the table should be sorted. Sorting defaults to ascending and can be changed by setting :asc or :desc as a suffix to the column name.

  • local boolean

    If true, the request computes the list of selected nodes from the local cluster state. If false the list of selected nodes are computed from the cluster state of the master node. In both cases the coordinating node will send requests for further information to each selected node.

  • Period to wait for a connection to the master node.

    Values are -1 or 0.

Responses

GET /_cat/allocation/{node_id}
GET /_cat/allocation?v=true&format=json
curl \
 --request GET 'http://api.example.com/_cat/allocation/{node_id}' \
 --header "Authorization: $API_KEY"
Response examples (200)
A successful response from `GET /_cat/allocation?v=true&format=json`. It shows a single shard is allocated to the one node available.
[
  {
    "shards": "1",
    "shards.undesired": "0",
    "write_load.forecast": "0.0",
    "disk.indices.forecast": "260b",
    "disk.indices": "260b",
    "disk.used": "47.3gb",
    "disk.avail": "43.4gb",
    "disk.total": "100.7gb",
    "disk.percent": "46",
    "host": "127.0.0.1",
    "ip": "127.0.0.1",
    "node": "CSUXak2",
    "node.role": "himrst"
  }
]




















































Get datafeeds Added in 7.7.0

GET /_cat/ml/datafeeds

Get configuration and usage information about datafeeds. This API returns a maximum of 10,000 datafeeds. If the Elasticsearch security features are enabled, you must have monitor_ml, monitor, manage_ml, or manage cluster privileges to use this API.

IMPORTANT: CAT APIs are only intended for human consumption using the Kibana console or command line. They are not intended for use by applications. For application consumption, use the get datafeed statistics API.

Query parameters

  • Specifies what to do when the request:

    • Contains wildcard expressions and there are no datafeeds that match.
    • Contains the _all string or no identifiers and there are no matches.
    • Contains wildcard expressions and there are only partial matches.

    If true, the API returns an empty datafeeds array when there are no matches and the subset of results when there are partial matches. If false, the API returns a 404 status code when there are no matches or only partial matches.

  • h string | array[string]

    Comma-separated list of column names to display.

    Supported values include:

    • ae (or assignment_explanation): For started datafeeds only, contains messages relating to the selection of a node.
    • bc (or buckets.count, bucketsCount): The number of buckets processed.
    • id: A numerical character string that uniquely identifies the datafeed.
    • na (or node.address, nodeAddress): For started datafeeds only, the network address of the node where the datafeed is started.
    • ne (or node.ephemeral_id, nodeEphemeralId): For started datafeeds only, the ephemeral ID of the node where the datafeed is started.
    • ni (or node.id, nodeId): For started datafeeds only, the unique identifier of the node where the datafeed is started.
    • nn (or node.name, nodeName): For started datafeeds only, the name of the node where the datafeed is started.
    • sba (or search.bucket_avg, searchBucketAvg): The average search time per bucket, in milliseconds.
    • sc (or search.count, searchCount): The number of searches run by the datafeed.
    • seah (or search.exp_avg_hour, searchExpAvgHour): The exponential average search time per hour, in milliseconds.
    • st (or search.time, searchTime): The total time the datafeed spent searching, in milliseconds.
    • s (or state): The status of the datafeed: starting, started, stopping, or stopped. If starting, the datafeed has been requested to start but has not yet started. If started, the datafeed is actively receiving data. If stopping, the datafeed has been requested to stop gracefully and is completing its final action. If stopped, the datafeed is stopped and will not receive data until it is re-started.

    Values are ae, assignment_explanation, bc, buckets.count, bucketsCount, id, na, node.address, nodeAddress, ne, node.ephemeral_id, nodeEphemeralId, ni, node.id, nodeId, nn, node.name, nodeName, sba, search.bucket_avg, searchBucketAvg, sc, search.count, searchCount, seah, search.exp_avg_hour, searchExpAvgHour, st, search.time, searchTime, s, or state.

  • s string | array[string]

    Comma-separated list of column names or column aliases used to sort the response.

    Supported values include:

    • ae (or assignment_explanation): For started datafeeds only, contains messages relating to the selection of a node.
    • bc (or buckets.count, bucketsCount): The number of buckets processed.
    • id: A numerical character string that uniquely identifies the datafeed.
    • na (or node.address, nodeAddress): For started datafeeds only, the network address of the node where the datafeed is started.
    • ne (or node.ephemeral_id, nodeEphemeralId): For started datafeeds only, the ephemeral ID of the node where the datafeed is started.
    • ni (or node.id, nodeId): For started datafeeds only, the unique identifier of the node where the datafeed is started.
    • nn (or node.name, nodeName): For started datafeeds only, the name of the node where the datafeed is started.
    • sba (or search.bucket_avg, searchBucketAvg): The average search time per bucket, in milliseconds.
    • sc (or search.count, searchCount): The number of searches run by the datafeed.
    • seah (or search.exp_avg_hour, searchExpAvgHour): The exponential average search time per hour, in milliseconds.
    • st (or search.time, searchTime): The total time the datafeed spent searching, in milliseconds.
    • s (or state): The status of the datafeed: starting, started, stopping, or stopped. If starting, the datafeed has been requested to start but has not yet started. If started, the datafeed is actively receiving data. If stopping, the datafeed has been requested to stop gracefully and is completing its final action. If stopped, the datafeed is stopped and will not receive data until it is re-started.

    Values are ae, assignment_explanation, bc, buckets.count, bucketsCount, id, na, node.address, nodeAddress, ne, node.ephemeral_id, nodeEphemeralId, ni, node.id, nodeId, nn, node.name, nodeName, sba, search.bucket_avg, searchBucketAvg, sc, search.count, searchCount, seah, search.exp_avg_hour, searchExpAvgHour, st, search.time, searchTime, s, or state.

  • time string

    The unit used to display time values.

    Values are nanos, micros, ms, s, m, h, or d.

Responses

  • 200 application/json
    Hide response attributes Show response attributes object
    • id string

      The datafeed identifier.

    • state string

      Values are started, stopped, starting, or stopping.

    • For started datafeeds only, contains messages relating to the selection of a node.

    • The number of buckets processed.

    • The number of searches run by the datafeed.

    • The total time the datafeed spent searching, in milliseconds.

    • The average search time per bucket, in milliseconds.

    • The exponential average search time per hour, in milliseconds.

    • node.id string

      The unique identifier of the assigned node. For started datafeeds only, this information pertains to the node upon which the datafeed is started.

    • The name of the assigned node. For started datafeeds only, this information pertains to the node upon which the datafeed is started.

    • The ephemeral identifier of the assigned node. For started datafeeds only, this information pertains to the node upon which the datafeed is started.

    • The network address of the assigned node. For started datafeeds only, this information pertains to the node upon which the datafeed is started.

GET /_cat/ml/datafeeds
GET _cat/ml/datafeeds?v=true&format=json
curl \
 --request GET 'http://api.example.com/_cat/ml/datafeeds' \
 --header "Authorization: $API_KEY"
Response examples (200)
A successful response from `GET _cat/ml/datafeeds?v=true&format=json`.
[
  {
    "id": "datafeed-high_sum_total_sales",
    "state": "stopped",
    "buckets.count": "743",
    "search.count": "7"
  },
  {
    "id": "datafeed-low_request_rate",
    "state": "stopped",
    "buckets.count": "1457",
    "search.count": "3"
  },
  {
    "id": "datafeed-response_code_rates",
    "state": "stopped",
    "buckets.count": "1460",
    "search.count": "18"
  },
  {
    "id": "datafeed-url_scanning",
    "state": "stopped",
    "buckets.count": "1460",
    "search.count": "18"
  }
]









































































































Explain the shard allocations Added in 5.0.0

POST /_cluster/allocation/explain

Get explanations for shard allocations in the cluster. For unassigned shards, it provides an explanation for why the shard is unassigned. For assigned shards, it provides an explanation for why the shard is remaining on its current node and has not moved or rebalanced to another node. This API can be very useful when attempting to diagnose why a shard is unassigned or why a shard continues to remain on its current node when you might expect otherwise.

Query parameters

application/json

Body

  • Specifies the node ID or the name of the node to only explain a shard that is currently located on the specified node.

  • index string
  • primary boolean

    If true, returns explanation for the primary shard for the given shard ID.

  • shard number

    Specifies the ID of the shard that you would like an explanation for.

Responses

POST /_cluster/allocation/explain
GET _cluster/allocation/explain
{
  "index": "my-index-000001",
  "shard": 0,
  "primary": false,
  "current_node": "my-node"
}
curl \
 --request POST 'http://api.example.com/_cluster/allocation/explain' \
 --header "Authorization: $API_KEY" \
 --header "Content-Type: application/json" \
 --data '"{\n  \"index\": \"my-index-000001\",\n  \"shard\": 0,\n  \"primary\": false,\n  \"current_node\": \"my-node\"\n}"'
Request example
Run `GET _cluster/allocation/explain` to get an explanation for a shard's current allocation.
{
  "index": "my-index-000001",
  "shard": 0,
  "primary": false,
  "current_node": "my-node"
}
Response examples (200)
An example of an allocation explanation for an unassigned primary shard. In this example, a newly created index has an index setting that requires that it only be allocated to a node named `nonexistent_node`, which does not exist, so the index is unable to allocate.
{
  "index" : "my-index-000001",
  "shard" : 0,
  "primary" : true,
  "current_state" : "unassigned",
  "unassigned_info" : {
    "reason" : "INDEX_CREATED",
    "at" : "2017-01-04T18:08:16.600Z",
    "last_allocation_status" : "no"
  },
  "can_allocate" : "no",
  "allocate_explanation" : "Elasticsearch isn't allowed to allocate this shard to any of the nodes in the cluster. Choose a node to which you expect this shard to be allocated, find this node in the node-by-node explanation, and address the reasons which prevent Elasticsearch from allocating this shard there.",
  "node_allocation_decisions" : [
    {
      "node_id" : "8qt2rY-pT6KNZB3-hGfLnw",
      "node_name" : "node-0",
      "transport_address" : "127.0.0.1:9401",
      "roles" : ["data", "data_cold", "data_content", "data_frozen", "data_hot", "data_warm", "ingest", "master", "ml", "remote_cluster_client", "transform"],
      "node_attributes" : {},
      "node_decision" : "no",
      "weight_ranking" : 1,
      "deciders" : [
        {
          "decider" : "filter",
          "decision" : "NO",
          "explanation" : "node does not match index setting [index.routing.allocation.include] filters [_name:\"nonexistent_node\"]"
        }
      ]
    }
  ]
}
An example of an allocation explanation for an unassigned primary shard that has reached the maximum number of allocation retry attempts. After the maximum number of retries is reached, Elasticsearch stops attempting to allocate the shard in order to prevent infinite retries which may impact cluster performance.
{
  "index" : "my-index-000001",
  "shard" : 0,
  "primary" : true,
  "current_state" : "unassigned",
  "unassigned_info" : {
    "at" : "2017-01-04T18:03:28.464Z",
    "failed shard on node [mEKjwwzLT1yJVb8UxT6anw]: failed recovery, failure RecoveryFailedException",
    "reason": "ALLOCATION_FAILED",
    "failed_allocation_attempts": 5,
    "last_allocation_status": "no",
  },
  "can_allocate": "no",
  "allocate_explanation": "cannot allocate because allocation is not permitted to any of the nodes",
  "node_allocation_decisions" : [
    {
      "node_id" : "3sULLVJrRneSg0EfBB-2Ew",
      "node_name" : "node_t0",
      "transport_address" : "127.0.0.1:9400",
      "roles" : ["data_content", "data_hot"],
      "node_decision" : "no",
      "store" : {
        "matching_size" : "4.2kb",
        "matching_size_in_bytes" : 4325
      },
      "deciders" : [
        {
          "decider": "max_retry",
          "decision" : "NO",
          "explanation": "shard has exceeded the maximum number of retries [5] on failed allocation attempts - manually call [POST /_cluster/reroute?retry_failed] to retry, [unassigned_info[[reason=ALLOCATION_FAILED], at[2024-07-30T21:04:12.166Z], failed_attempts[5], failed_nodes[[mEKjwwzLT1yJVb8UxT6anw]], delayed=false, details[failed shard on node [mEKjwwzLT1yJVb8UxT6anw]: failed recovery, failure RecoveryFailedException], allocation_status[deciders_no]]]"
        }
      ]
    }
  ]
}


































































































































































































Get a connector sync job Beta

GET /_connector/_sync_job/{connector_sync_job_id}

Path parameters

Responses

GET /_connector/_sync_job/{connector_sync_job_id}
curl \
 --request GET 'http://api.example.com/_connector/_sync_job/{connector_sync_job_id}' \
 --header "Authorization: $API_KEY"












































Update the connector draft filtering validation Technical preview

PUT /_connector/{connector_id}/_filtering/_validation

Update the draft filtering validation info for a connector.

Path parameters

  • connector_id string Required

    The unique identifier of the connector to be updated

application/json

Body Required

  • validation object Required
    Hide validation attributes Show validation attributes object
    • errors array[object] Required
      Hide errors attributes Show errors attributes object
    • state string Required

      Values are edited, invalid, or valid.

Responses

  • 200 application/json
    Hide response attribute Show response attribute object
    • result string Required

      Values are created, updated, deleted, not_found, or noop.

PUT /_connector/{connector_id}/_filtering/_validation
curl \
 --request PUT 'http://api.example.com/_connector/{connector_id}/_filtering/_validation' \
 --header "Authorization: $API_KEY" \
 --header "Content-Type: application/json" \
 --data '{"validation":{"errors":[{"ids":["string"],"messages":["string"]}],"state":"edited"}}'




















Path parameters

  • connector_id string Required

    The unique identifier of the connector to be updated

application/json

Body Required

Responses

  • 200 application/json
    Hide response attribute Show response attribute object
    • result string Required

      Values are created, updated, deleted, not_found, or noop.

PUT /_connector/{connector_id}/_service_type
PUT _connector/my-connector/_service_type
{
    "service_type": "sharepoint_online"
}
curl \
 --request PUT 'http://api.example.com/_connector/{connector_id}/_service_type' \
 --header "Authorization: $API_KEY" \
 --header "Content-Type: application/json" \
 --data '"{\n    \"service_type\": \"sharepoint_online\"\n}"'
Request example
{
    "service_type": "sharepoint_online"
}
Response examples (200)
{
  "result": "updated"
}

















Create a follower Added in 6.5.0

PUT /{index}/_ccr/follow

Create a cross-cluster replication follower index that follows a specific leader index. When the API returns, the follower index exists and cross-cluster replication starts replicating operations from the leader index to the follower index.

Path parameters

  • index string Required

    The name of the follower index.

Query parameters

  • Period to wait for a connection to the master node.

    Values are -1 or 0.

  • wait_for_active_shards number | string

    Specifies the number of shards to wait on being active before responding. This defaults to waiting on none of the shards to be active. A shard must be restored from the leader index before being active. Restoring a follower shard requires transferring all the remote Lucene segment files to the follower index.

    Values are all or index-setting.

application/json

Body Required

Responses

PUT /{index}/_ccr/follow
PUT /follower_index/_ccr/follow?wait_for_active_shards=1
{
  "remote_cluster" : "remote_cluster",
  "leader_index" : "leader_index",
  "settings": {
    "index.number_of_replicas": 0
  },
  "max_read_request_operation_count" : 1024,
  "max_outstanding_read_requests" : 16,
  "max_read_request_size" : "1024k",
  "max_write_request_operation_count" : 32768,
  "max_write_request_size" : "16k",
  "max_outstanding_write_requests" : 8,
  "max_write_buffer_count" : 512,
  "max_write_buffer_size" : "512k",
  "max_retry_delay" : "10s",
  "read_poll_timeout" : "30s"
}
curl \
 --request PUT 'http://api.example.com/{index}/_ccr/follow' \
 --header "Authorization: $API_KEY" \
 --header "Content-Type: application/json" \
 --data '"{\n  \"remote_cluster\" : \"remote_cluster\",\n  \"leader_index\" : \"leader_index\",\n  \"settings\": {\n    \"index.number_of_replicas\": 0\n  },\n  \"max_read_request_operation_count\" : 1024,\n  \"max_outstanding_read_requests\" : 16,\n  \"max_read_request_size\" : \"1024k\",\n  \"max_write_request_operation_count\" : 32768,\n  \"max_write_request_size\" : \"16k\",\n  \"max_outstanding_write_requests\" : 8,\n  \"max_write_buffer_count\" : 512,\n  \"max_write_buffer_size\" : \"512k\",\n  \"max_retry_delay\" : \"10s\",\n  \"read_poll_timeout\" : \"30s\"\n}"'
Request example
Run `PUT /follower_index/_ccr/follow?wait_for_active_shards=1` to create a follower index named `follower_index`.
{
  "remote_cluster" : "remote_cluster",
  "leader_index" : "leader_index",
  "settings": {
    "index.number_of_replicas": 0
  },
  "max_read_request_operation_count" : 1024,
  "max_outstanding_read_requests" : 16,
  "max_read_request_size" : "1024k",
  "max_write_request_operation_count" : 32768,
  "max_write_request_size" : "16k",
  "max_outstanding_write_requests" : 8,
  "max_write_buffer_count" : 512,
  "max_write_buffer_size" : "512k",
  "max_retry_delay" : "10s",
  "read_poll_timeout" : "30s"
}
Response examples (200)
A successful response from `PUT /follower_index/_ccr/follow?wait_for_active_shards=1`.
{
  "follow_index_created" : true,
  "follow_index_shards_acked" : true,
  "index_following_started" : true
}

Get follower information Added in 6.7.0

GET /{index}/_ccr/info

Get information about all cross-cluster replication follower indices. For example, the results include follower index names, leader index names, replication options, and whether the follower indices are active or paused.

External documentation

Path parameters

  • index string | array[string] Required

    A comma-delimited list of follower index patterns.

Query parameters

  • The period to wait for a connection to the master node. If the master node is not available before the timeout expires, the request fails and returns an error. It can also be set to -1 to indicate that the request should never timeout.

    Values are -1 or 0.

Responses

GET /{index}/_ccr/info
GET /follower_index/_ccr/info
curl \
 --request GET 'http://api.example.com/{index}/_ccr/info' \
 --header "Authorization: $API_KEY"
Response examples (200)
A successful response from `GET /follower_index/_ccr/info` when the follower index is active.
{
  "follower_indices": [
    {
      "follower_index": "follower_index",
      "remote_cluster": "remote_cluster",
      "leader_index": "leader_index",
      "status": "active",
      "parameters": {
        "max_read_request_operation_count": 5120,
        "max_read_request_size": "32mb",
        "max_outstanding_read_requests": 12,
        "max_write_request_operation_count": 5120,
        "max_write_request_size": "9223372036854775807b",
        "max_outstanding_write_requests": 9,
        "max_write_buffer_count": 2147483647,
        "max_write_buffer_size": "512mb",
        "max_retry_delay": "500ms",
        "read_poll_timeout": "1m"
      }
    }
  ]
}
A successful response from `GET /follower_index/_ccr/info` when the follower index is paused.
{
  "follower_indices": [
    {
      "follower_index": "follower_index",
      "remote_cluster": "remote_cluster",
      "leader_index": "leader_index",
      "status": "paused"
    }
  ]
}






















































































































Create a new document in the index Added in 5.0.0

PUT /{index}/_create/{id}

You can index a new JSON document with the /<target>/_doc/ or /<target>/_create/<_id> APIs Using _create guarantees that the document is indexed only if it does not already exist. It returns a 409 response when a document with a same ID already exists in the index. To update an existing document, you must use the /<target>/_doc/ API.

If the Elasticsearch security features are enabled, you must have the following index privileges for the target data stream, index, or index alias:

  • To add a document using the PUT /<target>/_create/<_id> or POST /<target>/_create/<_id> request formats, you must have the create_doc, create, index, or write index privilege.
  • To automatically create a data stream or index with this API request, you must have the auto_configure, create_index, or manage index privilege.

Automatic data stream creation requires a matching index template with data stream enabled.

Automatically create data streams and indices

If the request's target doesn't exist and matches an index template with a data_stream definition, the index operation automatically creates the data stream.

If the target doesn't exist and doesn't match a data stream template, the operation automatically creates the index and applies any matching index templates.

NOTE: Elasticsearch includes several built-in index templates. To avoid naming collisions with these templates, refer to index pattern documentation.

If no mapping exists, the index operation creates a dynamic mapping. By default, new fields and objects are automatically added to the mapping if needed.

Automatic index creation is controlled by the action.auto_create_index setting. If it is true, any index can be created automatically. You can modify this setting to explicitly allow or block automatic creation of indices that match specified patterns or set it to false to turn off automatic index creation entirely. Specify a comma-separated list of patterns you want to allow or prefix each pattern with + or - to indicate whether it should be allowed or blocked. When a list is specified, the default behaviour is to disallow.

NOTE: The action.auto_create_index setting affects the automatic creation of indices only. It does not affect the creation of data streams.

Routing

By default, shard placement — or routing — is controlled by using a hash of the document's ID value. For more explicit control, the value fed into the hash function used by the router can be directly specified on a per-operation basis using the routing parameter.

When setting up explicit mapping, you can also use the _routing field to direct the index operation to extract the routing value from the document itself. This does come at the (very minimal) cost of an additional document parsing pass. If the _routing mapping is defined and set to be required, the index operation will fail if no routing value is provided or extracted.

NOTE: Data streams do not support custom routing unless they were created with the allow_custom_routing setting enabled in the template.

Distributed

The index operation is directed to the primary shard based on its route and performed on the actual node containing this shard. After the primary shard completes the operation, if needed, the update is distributed to applicable replicas.

Active shards

To improve the resiliency of writes to the system, indexing operations can be configured to wait for a certain number of active shard copies before proceeding with the operation. If the requisite number of active shard copies are not available, then the write operation must wait and retry, until either the requisite shard copies have started or a timeout occurs. By default, write operations only wait for the primary shards to be active before proceeding (that is to say wait_for_active_shards is 1). This default can be overridden in the index settings dynamically by setting index.write.wait_for_active_shards. To alter this behavior per operation, use the wait_for_active_shards request parameter.

Valid values are all or any positive integer up to the total number of configured copies per shard in the index (which is number_of_replicas+1). Specifying a negative value or a number greater than the number of shard copies will throw an error.

For example, suppose you have a cluster of three nodes, A, B, and C and you create an index index with the number of replicas set to 3 (resulting in 4 shard copies, one more copy than there are nodes). If you attempt an indexing operation, by default the operation will only ensure the primary copy of each shard is available before proceeding. This means that even if B and C went down and A hosted the primary shard copies, the indexing operation would still proceed with only one copy of the data. If wait_for_active_shards is set on the request to 3 (and all three nodes are up), the indexing operation will require 3 active shard copies before proceeding. This requirement should be met because there are 3 active nodes in the cluster, each one holding a copy of the shard. However, if you set wait_for_active_shards to all (or to 4, which is the same in this situation), the indexing operation will not proceed as you do not have all 4 copies of each shard active in the index. The operation will timeout unless a new node is brought up in the cluster to host the fourth copy of the shard.

It is important to note that this setting greatly reduces the chances of the write operation not writing to the requisite number of shard copies, but it does not completely eliminate the possibility, because this check occurs before the write operation starts. After the write operation is underway, it is still possible for replication to fail on any number of shard copies but still succeed on the primary. The _shards section of the API response reveals the number of shard copies on which replication succeeded and failed.

External documentation

Path parameters

  • index string Required

    The name of the data stream or index to target. If the target doesn't exist and matches the name or wildcard (*) pattern of an index template with a data_stream definition, this request creates the data stream. If the target doesn't exist and doesn’t match a data stream template, this request creates the index.

  • id string Required

    A unique identifier for the document. To automatically generate a document ID, use the POST /<target>/_doc/ request format.

Query parameters

  • Only perform the operation if the document has this primary term.

  • Only perform the operation if the document has this sequence number.

  • True or false if to include the document source in the error message in case of parsing errors.

  • op_type string

    Set to create to only index the document if it does not already exist (put if absent). If a document with the specified _id already exists, the indexing operation will fail. The behavior is the same as using the <index>/_create endpoint. If a document ID is specified, this paramater defaults to index. Otherwise, it defaults to create. If the request targets a data stream, an op_type of create is required.

    Supported values include:

    • index: Overwrite any documents that already exist.
    • create: Only index documents that do not already exist.

    Values are index or create.

  • pipeline string

    The ID of the pipeline to use to preprocess incoming documents. If the index has a default ingest pipeline specified, setting the value to _none turns off the default ingest pipeline for this request. If a final pipeline is configured, it will always run regardless of the value of this parameter.

  • refresh string

    If true, Elasticsearch refreshes the affected shards to make this operation visible to search. If wait_for, it waits for a refresh to make this operation visible to search. If false, it does nothing with refreshes.

    Values are true, false, or wait_for.

  • If true, the destination must be an index alias.

  • If true, the request's actions must target a data stream (existing or to be created).

  • routing string

    A custom value that is used to route operations to a specific shard.

  • timeout string

    The period the request waits for the following operations: automatic index creation, dynamic mapping updates, waiting for active shards. Elasticsearch waits for at least the specified timeout period before failing. The actual wait time could be longer, particularly when multiple waits occur.

    This parameter is useful for situations where the primary shard assigned to perform the operation might not be available when the operation runs. Some reasons for this might be that the primary shard is currently recovering from a gateway or undergoing relocation. By default, the operation will wait on the primary shard to become available for at least 1 minute before failing and responding with an error. The actual wait time could be longer, particularly when multiple waits occur.

    Values are -1 or 0.

  • version number

    The explicit version number for concurrency control. It must be a non-negative long number.

  • The version type.

    Supported values include:

    • internal: Use internal versioning that starts at 1 and increments with each update or delete.
    • external: Only index the document if the specified version is strictly higher than the version of the stored document or if there is no existing document.
    • external_gte: Only index the document if the specified version is equal or higher than the version of the stored document or if there is no existing document. NOTE: The external_gte version type is meant for special use cases and should be used with care. If used incorrectly, it can result in loss of data.
    • force: This option is deprecated because it can cause primary and replica shards to diverge.

    Values are internal, external, external_gte, or force.

  • wait_for_active_shards number | string

    The number of shard copies that must be active before proceeding with the operation. You can set it to all or any positive integer up to the total number of shards in the index (number_of_replicas+1). The default value of 1 means it waits for each primary shard to be active.

    Values are all or index-setting.

application/json

Body Required

object object

Responses

PUT /{index}/_create/{id}
PUT my-index-000001/_create/1
{
  "@timestamp": "2099-11-15T13:12:00",
  "message": "GET /search HTTP/1.1 200 1070000",
  "user": {
    "id": "kimchy"
  }
}
curl \
 --request PUT 'http://api.example.com/{index}/_create/{id}' \
 --header "Authorization: $API_KEY" \
 --header "Content-Type: application/json" \
 --data '"{\n  \"@timestamp\": \"2099-11-15T13:12:00\",\n  \"message\": \"GET /search HTTP/1.1 200 1070000\",\n  \"user\": {\n    \"id\": \"kimchy\"\n  }\n}"'
Request example
Run `PUT my-index-000001/_create/1` to index a document into the `my-index-000001` index if no document with that ID exists.
{
  "@timestamp": "2099-11-15T13:12:00",
  "message": "GET /search HTTP/1.1 200 1070000",
  "user": {
    "id": "kimchy"
  }
}
























Delete documents Added in 5.0.0

POST /{index}/_delete_by_query

Deletes documents that match the specified query.

If the Elasticsearch security features are enabled, you must have the following index privileges for the target data stream, index, or alias:

  • read
  • delete or write

You can specify the query criteria in the request URI or the request body using the same syntax as the search API. When you submit a delete by query request, Elasticsearch gets a snapshot of the data stream or index when it begins processing the request and deletes matching documents using internal versioning. If a document changes between the time that the snapshot is taken and the delete operation is processed, it results in a version conflict and the delete operation fails.

NOTE: Documents with a version equal to 0 cannot be deleted using delete by query because internal versioning does not support 0 as a valid version number.

While processing a delete by query request, Elasticsearch performs multiple search requests sequentially to find all of the matching documents to delete. A bulk delete request is performed for each batch of matching documents. If a search or bulk request is rejected, the requests are retried up to 10 times, with exponential back off. If the maximum retry limit is reached, processing halts and all failed requests are returned in the response. Any delete requests that completed successfully still stick, they are not rolled back.

You can opt to count version conflicts instead of halting and returning by setting conflicts to proceed. Note that if you opt to count version conflicts the operation could attempt to delete more documents from the source than max_docs until it has successfully deleted max_docs documents, or it has gone through every document in the source query.

Throttling delete requests

To control the rate at which delete by query issues batches of delete operations, you can set requests_per_second to any positive decimal number. This pads each batch with a wait time to throttle the rate. Set requests_per_second to -1 to disable throttling.

Throttling uses a wait time between batches so that the internal scroll requests can be given a timeout that takes the request padding into account. The padding time is the difference between the batch size divided by the requests_per_second and the time spent writing. By default the batch size is 1000, so if requests_per_second is set to 500:

target_time = 1000 / 500 per second = 2 seconds
wait_time = target_time - write_time = 2 seconds - .5 seconds = 1.5 seconds

Since the batch is issued as a single _bulk request, large batch sizes cause Elasticsearch to create many requests and wait before starting the next set. This is "bursty" instead of "smooth".

Slicing

Delete by query supports sliced scroll to parallelize the delete process. This can improve efficiency and provide a convenient way to break the request down into smaller parts.

Setting slices to auto lets Elasticsearch choose the number of slices to use. This setting will use one slice per shard, up to a certain limit. If there are multiple source data streams or indices, it will choose the number of slices based on the index or backing index with the smallest number of shards. Adding slices to the delete by query operation creates sub-requests which means it has some quirks:

  • You can see these requests in the tasks APIs. These sub-requests are "child" tasks of the task for the request with slices.
  • Fetching the status of the task for the request with slices only contains the status of completed slices.
  • These sub-requests are individually addressable for things like cancellation and rethrottling.
  • Rethrottling the request with slices will rethrottle the unfinished sub-request proportionally.
  • Canceling the request with slices will cancel each sub-request.
  • Due to the nature of slices each sub-request won't get a perfectly even portion of the documents. All documents will be addressed, but some slices may be larger than others. Expect larger slices to have a more even distribution.
  • Parameters like requests_per_second and max_docs on a request with slices are distributed proportionally to each sub-request. Combine that with the earlier point about distribution being uneven and you should conclude that using max_docs with slices might not result in exactly max_docs documents being deleted.
  • Each sub-request gets a slightly different snapshot of the source data stream or index though these are all taken at approximately the same time.

If you're slicing manually or otherwise tuning automatic slicing, keep in mind that:

  • Query performance is most efficient when the number of slices is equal to the number of shards in the index or backing index. If that number is large (for example, 500), choose a lower number as too many slices hurts performance. Setting slices higher than the number of shards generally does not improve efficiency and adds overhead.
  • Delete performance scales linearly across available resources with the number of slices.

Whether query or delete performance dominates the runtime depends on the documents being reindexed and cluster resources.

Cancel a delete by query operation

Any delete by query can be canceled using the task cancel API. For example:

POST _tasks/r1A2WoRbTwKZ516z6NEs5A:36619/_cancel

The task ID can be found by using the get tasks API.

Cancellation should happen quickly but might take a few seconds. The get task status API will continue to list the delete by query task until this task checks that it has been cancelled and terminates itself.

Path parameters

  • index string | array[string] Required

    A comma-separated list of data streams, indices, and aliases to search. It supports wildcards (*). To search all data streams or indices, omit this parameter or use * or _all.

Query parameters

  • If false, the request returns an error if any wildcard expression, index alias, or _all value targets only missing or closed indices. This behavior applies even if the request targets other open indices. For example, a request targeting foo*,bar* returns an error if an index starts with foo but no index starts with bar.

  • analyzer string

    Analyzer to use for the query string. This parameter can be used only when the q query string parameter is specified.

  • If true, wildcard and prefix queries are analyzed. This parameter can be used only when the q query string parameter is specified.

  • What to do if delete by query hits version conflicts: abort or proceed.

    Supported values include:

    • abort: Stop reindexing if there are conflicts.
    • proceed: Continue reindexing even if there are conflicts.

    Values are abort or proceed.

  • The default operator for query string query: AND or OR. This parameter can be used only when the q query string parameter is specified.

    Values are and, AND, or, or OR.

  • df string

    The field to use as default where no field prefix is given in the query string. This parameter can be used only when the q query string parameter is specified.

  • expand_wildcards string | array[string]

    The type of index that wildcard patterns can match. If the request can target data streams, this argument determines whether wildcard expressions match hidden data streams. It supports comma-separated values, such as open,hidden.

    Supported values include:

    • all: Match any data stream or index, including hidden ones.
    • open: Match open, non-hidden indices. Also matches any non-hidden data stream.
    • closed: Match closed, non-hidden indices. Also matches any non-hidden data stream. Data streams cannot be closed.
    • hidden: Match hidden data streams and hidden indices. Must be combined with open, closed, or both.
    • none: Wildcard expressions are not accepted.

    Values are all, open, closed, hidden, or none.

  • from number

    Skips the specified number of documents.

  • If false, the request returns an error if it targets a missing or closed index.

  • lenient boolean

    If true, format-based query failures (such as providing text to a numeric field) in the query string will be ignored. This parameter can be used only when the q query string parameter is specified.

  • max_docs number

    The maximum number of documents to process. Defaults to all documents. When set to a value less then or equal to scroll_size, a scroll will not be used to retrieve the results for the operation.

  • The node or shard the operation should be performed on. It is random by default.

  • refresh boolean

    If true, Elasticsearch refreshes all shards involved in the delete by query after the request completes. This is different than the delete API's refresh parameter, which causes just the shard that received the delete request to be refreshed. Unlike the delete API, it does not support wait_for.

  • If true, the request cache is used for this request. Defaults to the index-level setting.

  • The throttle for this request in sub-requests per second.

  • routing string

    A custom value used to route operations to a specific shard.

  • q string

    A query in the Lucene query string syntax.

  • scroll string

    The period to retain the search context for scrolling.

    Values are -1 or 0.

  • The size of the scroll request that powers the operation.

  • The explicit timeout for each search request. It defaults to no timeout.

    Values are -1 or 0.

  • The type of the search operation. Available options include query_then_fetch and dfs_query_then_fetch.

    Supported values include:

    • query_then_fetch: Documents are scored using local term and document frequencies for the shard. This is usually faster but less accurate.
    • dfs_query_then_fetch: Documents are scored using global term and document frequencies across all shards. This is usually slower but more accurate.

    Values are query_then_fetch or dfs_query_then_fetch.

  • slices number | string

    The number of slices this task should be divided into.

    Value is auto.

  • sort array[string]

    A comma-separated list of <field>:<direction> pairs.

  • stats array[string]

    The specific tag of the request for logging and statistical purposes.

  • The maximum number of documents to collect for each shard. If a query reaches this limit, Elasticsearch terminates the query early. Elasticsearch collects documents before sorting.

    Use with caution. Elasticsearch applies this parameter to each shard handling the request. When possible, let Elasticsearch perform early termination automatically. Avoid specifying this parameter for requests that target data streams with backing indices across multiple data tiers.

  • timeout string

    The period each deletion request waits for active shards.

    Values are -1 or 0.

  • version boolean

    If true, returns the document version as part of a hit.

  • wait_for_active_shards number | string

    The number of shard copies that must be active before proceeding with the operation. Set to all or any positive integer up to the total number of shards in the index (number_of_replicas+1). The timeout value controls how long each write request waits for unavailable shards to become available.

    Values are all or index-setting.

  • If true, the request blocks until the operation is complete. If false, Elasticsearch performs some preflight checks, launches the request, and returns a task you can use to cancel or get the status of the task. Elasticsearch creates a record of this task as a document at .tasks/task/${taskId}. When you are done with a task, you should delete the task document so Elasticsearch can reclaim the space.

application/json

Body Required

  • max_docs number

    The maximum number of documents to delete.

  • query object

    An Elasticsearch Query DSL (Domain Specific Language) object that defines a query.

    External documentation
  • slice object
    Hide slice attributes Show slice attributes object
    • field string

      Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.

