Index API

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

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. For more information about field mapping, see mapping and the update mapping API.

Automatic index creation is controlled by the action.auto_create_index setting. This setting defaults to true, which allows any index to 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 disable 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.

response = client.cluster.put_settings(
  body: {
    persistent: {
      "action.auto_create_index": 'my-index-000001,index10,-index1*,+ind*'
    }
  }
)
puts response

response = client.cluster.put_settings(
  body: {
    persistent: {
      "action.auto_create_index": 'false'
    }
  }
)
puts response

response = client.cluster.put_settings(
  body: {
    persistent: {
      "action.auto_create_index": 'true'
    }
  }
)
puts response

PUT _cluster/settings
{
  "persistent": {
    "action.auto_create_index": "my-index-000001,index10,-index1*,+ind*" 
  }
}

PUT _cluster/settings
{
  "persistent": {
    "action.auto_create_index": "false" 
  }
}

PUT _cluster/settings
{
  "persistent": {
    "action.auto_create_index": "true" 
  }
}

You can force a create operation by using the _create resource or setting the op_type parameter to create. In this case, the index operation fails if a document with the specified ID already exists in the index.

When using the POST /<target>/_doc/ request format, the op_type is automatically set to create and the index operation generates a unique ID for the document.

POST my-index-000001/_doc/
{
  "@timestamp": "2099-11-15T13:12:00",
  "message": "GET /search HTTP/1.1 200 1070000",
  "user": {
    "id": "kimchy"
  }
}

The API returns the following result:

{
  "_shards": {
    "total": 2,
    "failed": 0,
    "successful": 2
  },
  "_index": "my-index-000001",
  "_id": "W0tpsmIBdwcYyG50zbta",
  "_version": 1,
  "_seq_no": 0,
  "_primary_term": 1,
  "result": "created"
}

Index operations can be made conditional and only be performed if the last modification to the document was assigned the sequence number and primary term specified by the if_seq_no and if_primary_term parameters. If a mismatch is detected, the operation will result in a VersionConflictException and a status code of 409. See Optimistic concurrency control for more details.

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. For example:

POST my-index-000001/_doc?routing=kimchy
{
  "@timestamp": "2099-11-15T13:12:00",
  "message": "GET /search HTTP/1.1 200 1070000",
  "user": {
    "id": "kimchy"
  }
}

In this example, the document is routed to a shard based on the routing parameter provided: "kimchy".

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.

The index operation is directed to the primary shard based on its route (see the Routing section above) 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.

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 (i.e. wait_for_active_shards=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, the wait_for_active_shards request parameter can be used.

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 we have a cluster of three nodes, A, B, and C and we 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 we 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 3 nodes are up), then the indexing operation will require 3 active shard copies before proceeding, a requirement which should be met because there are 3 active nodes in the cluster, each one holding a copy of the shard. However, if we set wait_for_active_shards to all (or to 4, which is the same), the indexing operation will not proceed as we 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 commences. Once 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 write operation’s response reveals the number of shard copies on which replication succeeded/failed.

{
  "_shards": {
    "total": 2,
    "failed": 0,
    "successful": 2
  }
}

Control when the changes made by this request are visible to search. See refresh.

When updating a document using the index API a new version of the document is always created even if the document hasn’t changed. If this isn’t acceptable use the _update API with detect_noop set to true. This option isn’t available on the index API because the index API doesn’t fetch the old source and isn’t able to compare it against the new source.

There isn’t a hard and fast rule about when noop updates aren’t acceptable. It’s a combination of lots of factors like how frequently your data source sends updates that are actually noops and how many queries per second Elasticsearch runs on the shard receiving the updates.

The primary shard assigned to perform the index operation might not be available when the index operation is executed. Some reasons for this might be that the primary shard is currently recovering from a gateway or undergoing relocation. By default, the index operation will wait on the primary shard to become available for up to 1 minute before failing and responding with an error. The timeout parameter can be used to explicitly specify how long it waits. Here is an example of setting it to 5 minutes:

PUT my-index-000001/_doc/1?timeout=5m
{
  "@timestamp": "2099-11-15T13:12:00",
  "message": "GET /search HTTP/1.1 200 1070000",
  "user": {
    "id": "kimchy"
  }
}

Each indexed document is given a version number. By default, internal versioning is used that starts at 1 and increments with each update, deletes included. Optionally, the version number can be set to an external value (for example, if maintained in a database). To enable this functionality, version_type should be set to external. The value provided must be a numeric, long value greater than or equal to 0, and less than around 9.2e+18.

When using the external version type, the system checks to see if the version number passed to the index request is greater than the version of the currently stored document. If true, the document will be indexed and the new version number used. If the value provided is less than or equal to the stored document’s version number, a version conflict will occur and the index operation will fail. For example:

response = client.index(
  index: 'my-index-000001',
  id: 1,
  version: 2,
  version_type: 'external',
  body: {
    user: {
      id: 'elkbee'
    }
  }
)
puts response

PUT my-index-000001/_doc/1?version=2&version_type=external
{
  "user": {
    "id": "elkbee"
  }
}

In the previous example, the operation will succeed since the supplied version of 2 is higher than the current document version of 1. If the document was already updated and its version was set to 2 or higher, the indexing command will fail and result in a conflict (409 http status code).

A nice side effect is that there is no need to maintain strict ordering of async indexing operations executed as a result of changes to a source database, as long as version numbers from the source database are used. Even the simple case of updating the Elasticsearch index using data from a database is simplified if external versioning is used, as only the latest version will be used if the index operations arrive out of order for whatever reason.

In addition to the external version type, Elasticsearch also supports other types for specific use cases: