http://api.example.comElasticsearch provides REST APIs that are used by the UI components and can be called directly to configure and access Elasticsearch features.
This documentation is derived from the main branch of the elasticsearch-specification repository. It is provided under license Attribution-NonCommercial-NoDerivatives 4.0 International.
This documentation contains work-in-progress information for future Elastic Stack releases.
Last update on Aug 20, 2025.
This API is provided under license Apache 2.0.
The API accepts 3 different authentication methods:
Elasticsearch APIs support key-based authentication. You must create an API key and use the encoded value in the request header. For example:
curl -X GET "${ES_URL}/_cat/indices?v=true" \
-H "Authorization: ApiKey ${API_KEY}"
To get API keys, use the /_security/api_key APIs.
Elasticsearch APIs support the use of bearer tokens in the Authorization HTTP header to authenticate with the API.
For examples, refer to Token-based authentication services
The autoscaling APIs enable you to create and manage autoscaling policies and retrieve information about autoscaling capacity. Autoscaling adjusts resources based on demand. A deployment can use autoscaling to scale resources as needed, ensuring sufficient capacity to meet workload requirements.
NOTE: This feature is designed for indirect use by Elasticsearch Service, Elastic Cloud Enterprise, and Elastic Cloud on Kubernetes. Direct use is not supported.
GET /_autoscaling/policy/my_autoscaling_policy
resp = client.autoscaling.get_autoscaling_policy(
name="my_autoscaling_policy",
)const response = await client.autoscaling.getAutoscalingPolicy({
name: "my_autoscaling_policy",
});response = client.autoscaling.get_autoscaling_policy(
name: "my_autoscaling_policy"
)$resp = $client->autoscaling()->getAutoscalingPolicy([
"name" => "my_autoscaling_policy",
]);curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_autoscaling/policy/my_autoscaling_policy"client.autoscaling().getAutoscalingPolicy(g -> g
.name("my_autoscaling_policy")
);
{
"roles": <roles>,
"deciders": <deciders>
}NOTE: This feature is designed for indirect use by Elasticsearch Service, Elastic Cloud Enterprise, and Elastic Cloud on Kubernetes. Direct use is not supported.
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.
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.
Decider settings.
PUT /_autoscaling/policy/<name>
{
"roles": [],
"deciders": {
"fixed": {
}
}
}resp = client.autoscaling.put_autoscaling_policy(
name="<name>",
policy={
"roles": [],
"deciders": {
"fixed": {}
}
},
)const response = await client.autoscaling.putAutoscalingPolicy({
name: "<name>",
policy: {
roles: [],
deciders: {
fixed: {},
},
},
});response = client.autoscaling.put_autoscaling_policy(
name: "<name>",
body: {
"roles": [],
"deciders": {
"fixed": {}
}
}
)$resp = $client->autoscaling()->putAutoscalingPolicy([
"name" => "<name>",
"body" => [
"roles" => array(
),
"deciders" => [
"fixed" => new ArrayObject([]),
],
],
]);curl -X PUT -H "Authorization: ApiKey $ELASTIC_API_KEY" -H "Content-Type: application/json" -d '{"roles":[],"deciders":{"fixed":{}}}' "$ELASTICSEARCH_URL/_autoscaling/policy/<name>"client.autoscaling().putAutoscalingPolicy(p -> p
.name("<name>")
.policy(po -> po
.deciders("fixed", JsonData.fromJson("{}"))
)
);
{
"roles": [],
"deciders": {
"fixed": {
}
}
}{
"roles" : [ "data_hot" ],
"deciders": {
"fixed": {
}
}
}{
"acknowledged": true
}NOTE: This feature is designed for indirect use by Elasticsearch Service, Elastic Cloud Enterprise, and Elastic Cloud on Kubernetes. Direct use is not supported.
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.
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.