    • id string Required
    • max number Required

Responses

  • 200 application/json
    Hide response attributes Show response attributes object
    • batches number

      The number of scroll responses pulled back by the delete by query.

    • deleted number

      The number of documents that were successfully deleted.

    • failures array[object]

      An array of failures if there were any unrecoverable errors during the process. If this array is not empty, the request ended abnormally because of those failures. Delete by query is implemented using batches and any failures cause the entire process to end but all failures in the current batch are collected into the array. You can use the conflicts option to prevent reindex from ending on version conflicts.

      Hide failures attributes Show failures attributes object
    • noops number

      This field is always equal to zero for delete by query. It exists only so that delete by query, update by query, and reindex APIs return responses with the same structure.

    • The number of requests per second effectively run during the delete by query.

    • retries object
      Hide retries attributes Show retries attributes object
      • bulk number Required

        The number of bulk actions retried.

    • slice_id number
    • A duration. Units can be nanos, micros, ms (milliseconds), s (seconds), m (minutes), h (hours) and d (days). Also accepts "0" without a unit and "-1" to indicate an unspecified value.

    • Time unit for milliseconds

    • A duration. Units can be nanos, micros, ms (milliseconds), s (seconds), m (minutes), h (hours) and d (days). Also accepts "0" without a unit and "-1" to indicate an unspecified value.

    • Time unit for milliseconds

    • timed_out boolean

      If true, some requests run during the delete by query operation timed out.

    • took number

      Time unit for milliseconds

    • total number

      The number of documents that were successfully processed.

    • The number of version conflicts that the delete by query hit.

POST /{index}/_delete_by_query
POST /my-index-000001,my-index-000002/_delete_by_query
{
  "query": {
    "match_all": {}
  }
}
curl \
 --request POST 'http://api.example.com/{index}/_delete_by_query' \
 --header "Authorization: $API_KEY" \
 --header "Content-Type: application/json" \
 --data '"{\n  \"query\": {\n    \"match_all\": {}\n  }\n}"'
Run `POST /my-index-000001,my-index-000002/_delete_by_query` to delete all documents from multiple data streams or indices.
{
  "query": {
    "match_all": {}
  }
}
Run `POST my-index-000001/_delete_by_query` to delete a document by using a unique attribute.
{
  "query": {
    "term": {
      "user.id": "kimchy"
    }
  },
  "max_docs": 1
}
Run `POST my-index-000001/_delete_by_query` to slice a delete by query manually. Provide a slice ID and total number of slices.
{
  "slice": {
    "id": 0,
    "max": 2
  },
  "query": {
    "range": {
      "http.response.bytes": {
        "lt": 2000000
      }
    }
  }
}
Run `POST my-index-000001/_delete_by_query?refresh&slices=5` to let delete by query automatically parallelize using sliced scroll to slice on `_id`. The `slices` query parameter value specifies the number of slices to use.
{
  "query": {
    "range": {
      "http.response.bytes": {
        "lt": 2000000
      }
    }
  }
}
Response examples (200)
A successful response from `POST /my-index-000001/_delete_by_query`.
{
  "took" : 147,
  "timed_out": false,
  "total": 119,
  "deleted": 119,
  "batches": 1,
  "version_conflicts": 0,
  "noops": 0,
  "retries": {
    "bulk": 0,
    "search": 0
  },
  "throttled_millis": 0,
  "requests_per_second": -1.0,
  "throttled_until_millis": 0,
  "failures" : [ ]
}
























































Get term vector information

GET /{index}/_termvectors/{id}

Get information and statistics about terms in the fields of a particular document.

You can retrieve term vectors for documents stored in the index or for artificial documents passed in the body of the request. You can specify the fields you are interested in through the fields parameter or by adding the fields to the request body. For example:

GET /my-index-000001/_termvectors/1?fields=message

Fields can be specified using wildcards, similar to the multi match query.

Term vectors are real-time by default, not near real-time. This can be changed by setting realtime parameter to false.

You can request three types of values: term information, term statistics, and field statistics. By default, all term information and field statistics are returned for all fields but term statistics are excluded.

Term information

  • term frequency in the field (always returned)
  • term positions (positions: true)
  • start and end offsets (offsets: true)
  • term payloads (payloads: true), as base64 encoded bytes

If the requested information wasn't stored in the index, it will be computed on the fly if possible. Additionally, term vectors could be computed for documents not even existing in the index, but instead provided by the user.


Start and end offsets assume UTF-16 encoding is being used. If you want to use these offsets in order to get the original text that produced this token, you should make sure that the string you are taking a sub-string of is also encoded using UTF-16.

Behaviour

The term and field statistics are not accurate. Deleted documents are not taken into account. The information is only retrieved for the shard the requested document resides in. The term and field statistics are therefore only useful as relative measures whereas the absolute numbers have no meaning in this context. By default, when requesting term vectors of artificial documents, a shard to get the statistics from is randomly selected. Use routing only to hit a particular shard.

Path parameters

  • index string Required

    The name of the index that contains the document.

  • id string Required

    A unique identifier for the document.

Query parameters

  • fields string | array[string]

    A comma-separated list or wildcard expressions of fields to include in the statistics. It is used as the default list unless a specific field list is provided in the completion_fields or fielddata_fields parameters.

  • If true, the response includes:

    • The document count (how many documents contain this field).
    • The sum of document frequencies (the sum of document frequencies for all terms in this field).
    • The sum of total term frequencies (the sum of total term frequencies of each term in this field).
  • offsets boolean

    If true, the response includes term offsets.

  • payloads boolean

    If true, the response includes term payloads.

  • positions boolean

    If true, the response includes term positions.

  • The node or shard the operation should be performed on. It is random by default.

  • realtime boolean

    If true, the request is real-time as opposed to near-real-time.

  • routing string

    A custom value that is used to route operations to a specific shard.

  • If true, the response includes:

    • The total term frequency (how often a term occurs in all documents).
    • The document frequency (the number of documents containing the current term).

    By default these values are not returned since term statistics can have a serious performance impact.

  • version number

    If true, returns the document version as part of a hit.

  • The version type.

    Supported values include:

    • internal: Use internal versioning that starts at 1 and increments with each update or delete.
    • external: Only index the document if the specified version is strictly higher than the version of the stored document or if there is no existing document.
    • external_gte: Only index the document if the specified version is equal or higher than the version of the stored document or if there is no existing document. NOTE: The external_gte version type is meant for special use cases and should be used with care. If used incorrectly, it can result in loss of data.
    • force: This option is deprecated because it can cause primary and replica shards to diverge.

    Values are internal, external, external_gte, or force.

application/json

Body

  • doc object

    An artificial document (a document not present in the index) for which you want to retrieve term vectors.

  • filter object
    Hide filter attributes Show filter attributes object
    • Ignore words which occur in more than this many docs. Defaults to unbounded.

    • The maximum number of terms that must be returned per field.

    • Ignore words with more than this frequency in the source doc. It defaults to unbounded.

    • The maximum word length above which words will be ignored. Defaults to unbounded.

    • Ignore terms which do not occur in at least this many docs.

    • Ignore words with less than this frequency in the source doc.

    • The minimum word length below which words will be ignored.

  • Override the default per-field analyzer. This is useful in order to generate term vectors in any fashion, especially when using artificial documents. When providing an analyzer for a field that already stores term vectors, the term vectors will be regenerated.

    Hide per_field_analyzer attribute Show per_field_analyzer attribute object
    • * string Additional properties
  • fields string | array[string]
  • If true, the response includes:

    • The document count (how many documents contain this field).
    • The sum of document frequencies (the sum of document frequencies for all terms in this field).
    • The sum of total term frequencies (the sum of total term frequencies of each term in this field).
  • offsets boolean

    If true, the response includes term offsets.

  • payloads boolean

    If true, the response includes term payloads.

  • positions boolean

    If true, the response includes term positions.

  • If true, the response includes:

    • The total term frequency (how often a term occurs in all documents).
    • The document frequency (the number of documents containing the current term).

    By default these values are not returned since term statistics can have a serious performance impact.

  • routing string
  • version number
  • Values are internal, external, external_gte, or force.