DELETE /_autoscaling/policy/*
resp = client.autoscaling.delete_autoscaling_policy(
name="*",
)const response = await client.autoscaling.deleteAutoscalingPolicy({
name: "*",
});response = client.autoscaling.delete_autoscaling_policy(
name: "*"
)$resp = $client->autoscaling()->deleteAutoscalingPolicy([
"name" => "*",
]);curl -X DELETE -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_autoscaling/policy/*"client.autoscaling().deleteAutoscalingPolicy(d -> d
.name("*")
);
{
"acknowledged": true
}NOTE: This feature is designed for indirect use by Elasticsearch Service, Elastic Cloud Enterprise, and Elastic Cloud on Kubernetes. Direct use is not supported.
This API gets the current autoscaling capacity based on the configured autoscaling policy. It will return information to size the cluster appropriately to the current workload.
The required_capacity is calculated as the maximum of the required_capacity result of all individual deciders that are enabled for the policy.
The operator should verify that the current_nodes match the operator’s knowledge of the cluster to avoid making autoscaling decisions based on stale or incomplete information.
The response contains decider-specific information you can use to diagnose how and why autoscaling determined a certain capacity was required. This information is provided for diagnosis only. Do not use this information to make autoscaling decisions.
GET /_autoscaling/capacity
resp = client.autoscaling.get_autoscaling_capacity()const response = await client.autoscaling.getAutoscalingCapacity();response = client.autoscaling.get_autoscaling_capacity$resp = $client->autoscaling()->getAutoscalingCapacity();curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_autoscaling/capacity"client.autoscaling().getAutoscalingCapacity(g -> g);
{
policies: {}
}All methods and paths for this operation:
GET _application/analytics/my*
resp = client.search_application.get_behavioral_analytics(
name="my*",
)const response = await client.searchApplication.getBehavioralAnalytics({
name: "my*",
});response = client.search_application.get_behavioral_analytics(
name: "my*"
)$resp = $client->searchApplication()->getBehavioralAnalytics([
"name" => "my*",
]);curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_application/analytics/my*"client.searchApplication().getBehavioralAnalytics(g -> g
.name("my*")
);
{
"my_analytics_collection": {
"event_data_stream": {
"name": "behavioral_analytics-events-my_analytics_collection"
}
},
"my_analytics_collection2": {
"event_data_stream": {
"name": "behavioral_analytics-events-my_analytics_collection2"
}
}
}PUT _application/analytics/my_analytics_collection
resp = client.search_application.put_behavioral_analytics(
name="my_analytics_collection",
)const response = await client.searchApplication.putBehavioralAnalytics({
name: "my_analytics_collection",
});response = client.search_application.put_behavioral_analytics(
name: "my_analytics_collection"
)$resp = $client->searchApplication()->putBehavioralAnalytics([
"name" => "my_analytics_collection",
]);curl -X PUT -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_application/analytics/my_analytics_collection"client.searchApplication().putBehavioralAnalytics(p -> p
.name("my_analytics_collection")
);
DELETE _application/analytics/my_analytics_collection/
resp = client.search_application.delete_behavioral_analytics(
name="my_analytics_collection",
)const response = await client.searchApplication.deleteBehavioralAnalytics({
name: "my_analytics_collection",
});response = client.search_application.delete_behavioral_analytics(
name: "my_analytics_collection"
)$resp = $client->searchApplication()->deleteBehavioralAnalytics([
"name" => "my_analytics_collection",
]);curl -X DELETE -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_application/analytics/my_analytics_collection/"client.searchApplication().deleteBehavioralAnalytics(d -> d
.name("my_analytics_collection")
);
The name of the behavioral analytics collection.
The analytics event type.
Values are page_view, search, or search_click.
POST _application/analytics/my_analytics_collection/event/search_click
{
"session": {
"id": "1797ca95-91c9-4e2e-b1bd-9c38e6f386a9"
},
"user": {
"id": "5f26f01a-bbee-4202-9298-81261067abbd"
},
"search":{
"query": "search term",
"results": {
"items": [
{
"document": {
"id": "123",
"index": "products"
}
}
],
"total_results": 10
},
"sort": {
"name": "relevance"
},
"search_application": "website"
},
"document":{
"id": "123",
"index": "products"
}
}resp = client.search_application.post_behavioral_analytics_event(
collection_name="my_analytics_collection",
event_type="search_click",
payload={
"session": {
"id": "1797ca95-91c9-4e2e-b1bd-9c38e6f386a9"
},
"user": {
"id": "5f26f01a-bbee-4202-9298-81261067abbd"
},
"search": {
"query": "search term",
"results": {
"items": [
{
"document": {
"id": "123",
"index": "products"
}
}
],
"total_results": 10
},
"sort": {
"name": "relevance"
},
"search_application": "website"
},
"document": {
"id": "123",
"index": "products"
}
},
)const response = await client.searchApplication.postBehavioralAnalyticsEvent({
collection_name: "my_analytics_collection",
event_type: "search_click",
payload: {
session: {
id: "1797ca95-91c9-4e2e-b1bd-9c38e6f386a9",
},
user: {
id: "5f26f01a-bbee-4202-9298-81261067abbd",
},
search: {
query: "search term",
results: {
items: [
{
document: {
id: "123",
index: "products",
},
},
],
total_results: 10,
},
sort: {
name: "relevance",
},
search_application: "website",
},
document: {
id: "123",
index: "products",
},
},
});response = client.search_application.post_behavioral_analytics_event(
collection_name: "my_analytics_collection",
event_type: "search_click",
body: {
"session": {
"id": "1797ca95-91c9-4e2e-b1bd-9c38e6f386a9"
},
"user": {
"id": "5f26f01a-bbee-4202-9298-81261067abbd"
},
"search": {
"query": "search term",
"results": {
"items": [
{
"document": {
"id": "123",
"index": "products"
}
}
],
"total_results": 10
},
"sort": {
"name": "relevance"
},
"search_application": "website"
},
"document": {
"id": "123",
"index": "products"
}
}
)$resp = $client->searchApplication()->postBehavioralAnalyticsEvent([
"collection_name" => "my_analytics_collection",
"event_type" => "search_click",
"body" => [
"session" => [
"id" => "1797ca95-91c9-4e2e-b1bd-9c38e6f386a9",
],
"user" => [
"id" => "5f26f01a-bbee-4202-9298-81261067abbd",
],
"search" => [
"query" => "search term",
"results" => [
"items" => array(
[
"document" => [
"id" => "123",
"index" => "products",
],
],
),
"total_results" => 10,
],
"sort" => [
"name" => "relevance",
],
"search_application" => "website",
],
"document" => [
"id" => "123",
"index" => "products",
],
],
]);curl -X POST -H "Authorization: ApiKey $ELASTIC_API_KEY" -H "Content-Type: application/json" -d '{"session":{"id":"1797ca95-91c9-4e2e-b1bd-9c38e6f386a9"},"user":{"id":"5f26f01a-bbee-4202-9298-81261067abbd"},"search":{"query":"search term","results":{"items":[{"document":{"id":"123","index":"products"}}],"total_results":10},"sort":{"name":"relevance"},"search_application":"website"},"document":{"id":"123","index":"products"}}' "$ELASTICSEARCH_URL/_application/analytics/my_analytics_collection/event/search_click"client.searchApplication().postBehavioralAnalyticsEvent(p -> p
.collectionName("my_analytics_collection")
.eventType(EventType.SearchClick)
.payload(JsonData.fromJson("{\"session\":{\"id\":\"1797ca95-91c9-4e2e-b1bd-9c38e6f386a9\"},\"user\":{\"id\":\"5f26f01a-bbee-4202-9298-81261067abbd\"},\"search\":{\"query\":\"search term\",\"results\":{\"items\":[{\"document\":{\"id\":\"123\",\"index\":\"products\"}}],\"total_results\":10},\"sort\":{\"name\":\"relevance\"},\"search_application\":\"website\"},\"document\":{\"id\":\"123\",\"index\":\"products\"}}"))
);
{
"session": {
"id": "1797ca95-91c9-4e2e-b1bd-9c38e6f386a9"
},
"user": {
"id": "5f26f01a-bbee-4202-9298-81261067abbd"
},
"search":{
"query": "search term",
"results": {
"items": [
{
"document": {
"id": "123",
"index": "products"
}
}
],
"total_results": 10
},
"sort": {
"name": "relevance"
},
"search_application": "website"
},
"document":{
"id": "123",
"index": "products"
}
}The compact and aligned text (CAT) APIs aim are intended only for human consumption using the Kibana console or command line. They are not intended for use by applications. For application consumption, it's recommend to use a corresponding JSON API.