Responses

GET /{index}/_termvectors/{id}
GET /my-index-000001/_termvectors/1
{
  "fields" : ["text"],
  "offsets" : true,
  "payloads" : true,
  "positions" : true,
  "term_statistics" : true,
  "field_statistics" : true
}
curl \
 --request GET 'http://api.example.com/{index}/_termvectors/{id}' \
 --header "Authorization: $API_KEY" \
 --header "Content-Type: application/json" \
 --data '"{\n  \"fields\" : [\"text\"],\n  \"offsets\" : true,\n  \"payloads\" : true,\n  \"positions\" : true,\n  \"term_statistics\" : true,\n  \"field_statistics\" : true\n}"'
Run `GET /my-index-000001/_termvectors/1` to return all information and statistics for field `text` in document 1.
{
  "fields" : ["text"],
  "offsets" : true,
  "payloads" : true,
  "positions" : true,
  "term_statistics" : true,
  "field_statistics" : true
}
Run `GET /my-index-000001/_termvectors/1` to set per-field analyzers. A different analyzer than the one at the field may be provided by using the `per_field_analyzer` parameter.
{
  "doc" : {
    "fullname" : "John Doe",
    "text" : "test test test"
  },
  "fields": ["fullname"],
  "per_field_analyzer" : {
    "fullname": "keyword"
  }
}
Run `GET /imdb/_termvectors` to filter the terms returned based on their tf-idf scores. It returns the three most "interesting" keywords from the artificial document having the given "plot" field value. Notice that the keyword "Tony" or any stop words are not part of the response, as their tf-idf must be too low.
{
  "doc": {
    "plot": "When wealthy industrialist Tony Stark is forced to build an armored suit after a life-threatening incident, he ultimately decides to use its technology to fight against evil."
  },
  "term_statistics": true,
  "field_statistics": true,
  "positions": false,
  "offsets": false,
  "filter": {
    "max_num_terms": 3,
    "min_term_freq": 1,
    "min_doc_freq": 1
  }
}
Run `GET /my-index-000001/_termvectors/1`. Term vectors which are not explicitly stored in the index are automatically computed on the fly. This request returns all information and statistics for the fields in document 1, even though the terms haven't been explicitly stored in the index. Note that for the field text, the terms are not regenerated.
{
  "fields" : ["text", "some_field_without_term_vectors"],
  "offsets" : true,
  "positions" : true,
  "term_statistics" : true,
  "field_statistics" : true
}
Run `GET /my-index-000001/_termvectors`. Term vectors can be generated for artificial documents, that is for documents not present in the index. If dynamic mapping is turned on (default), the document fields not in the original mapping will be dynamically created.
{
  "doc" : {
    "fullname" : "John Doe",
    "text" : "test test test"
  }
}
Response examples (200)
A successful response from `GET /my-index-000001/_termvectors/1`.
{
  "_index": "my-index-000001",
  "_id": "1",
  "_version": 1,
  "found": true,
  "took": 6,
  "term_vectors": {
    "text": {
      "field_statistics": {
        "sum_doc_freq": 4,
        "doc_count": 2,
        "sum_ttf": 6
      },
      "terms": {
        "test": {
          "doc_freq": 2,
          "ttf": 4,
          "term_freq": 3,
          "tokens": [
            {
              "position": 0,
              "start_offset": 0,
              "end_offset": 4,
              "payload": "d29yZA=="
            },
            {
              "position": 1,
              "start_offset": 5,
              "end_offset": 9,
              "payload": "d29yZA=="
            },
            {
              "position": 2,
              "start_offset": 10,
              "end_offset": 14,
              "payload": "d29yZA=="
            }
          ]
        }
      }
    }
  }
}
A successful response from `GET /my-index-000001/_termvectors` with `per_field_analyzer` in the request body.
{
  "_index": "my-index-000001",
  "_version": 0,
  "found": true,
  "took": 6,
  "term_vectors": {
    "fullname": {
      "field_statistics": {
          "sum_doc_freq": 2,
          "doc_count": 4,
          "sum_ttf": 4
      },
      "terms": {
          "John Doe": {
            "term_freq": 1,
            "tokens": [
                {
                  "position": 0,
                  "start_offset": 0,
                  "end_offset": 8
                }
            ]
          }
      }
    }
  }
}
A successful response from `GET /my-index-000001/_termvectors` with a `filter` in the request body.
{
  "_index": "imdb",
  "_version": 0,
  "found": true,
  "term_vectors": {
      "plot": {
        "field_statistics": {
            "sum_doc_freq": 3384269,
            "doc_count": 176214,
            "sum_ttf": 3753460
        },
        "terms": {
            "armored": {
              "doc_freq": 27,
              "ttf": 27,
              "term_freq": 1,
              "score": 9.74725
            },
            "industrialist": {
              "doc_freq": 88,
              "ttf": 88,
              "term_freq": 1,
              "score": 8.590818
            },
            "stark": {
              "doc_freq": 44,
              "ttf": 47,
              "term_freq": 1,
              "score": 9.272792
            }
        }
      }
  }
}




Get term vector information

GET /{index}/_termvectors

Get information and statistics about terms in the fields of a particular document.

You can retrieve term vectors for documents stored in the index or for artificial documents passed in the body of the request. You can specify the fields you are interested in through the fields parameter or by adding the fields to the request body. For example:

GET /my-index-000001/_termvectors/1?fields=message

Fields can be specified using wildcards, similar to the multi match query.

Term vectors are real-time by default, not near real-time. This can be changed by setting realtime parameter to false.

You can request three types of values: term information, term statistics, and field statistics. By default, all term information and field statistics are returned for all fields but term statistics are excluded.

Term information

  • term frequency in the field (always returned)
  • term positions (positions: true)
  • start and end offsets (offsets: true)
  • term payloads (payloads: true), as base64 encoded bytes

If the requested information wasn't stored in the index, it will be computed on the fly if possible. Additionally, term vectors could be computed for documents not even existing in the index, but instead provided by the user.


Start and end offsets assume UTF-16 encoding is being used. If you want to use these offsets in order to get the original text that produced this token, you should make sure that the string you are taking a sub-string of is also encoded using UTF-16.

Behaviour

The term and field statistics are not accurate. Deleted documents are not taken into account. The information is only retrieved for the shard the requested document resides in. The term and field statistics are therefore only useful as relative measures whereas the absolute numbers have no meaning in this context. By default, when requesting term vectors of artificial documents, a shard to get the statistics from is randomly selected. Use routing only to hit a particular shard.

Path parameters

  • index string Required

    The name of the index that contains the document.

Query parameters

  • fields string | array[string]

    A comma-separated list or wildcard expressions of fields to include in the statistics. It is used as the default list unless a specific field list is provided in the completion_fields or fielddata_fields parameters.

  • If true, the response includes:

    • The document count (how many documents contain this field).
    • The sum of document frequencies (the sum of document frequencies for all terms in this field).
    • The sum of total term frequencies (the sum of total term frequencies of each term in this field).
  • offsets boolean

    If true, the response includes term offsets.

  • payloads boolean

    If true, the response includes term payloads.

  • positions boolean

    If true, the response includes term positions.

  • The node or shard the operation should be performed on. It is random by default.

  • realtime boolean

    If true, the request is real-time as opposed to near-real-time.

  • routing string

    A custom value that is used to route operations to a specific shard.

  • If true, the response includes:

    • The total term frequency (how often a term occurs in all documents).
    • The document frequency (the number of documents containing the current term).

    By default these values are not returned since term statistics can have a serious performance impact.

  • version number

    If true, returns the document version as part of a hit.

  • The version type.

    Supported values include:

    • internal: Use internal versioning that starts at 1 and increments with each update or delete.
    • external: Only index the document if the specified version is strictly higher than the version of the stored document or if there is no existing document.
    • external_gte: Only index the document if the specified version is equal or higher than the version of the stored document or if there is no existing document. NOTE: The external_gte version type is meant for special use cases and should be used with care. If used incorrectly, it can result in loss of data.
    • force: This option is deprecated because it can cause primary and replica shards to diverge.

    Values are internal, external, external_gte, or force.

application/json

Body

  • doc object

    An artificial document (a document not present in the index) for which you want to retrieve term vectors.

  • filter object
    Hide filter attributes Show filter attributes object
    • Ignore words which occur in more than this many docs. Defaults to unbounded.

    • The maximum number of terms that must be returned per field.

    • Ignore words with more than this frequency in the source doc. It defaults to unbounded.

    • The maximum word length above which words will be ignored. Defaults to unbounded.

    • Ignore terms which do not occur in at least this many docs.

    • Ignore words with less than this frequency in the source doc.

    • The minimum word length below which words will be ignored.

  • Override the default per-field analyzer. This is useful in order to generate term vectors in any fashion, especially when using artificial documents. When providing an analyzer for a field that already stores term vectors, the term vectors will be regenerated.

    Hide per_field_analyzer attribute Show per_field_analyzer attribute object
    • * string Additional properties
  • fields string | array[string]
  • If true, the response includes:

    • The document count (how many documents contain this field).
    • The sum of document frequencies (the sum of document frequencies for all terms in this field).
    • The sum of total term frequencies (the sum of total term frequencies of each term in this field).
  • offsets boolean

    If true, the response includes term offsets.

  • payloads boolean

    If true, the response includes term payloads.

  • positions boolean

    If true, the response includes term positions.

  • If true, the response includes:

    • The total term frequency (how often a term occurs in all documents).
    • The document frequency (the number of documents containing the current term).

    By default these values are not returned since term statistics can have a serious performance impact.

  • routing string
  • version number
  • Values are internal, external, external_gte, or force.