All the cat commands accept a query string parameter help to see all the headers and info they provide, and the /_cat command alone lists all the available commands.
All methods and paths for this operation:
Get the cluster's index aliases, including filter and routing information. This API does not return data stream aliases.
IMPORTANT: CAT APIs are only intended for human consumption using the command line or the Kibana console. They are not intended for use by applications. For application consumption, use the aliases API.
view_index_metadataA comma-separated list of aliases to retrieve. Supports wildcards (*). To retrieve all aliases, omit this parameter or use * or _all.
A comma-separated list of columns names to display. It supports simple wildcards.
Supported values include:
alias (or a): The name of the alias.index (or i, idx): The name of the index the alias points to.filter (or f, fi): The filter applied to the alias.routing.index (or ri, routingIndex): Index routing value for the alias.routing.search (or rs, routingSearch): Search routing value for the alias.is_write_index (or w, isWriteIndex): Indicates if the index is the write index for the alias.Values are alias, a, index, i, idx, filter, f, fi, routing.index, ri, routingIndex, routing.search, rs, routingSearch, is_write_index, w, or isWriteIndex.
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.
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.
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.
To indicated that the request should never timeout, you can set it to -1.
Values are -1 or 0.
GET _cat/aliases?format=json&v=true
resp = client.cat.aliases(
format="json",
v=True,
)const response = await client.cat.aliases({
format: "json",
v: "true",
});response = client.cat.aliases(
format: "json",
v: "true"
)$resp = $client->cat()->aliases([
"format" => "json",
"v" => "true",
]);curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_cat/aliases?format=json&v=true"client.cat().aliases();
[
{
"alias": "alias1",
"index": "test1",
"filter": "-",
"routing.index": "-",
"routing.search": "-",
"is_write_index": "true"
},
{
"alias": "alias1",
"index": "test1",
"filter": "*",
"routing.index": "-",
"routing.search": "-",
"is_write_index": "true"
},
{
"alias": "alias3",
"index": "test1",
"filter": "-",
"routing.index": "1",
"routing.search": "1",
"is_write_index": "true"
},
{
"alias": "alias4",
"index": "test1",
"filter": "-",
"routing.index": "2",
"routing.search": "1,2",
"is_write_index": "true"
}
]All methods and paths for this operation:
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.
monitorA comma-separated list of node identifiers or names used to limit the returned information.
The unit used to display byte values.
Values are b, kb, mb, gb, tb, or pb.
A comma-separated list of columns names to display. It supports simple wildcards.
Supported values include:
shards (or s): The number of shards on the node.shards.undesired: The number of shards scheduled to be moved elsewhere in the cluster.write_load.forecast (or wlf, writeLoadForecast): The sum of index write load forecasts.disk.indices.forecast (or dif, diskIndicesForecast): The sum of shard size forecasts.disk.indices (or di, diskIndices): The disk space used by Elasticsearch indices.disk.used (or du, diskUsed): The total disk space used on the node.disk.avail (or da, diskAvail): The available disk space on the node.disk.total (or dt, diskTotal): The total disk capacity of all volumes on the node.disk.percent (or dp, diskPercent): The percentage of disk space used on the node.host (or h): IThe host of the node.ip: The IP address of the node.node (or n): The name of the node.node.role (or r, role, nodeRole): The roles assigned to the node.Values are shards, s, shards.undesired, write_load.forecast, wlf, writeLoadForecast, disk.indices.forecast, dif, diskIndicesForecast, disk.indices, di, diskIndices, disk.used, du, diskUsed, disk.avail, da, diskAvail, disk.total, dt, diskTotal, disk.percent, dp, diskPercent, host, h, ip, node, n, node.role, r, role, or nodeRole.