Responses

GET /{index}/_termvectors
GET /my-index-000001/_termvectors/1
{
  "fields" : ["text"],
  "offsets" : true,
  "payloads" : true,
  "positions" : true,
  "term_statistics" : true,
  "field_statistics" : true
}
curl \
 --request GET 'http://api.example.com/{index}/_termvectors' \
 --header "Authorization: $API_KEY" \
 --header "Content-Type: application/json" \
 --data '"{\n  \"fields\" : [\"text\"],\n  \"offsets\" : true,\n  \"payloads\" : true,\n  \"positions\" : true,\n  \"term_statistics\" : true,\n  \"field_statistics\" : true\n}"'
Run `GET /my-index-000001/_termvectors/1` to return all information and statistics for field `text` in document 1.
{
  "fields" : ["text"],
  "offsets" : true,
  "payloads" : true,
  "positions" : true,
  "term_statistics" : true,
  "field_statistics" : true
}
Run `GET /my-index-000001/_termvectors/1` to set per-field analyzers. A different analyzer than the one at the field may be provided by using the `per_field_analyzer` parameter.
{
  "doc" : {
    "fullname" : "John Doe",
    "text" : "test test test"
  },
  "fields": ["fullname"],
  "per_field_analyzer" : {
    "fullname": "keyword"
  }
}
Run `GET /imdb/_termvectors` to filter the terms returned based on their tf-idf scores. It returns the three most "interesting" keywords from the artificial document having the given "plot" field value. Notice that the keyword "Tony" or any stop words are not part of the response, as their tf-idf must be too low.
{
  "doc": {
    "plot": "When wealthy industrialist Tony Stark is forced to build an armored suit after a life-threatening incident, he ultimately decides to use its technology to fight against evil."
  },
  "term_statistics": true,
  "field_statistics": true,
  "positions": false,
  "offsets": false,
  "filter": {
    "max_num_terms": 3,
    "min_term_freq": 1,
    "min_doc_freq": 1
  }
}
Run `GET /my-index-000001/_termvectors/1`. Term vectors which are not explicitly stored in the index are automatically computed on the fly. This request returns all information and statistics for the fields in document 1, even though the terms haven't been explicitly stored in the index. Note that for the field text, the terms are not regenerated.
{
  "fields" : ["text", "some_field_without_term_vectors"],
  "offsets" : true,
  "positions" : true,
  "term_statistics" : true,
  "field_statistics" : true
}
Run `GET /my-index-000001/_termvectors`. Term vectors can be generated for artificial documents, that is for documents not present in the index. If dynamic mapping is turned on (default), the document fields not in the original mapping will be dynamically created.
{
  "doc" : {
    "fullname" : "John Doe",
    "text" : "test test test"
  }
}
Response examples (200)
A successful response from `GET /my-index-000001/_termvectors/1`.
{
  "_index": "my-index-000001",
  "_id": "1",
  "_version": 1,
  "found": true,
  "took": 6,
  "term_vectors": {
    "text": {
      "field_statistics": {
        "sum_doc_freq": 4,
        "doc_count": 2,
        "sum_ttf": 6
      },
      "terms": {
        "test": {
          "doc_freq": 2,
          "ttf": 4,
          "term_freq": 3,
          "tokens": [
            {
              "position": 0,
              "start_offset": 0,
              "end_offset": 4,
              "payload": "d29yZA=="
            },
            {
              "position": 1,
              "start_offset": 5,
              "end_offset": 9,
              "payload": "d29yZA=="
            },
            {
              "position": 2,
              "start_offset": 10,
              "end_offset": 14,
              "payload": "d29yZA=="
            }
          ]
        }
      }
    }
  }
}
A successful response from `GET /my-index-000001/_termvectors` with `per_field_analyzer` in the request body.
{
  "_index": "my-index-000001",
  "_version": 0,
  "found": true,
  "took": 6,
  "term_vectors": {
    "fullname": {
      "field_statistics": {
          "sum_doc_freq": 2,
          "doc_count": 4,
          "sum_ttf": 4
      },
      "terms": {
          "John Doe": {
            "term_freq": 1,
            "tokens": [
                {
                  "position": 0,
                  "start_offset": 0,
                  "end_offset": 8
                }
            ]
          }
      }
    }
  }
}
A successful response from `GET /my-index-000001/_termvectors` with a `filter` in the request body.
{
  "_index": "imdb",
  "_version": 0,
  "found": true,
  "term_vectors": {
      "plot": {
        "field_statistics": {
            "sum_doc_freq": 3384269,
            "doc_count": 176214,
            "sum_ttf": 3753460
        },
        "terms": {
            "armored": {
              "doc_freq": 27,
              "ttf": 27,
              "term_freq": 1,
              "score": 9.74725
            },
            "industrialist": {
              "doc_freq": 88,
              "ttf": 88,
              "term_freq": 1,
              "score": 8.590818
            },
            "stark": {
              "doc_freq": 44,
              "ttf": 47,
              "term_freq": 1,
              "score": 9.272792
            }
        }
      }
  }
}



















































































































































Create or update a component template Added in 7.8.0

POST /_component_template/{name}

Component templates are building blocks for constructing index templates that specify index mappings, settings, and aliases.

An index template can be composed of multiple component templates. To use a component template, specify it in an index template’s composed_of list. Component templates are only applied to new data streams and indices as part of a matching index template.

Settings and mappings specified directly in the index template or the create index request override any settings or mappings specified in a component template.

Component templates are only used during index creation. For data streams, this includes data stream creation and the creation of a stream’s backing indices. Changes to component templates do not affect existing indices, including a stream’s backing indices.

You can use C-style /* *\/ block comments in component templates. You can include comments anywhere in the request body except before the opening curly bracket.

Applying component templates

You cannot directly apply a component template to a data stream or index. To be applied, a component template must be included in an index template's composed_of list.

Path parameters

  • name string Required

    Name of the component template to create. Elasticsearch includes the following built-in component templates: logs-mappings; logs-settings; metrics-mappings; metrics-settings;synthetics-mapping; synthetics-settings. Elastic Agent uses these templates to configure backing indices for its data streams. If you use Elastic Agent and want to overwrite one of these templates, set the version for your replacement template higher than the current version. If you don’t use Elastic Agent and want to disable all built-in component and index templates, set stack.templates.enabled to false using the cluster update settings API.

Query parameters

  • create boolean

    If true, this request cannot replace or update existing component templates.

  • Period to wait for a connection to the master node. If no response is received before the timeout expires, the request fails and returns an error.

    Values are -1 or 0.

application/json

Body Required

Responses

  • 200 application/json
    Hide response attribute Show response attribute object
    • acknowledged boolean Required

      For a successful response, this value is always true. On failure, an exception is returned instead.

POST /_component_template/{name}
PUT _component_template/template_1
{
  "template": null,
  "settings": {
    "number_of_shards": 1
  },
  "mappings": {
    "_source": {
      "enabled": false
    },
    "properties": {
      "host_name": {
        "type": "keyword"
      },
      "created_at": {
        "type": "date",
        "format": "EEE MMM dd HH:mm:ss Z yyyy"
      }
    }
  }
}
curl \
 --request POST 'http://api.example.com/_component_template/{name}' \
 --header "Authorization: $API_KEY" \
 --header "Content-Type: application/json" \
 --data '"{\n  \"template\": null,\n  \"settings\": {\n    \"number_of_shards\": 1\n  },\n  \"mappings\": {\n    \"_source\": {\n      \"enabled\": false\n    },\n    \"properties\": {\n      \"host_name\": {\n        \"type\": \"keyword\"\n      },\n      \"created_at\": {\n        \"type\": \"date\",\n        \"format\": \"EEE MMM dd HH:mm:ss Z yyyy\"\n      }\n    }\n  }\n}"'
Request examples
{
  "template": null,
  "settings": {
    "number_of_shards": 1
  },
  "mappings": {
    "_source": {
      "enabled": false
    },
    "properties": {
      "host_name": {
        "type": "keyword"
      },
      "created_at": {
        "type": "date",
        "format": "EEE MMM dd HH:mm:ss Z yyyy"
      }
    }
  }
}
You can include index aliases in a component template. During index creation, the `{index}` placeholder in the alias name will be replaced with the actual index name that the template gets applied to.
{
  "template": null,
  "settings": {
    "number_of_shards": 1
  },
  "aliases": {
    "alias1": {},
    "alias2": {
      "filter": {
        "term": {
          "user.id": "kimchy"
        }
      },
      "routing": "shard-1"
    },
    "{index}-alias": {}
  }
}












































































Check indices

HEAD /{index}

Check if one or more indices, index aliases, or data streams exist.

Path parameters

  • index string | array[string] Required

    Comma-separated list of data streams, indices, and aliases. Supports wildcards (*).

Query parameters

  • If false, the request returns an error if any wildcard expression, index alias, or _all value targets only missing or closed indices. This behavior applies even if the request targets other open indices.

  • expand_wildcards string | array[string]

    Type of index that wildcard patterns can match. If the request can target data streams, this argument determines whether wildcard expressions match hidden data streams. Supports comma-separated values, such as open,hidden. Valid values are: all, open, closed, hidden, none.

    Supported values include:

    • all: Match any data stream or index, including hidden ones.
    • open: Match open, non-hidden indices. Also matches any non-hidden data stream.
    • closed: Match closed, non-hidden indices. Also matches any non-hidden data stream. Data streams cannot be closed.
    • hidden: Match hidden data streams and hidden indices. Must be combined with open, closed, or both.
    • none: Wildcard expressions are not accepted.

    Values are all, open, closed, hidden, or none.

  • If true, returns settings in flat format.

  • If false, the request returns an error if it targets a missing or closed index.

  • If true, return all default settings in the response.

  • local boolean

    If true, the request retrieves information from the local node only.

Responses

HEAD /{index}
curl \
 --request HEAD 'http://api.example.com/{index}' \
 --header "Authorization: $API_KEY"




































Delete data stream options Added in 8.19.0

DELETE /_data_stream/{name}/_options

Removes the data stream options from a data stream.