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.
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.
GET /_cat/allocation?v=true&format=json
resp = client.cat.allocation(
v=True,
format="json",
)const response = await client.cat.allocation({
v: "true",
format: "json",
});response = client.cat.allocation(
v: "true",
format: "json"
)$resp = $client->cat()->allocation([
"v" => "true",
"format" => "json",
]);curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_cat/allocation?v=true&format=json"client.cat().allocation();
[
{
"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"
}
]All methods and paths for this operation:
Get information about component templates in a cluster. Component templates are building blocks for constructing index templates that specify index mappings, settings, and aliases.
IMPORTANT: CAT APIs are only intended for human consumption using the command line or Kibana console. They are not intended for use by applications. For application consumption, use the get component template API.
monitorThe name of the component template. It accepts wildcard expressions. If it is omitted, all component templates are returned.
A comma-separated list of columns names to display. It supports simple wildcards.
Supported values include:
name (or n): The name of the component template.version (or v): The version number of the component template.alias_count (or a): The number of aliases in the component template.mapping_count (or m): The number of mappings in the component template.settings_count (or s): The number of settings in the component template.metadata_count (or me): The number of metadata entries in the component template.included_in (or i): The index templates that include this component template.Values are name, n, version, v, alias_count, a, mapping_count, m, settings_count, s, metadata_count, me, included_in, or i.
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.
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.
The period to wait for a connection to the master node.
Values are -1 or 0.
GET _cat/component_templates/my-template-*?v=true&s=name&format=json
resp = client.cat.component_templates(
name="my-template-*",
v=True,
s="name",
format="json",
)const response = await client.cat.componentTemplates({
name: "my-template-*",
v: "true",
s: "name",
format: "json",
});response = client.cat.component_templates(
name: "my-template-*",
v: "true",
s: "name",
format: "json"
)$resp = $client->cat()->componentTemplates([
"name" => "my-template-*",
"v" => "true",
"s" => "name",
"format" => "json",
]);curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_cat/component_templates/my-template-*?v=true&s=name&format=json"client.cat().componentTemplates();
[
{
"name": "my-template-1",
"version": "null",
"alias_count": "0",
"mapping_count": "0",
"settings_count": "1",
"metadata_count": "0",
"included_in": "[my-index-template]"
},
{
"name": "my-template-2",
"version": null,
"alias_count": "0",
"mapping_count": "3",
"settings_count": "0",
"metadata_count": "0",
"included_in": "[my-index-template]"
}
]All methods and paths for this operation:
Get quick access to a document count for a data stream, an index, or an entire cluster. The document count only includes live documents, not deleted documents which have not yet been removed by the merge process.
IMPORTANT: CAT APIs are only intended for human consumption using the command line or Kibana console. They are not intended for use by applications. For application consumption, use the count API.
readA comma-separated list of data streams, indices, and aliases used to limit the request.
It supports wildcards (*).
To target all data streams and indices, omit this parameter or use * or _all.
A comma-separated list of columns names to display. It supports simple wildcards.
Supported values include:
epoch (or t, time): The Unix epoch time in seconds since 1970-01-01 00:00:00.timestamp (or ts, hms, hhmmss): The current time in HH:MM:SS format.count (or dc, docs.count, docsCount): The document count in the cluster or index.Values are epoch, t, time, timestamp, ts, hms, hhmmss, count, dc, docs.count, or docsCount.
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.
GET /_cat/count/my-index-000001?v=true&format=json
resp = client.cat.count(
index="my-index-000001",
v=True,
format="json",
)const response = await client.cat.count({
index: "my-index-000001",
v: "true",
format: "json",
});response = client.cat.count(
index: "my-index-000001",
v: "true",
format: "json"
)$resp = $client->cat()->count([
"index" => "my-index-000001",
"v" => "true",
"format" => "json",
]);curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_cat/count/my-index-000001?v=true&format=json"client.cat().count();
[
{
"epoch": "1475868259",
"timestamp": "15:24:20",
"count": "120"
}
][
{
"epoch": "1475868259",
"timestamp": "15:24:20",
"count": "121"
}
]All methods and paths for this operation:
Get the amount of heap memory currently used by the field data cache on every data node in the cluster.
IMPORTANT: cat APIs are only intended for human consumption using the command line or Kibana console. They are not intended for use by applications. For application consumption, use the nodes stats API.
monitorComma-separated list of fields used to limit returned information. To retrieve all fields, omit this parameter.
The unit used to display byte values.
Values are b, kb, mb, gb, tb, or pb.
Comma-separated list of fields used to limit returned information.
A comma-separated list of columns names to display. It supports simple wildcards.
Supported values include:
id: The node ID.host (or h): The host name of the node.ip: The IP address of the node.node (or n): The node name.field (or f): The field name.size (or s): The field data usage.Values are id, host, h, ip, node, n, field, f, size, or s.
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.
GET /_cat/fielddata?v=true&fields=body&format=json
resp = client.cat.fielddata(
v=True,
fields="body",
format="json",
)const response = await client.cat.fielddata({
v: "true",
fields: "body",
format: "json",
});response = client.cat.fielddata(
v: "true",
fields: "body",
format: "json"
)$resp = $client->cat()->fielddata([
"v" => "true",
"fields" => "body",
"format" => "json",
]);curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_cat/fielddata?v=true&fields=body&format=json"client.cat().fielddata();
[
{
"id": "Nqk-6inXQq-OxUfOUI8jNQ",
"host": "127.0.0.1",
"ip": "127.0.0.1",
"node": "Nqk-6in",
"field": "body",
"size": "544b"
}
][
{
"id": "Nqk-6inXQq-OxUfOUI8jNQ",
"host": "1127.0.0.1",
"ip": "127.0.0.1",
"node": "Nqk-6in",
"field": "body",
"size": "544b"
},
{
"id": "Nqk-6inXQq-OxUfOUI8jNQ",
"host": "127.0.0.1",
"ip": "127.0.0.1",
"node": "Nqk-6in",
"field": "soul",
"size": "480b"
}
]IMPORTANT: CAT APIs are only intended for human consumption using the command line or Kibana console.
They are not intended for use by applications. For application consumption, use the cluster health API.
This API is often used to check malfunctioning clusters.
To help you track cluster health alongside log files and alerting systems, the API returns timestamps in two formats:
HH:MM:SS, which is human-readable but includes no date information;
Unix epoch time, which is machine-sortable and includes date information.
The latter format is useful for cluster recoveries that take multiple days.
You can use the cat health API to verify cluster health across multiple nodes.
You also can use the API to track the recovery of a large cluster over a longer period of time.
monitorThe unit used to display time values.
Values are nanos, micros, ms, s, m, h, or d.
If true, returns HH:MM:SS and Unix epoch timestamps.
List of columns to appear in the response. Supports simple wildcards.
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.
GET /_cat/health?v=true&format=json
resp = client.cat.health(
v=True,
format="json",
)const response = await client.cat.health({
v: "true",
format: "json",
});response = client.cat.health(
v: "true",
format: "json"
)$resp = $client->cat()->health([
"v" => "true",
"format" => "json",
]);curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_cat/health?v=true&format=json"client.cat().health();
[
{
"epoch": "1475871424",
"timestamp": "16:17:04",
"cluster": "elasticsearch",
"status": "green",
"node.total": "1",
"node.data": "1",
"shards": "1",
"pri": "1",
"relo": "0",
"init": "0",
"unassign": "0",
"unassign.pri": "0",
"pending_tasks": "0",
"max_task_wait_time": "-",
"active_shards_percent": "100.0%"
}
]curl \
--request GET 'http://api.example.com/_cat' \
--header "Authorization: $API_KEY"All methods and paths for this operation:
Get high-level information about indices in a cluster, including backing indices for data streams.