Path parameters

  • name string | array[string] Required

    A comma-separated list of data streams of which the data stream options will be deleted; use * to get all data streams

Query parameters

  • expand_wildcards string | array[string]

    Whether wildcard expressions should get expanded to open or closed indices (default: open)

    Supported values include:

    • all: Match any data stream or index, including hidden ones.
    • open: Match open, non-hidden indices. Also matches any non-hidden data stream.
    • closed: Match closed, non-hidden indices. Also matches any non-hidden data stream. Data streams cannot be closed.
    • hidden: Match hidden data streams and hidden indices. Must be combined with open, closed, or both.
    • none: Wildcard expressions are not accepted.

    Values are all, open, closed, hidden, or none.

  • Specify timeout for connection to master

    Values are -1 or 0.

  • timeout string

    Explicit timestamp for the document

    Values are -1 or 0.

Responses

  • 200 application/json
    Hide response attribute Show response attribute object
    • acknowledged boolean Required

      For a successful response, this value is always true. On failure, an exception is returned instead.

DELETE /_data_stream/{name}/_options
curl \
 --request DELETE 'http://api.example.com/_data_stream/{name}/_options' \
 --header "Authorization: $API_KEY"
Response examples (200)
A successful response for deleting data stream options.
{
  "acknowledged": true
}
































































































































Update index settings

PUT /{index}/_settings

Changes dynamic index settings in real time. For data streams, index setting changes are applied to all backing indices by default.

To revert a setting to the default value, use a null value. The list of per-index settings that can be updated dynamically on live indices can be found in index settings documentation. To preserve existing settings from being updated, set the preserve_existing parameter to true.

There are multiple valid ways to represent index settings in the request body. You can specify only the setting, for example:

{
  "number_of_replicas": 1
}

Or you can use an index setting object:

{
  "index": {
    "number_of_replicas": 1
  }
}

Or you can use dot annotation:

{
  "index.number_of_replicas": 1
}

Or you can embed any of the aforementioned options in a settings object. For example:

{
  "settings": {
    "index": {
      "number_of_replicas": 1
    }
  }
}

NOTE: You can only define new analyzers on closed indices. To add an analyzer, you must close the index, define the analyzer, and reopen the index. You cannot close the write index of a data stream. To update the analyzer for a data stream's write index and future backing indices, update the analyzer in the index template used by the stream. Then roll over the data stream to apply the new analyzer to the stream's write index and future backing indices. This affects searches and any new data added to the stream after the rollover. However, it does not affect the data stream's backing indices or their existing data. To change the analyzer for existing backing indices, you must create a new data stream and reindex your data into it.

External documentation

Path parameters

  • index string | array[string] Required

    Comma-separated list of data streams, indices, and aliases used to limit the request. Supports wildcards (*). To target all data streams and indices, omit this parameter or use * or _all.

Query parameters

  • If false, the request returns an error if any wildcard expression, index alias, or _all value targets only missing or closed indices. This behavior applies even if the request targets other open indices. For example, a request targeting foo*,bar* returns an error if an index starts with foo but no index starts with bar.

  • expand_wildcards string | array[string]

    Type of index that wildcard patterns can match. If the request can target data streams, this argument determines whether wildcard expressions match hidden data streams. Supports comma-separated values, such as open,hidden.

    Supported values include:

    • all: Match any data stream or index, including hidden ones.
    • open: Match open, non-hidden indices. Also matches any non-hidden data stream.
    • closed: Match closed, non-hidden indices. Also matches any non-hidden data stream. Data streams cannot be closed.
    • hidden: Match hidden data streams and hidden indices. Must be combined with open, closed, or both.
    • none: Wildcard expressions are not accepted.

    Values are all, open, closed, hidden, or none.

  • If true, returns settings in flat format.

  • If true, returns settings in flat format.

  • Period to wait for a connection to the master node. If no response is received before the timeout expires, the request fails and returns an error.

    Values are -1 or 0.

  • If true, existing index settings remain unchanged.

  • reopen boolean

    Whether to close and reopen the index to apply non-dynamic settings. If set to true the indices to which the settings are being applied will be closed temporarily and then reopened in order to apply the changes.

  • timeout string

    Period to wait for a response. If no response is received before the timeout expires, the request fails and returns an error.

    Values are -1 or 0.

application/json

Responses

  • 200 application/json
    Hide response attribute Show response attribute object
    • acknowledged boolean Required

      For a successful response, this value is always true. On failure, an exception is returned instead.

PUT /{index}/_settings
PUT /my-index-000001/_settings
{
  "index" : {
    "number_of_replicas" : 2
  }
}
curl \
 --request PUT 'http://api.example.com/{index}/_settings' \
 --header "Authorization: $API_KEY" \
 --header "Content-Type: application/json" \
 --data '"{\n  \"index\" : {\n    \"number_of_replicas\" : 2\n  }\n}"'
{
  "index" : {
    "number_of_replicas" : 2
  }
}
To revert a setting to the default value, use `null`.
{
  "index" : {
    "refresh_interval" : null
  }
}
To add an analyzer, you must close the index, define the analyzer, then reopen the index.
{
  "analysis" : {
    "analyzer":{
      "content":{
        "type":"custom",
        "tokenizer":"whitespace"
      }
    }
  }
}

POST /my-index-000001/_open












































































































Split an index Added in 6.1.0

POST /{index}/_split/{target}

Split an index into a new index with more primary shards.

  • Before you can split an index:

  • The index must be read-only.

  • The cluster health status must be green.

You can do make an index read-only with the following request using the add index block API:

PUT /my_source_index/_block/write

The current write index on a data stream cannot be split. In order to split the current write index, the data stream must first be rolled over so that a new write index is created and then the previous write index can be split.

The number of times the index can be split (and the number of shards that each original shard can be split into) is determined by the index.number_of_routing_shards setting. The number of routing shards specifies the hashing space that is used internally to distribute documents across shards with consistent hashing. For instance, a 5 shard index with number_of_routing_shards set to 30 (5 x 2 x 3) could be split by a factor of 2 or 3.

A split operation:

  • Creates a new target index with the same definition as the source index, but with a larger number of primary shards.
  • Hard-links segments from the source index into the target index. If the file system doesn't support hard-linking, all segments are copied into the new index, which is a much more time consuming process.
  • Hashes all documents again, after low level files are created, to delete documents that belong to a different shard.
  • Recovers the target index as though it were a closed index which had just been re-opened.

IMPORTANT: Indices can only be split if they satisfy the following requirements:

  • The target index must not exist.
  • The source index must have fewer primary shards than the target index.
  • The number of primary shards in the target index must be a multiple of the number of primary shards in the source index.
  • The node handling the split process must have sufficient free disk space to accommodate a second copy of the existing index.

Path parameters

  • index string Required

    Name of the source index to split.

  • target string Required

    Name of the target index to create.

Query parameters

  • Period to wait for a connection to the master node. If no response is received before the timeout expires, the request fails and returns an error.

    Values are -1 or 0.

  • timeout string

    Period to wait for a response. If no response is received before the timeout expires, the request fails and returns an error.

    Values are -1 or 0.

  • wait_for_active_shards number | string

    The number of shard copies that must be active before proceeding with the operation. Set to all or any positive integer up to the total number of shards in the index (number_of_replicas+1).

    Values are all or index-setting.

application/json

Body

  • aliases object

    Aliases for the resulting index.

    Hide aliases attribute Show aliases attribute object
  • settings object

    Configuration options for the target index.

    Hide settings attribute Show settings attribute object
    • * object Additional properties

Responses

POST /{index}/_split/{target}
POST /my-index-000001/_split/split-my-index-000001
{
  "settings": {
    "index.number_of_shards": 2
  }
}
curl \
 --request POST 'http://api.example.com/{index}/_split/{target}' \
 --header "Authorization: $API_KEY" \
 --header "Content-Type: application/json" \
 --data '"{\n  \"settings\": {\n    \"index.number_of_shards\": 2\n  }\n}"'
Request example
Split an existing index into a new index with more primary shards.
{
  "settings": {
    "index.number_of_shards": 2
  }
}









































































Retry a policy Added in 6.6.0

POST /{index}/_ilm/retry

Retry running the lifecycle policy for an index that is in the ERROR step. The API sets the policy back to the step where the error occurred and runs the step. Use the explain lifecycle state API to determine whether an index is in the ERROR step.

Path parameters

  • index string Required

    The name of the indices (comma-separated) whose failed lifecycle step is to be retry

Responses

  • 200 application/json
    Hide response attribute Show response attribute object
    • acknowledged boolean Required

      For a successful response, this value is always true. On failure, an exception is returned instead.

POST /{index}/_ilm/retry
curl \
 --request POST 'http://api.example.com/{index}/_ilm/retry' \
 --header "Authorization: $API_KEY"








Inference

Inference APIs enable you to use certain services, such as built-in machine learning models (ELSER, E5), models uploaded through Eland, Cohere, OpenAI, Azure, Google AI Studio or Hugging Face. For built-in models and models uploaded through Eland, the inference APIs offer an alternative way to use and manage trained models. However, if you do not plan to use the inference APIs to use these models or if you want to use non-NLP models, use the machine learning trained model APIs.