Use this request to get the following information for each index in a cluster:
These metrics are retrieved directly from Lucene, which Elasticsearch uses internally to power indexing and search. As a result, all document counts include hidden nested documents. To get an accurate count of Elasticsearch documents, use the cat count or count APIs.
CAT APIs are only intended for human consumption using the command line or Kibana console. They are not intended for use by applications. For application consumption, use an index endpoint.
monitormonitorComma-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.
The unit used to display byte values.
Values are b, kb, mb, gb, tb, or pb.
The type of index that wildcard patterns can match.
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.
The health status used to limit returned indices. By default, the response includes indices of any health status.
Supported values include:
green (or GREEN): All shards are assigned.yellow (or YELLOW): All primary shards are assigned, but one or more replica shards are unassigned. If a node in the cluster fails, some data could be unavailable until that node is repaired.red (or RED): One or more primary shards are unassigned, so some data is unavailable. This can occur briefly during cluster startup as primary shards are assigned.unknownunavailableValues are green, GREEN, yellow, YELLOW, red, RED, unknown, or unavailable.
If true, the response includes information from segments that are not loaded into memory.
If true, the response only includes information from primary shards.
The unit used to display time values.
Values are nanos, micros, ms, s, m, h, or d.
Period to wait for a connection to the master node.
Values are -1 or 0.
List of columns to appear in the response. Supports simple wildcards.
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.
GET /_cat/indices/my-index-*?v=true&s=index&format=json
resp = client.cat.indices(
index="my-index-*",
v=True,
s="index",
format="json",
)const response = await client.cat.indices({
index: "my-index-*",
v: "true",
s: "index",
format: "json",
});response = client.cat.indices(
index: "my-index-*",
v: "true",
s: "index",
format: "json"
)$resp = $client->cat()->indices([
"index" => "my-index-*",
"v" => "true",
"s" => "index",
"format" => "json",
]);curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_cat/indices/my-index-*?v=true&s=index&format=json"client.cat().indices();
[
{
"health": "yellow",
"status": "open",
"index": "my-index-000001",
"uuid": "u8FNjxh8Rfy_awN11oDKYQ",
"pri": "1",
"rep": "1",
"docs.count": "1200",
"docs.deleted": "0",
"store.size": "88.1kb",
"pri.store.size": "88.1kb",
"dataset.size": "88.1kb"
},
{
"health": "green",
"status": "open",
"index": "my-index-000002",
"uuid": "nYFWZEO7TUiOjLQXBaYJpA ",
"pri": "1",
"rep": "0",
"docs.count": "0",
"docs.deleted": "0",
"store.size": "260b",
"pri.store.size": "260b",
"dataset.size": "260b"
}
]Get information about the master node, including the ID, bound IP address, and name.
IMPORTANT: cat APIs are only intended for human consumption using the command line or Kibana console. They are not intended for use by applications. For application consumption, use the nodes info API.
monitorList of columns to appear in the response. Supports simple wildcards.
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.
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.
GET /_cat/master?v=true&format=json
resp = client.cat.master(
v=True,
format="json",
)const response = await client.cat.master({
v: "true",
format: "json",
});response = client.cat.master(
v: "true",
format: "json"
)$resp = $client->cat()->master([
"v" => "true",
"format" => "json",
]);curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_cat/master?v=true&format=json"client.cat().master();
[
{
"id": "YzWoH_2BT-6UjVGDyPdqYg",
"host": "127.0.0.1",
"ip": "127.0.0.1",
"node": "YzWoH_2"
}
]All methods and paths for this operation:
Get configuration and usage information about data frame analytics jobs.
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 data frame analytics jobs statistics API.
monitor_mlWhether to ignore if a wildcard expression matches no configs. (This includes _all string or when no configs have been specified)
The unit in which to display byte values
Values are b, kb, mb, gb, tb, or pb.
Comma-separated list of column names to display.
Supported values include:
assignment_explanation (or ae): Contains messages relating to the selection of a node.create_time (or ct, createTime): The time when the data frame analytics job was created.description (or d): A description of a job.dest_index (or di, destIndex): Name of the destination index.failure_reason (or fr, failureReason): Contains messages about the reason why a data frame analytics job failed.id: Identifier for the data frame analytics job.model_memory_limit (or mml, modelMemoryLimit): The approximate maximum amount of memory resources that are permitted for
the data frame analytics job.node.address (or na, nodeAddress): The network address of the node that the data frame analytics job is
assigned to.node.ephemeral_id (or ne, nodeEphemeralId): The ephemeral ID of the node that the data frame analytics job is assigned
to.node.id (or ni, nodeId): The unique identifier of the node that the data frame analytics job is
assigned to.node.name (or nn, nodeName): The name of the node that the data frame analytics job is assigned to.progress (or p): The progress report of the data frame analytics job by phase.source_index (or si, sourceIndex): Name of the source index.state (or s): Current state of the data frame analytics job.type (or t): The type of analysis that the data frame analytics job performs.version (or v): The Elasticsearch version number in which the data frame analytics job was
created.Comma-separated list of column names or column aliases used to sort the response.
Supported values include:
assignment_explanation (or ae): Contains messages relating to the selection of a node.create_time (or ct, createTime): The time when the data frame analytics job was created.description (or d): A description of a job.dest_index (or di, destIndex): Name of the destination index.failure_reason (or fr, failureReason): Contains messages about the reason why a data frame analytics job failed.id: Identifier for the data frame analytics job.model_memory_limit (or mml, modelMemoryLimit): The approximate maximum amount of memory resources that are permitted for
the data frame analytics job.node.address (or na, nodeAddress): The network address of the node that the data frame analytics job is
assigned to.node.ephemeral_id (or ne, nodeEphemeralId): The ephemeral ID of the node that the data frame analytics job is assigned
to.node.id (or ni, nodeId): The unique identifier of the node that the data frame analytics job is
assigned to.node.name (or nn, nodeName): The name of the node that the data frame analytics job is assigned to.progress (or p): The progress report of the data frame analytics job by phase.source_index (or si, sourceIndex): Name of the source index.state (or s): Current state of the data frame analytics job.type (or t): The type of analysis that the data frame analytics job performs.version (or v): The Elasticsearch version number in which the data frame analytics job was
created.Unit used to display time values.
Values are nanos, micros, ms, s, m, h, or d.
GET _cat/ml/data_frame/analytics?v=true&format=json
resp = client.cat.ml_data_frame_analytics(
v=True,
format="json",
)const response = await client.cat.mlDataFrameAnalytics({
v: "true",
format: "json",
});response = client.cat.ml_data_frame_analytics(
v: "true",
format: "json"
)$resp = $client->cat()->mlDataFrameAnalytics([
"v" => "true",
"format" => "json",
]);curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_cat/ml/data_frame/analytics?v=true&format=json"client.cat().mlDataFrameAnalytics();
[
{
"id": "classifier_job_1",
"type": "classification",
"create_time": "2020-02-12T11:49:09.594Z",
"state": "stopped"
},
{
"id": "classifier_job_2",
"type": "classification",
"create_time": "2020-02-12T11:49:14.479Z",
"state": "stopped"
},
{
"id": "classifier_job_3",
"type": "classification",
"create_time": "2020-02-12T11:49:16.928Z",
"state": "stopped"
},
{
"id": "classifier_job_4",
"type": "classification",
"create_time": "2020-02-12T11:49:19.127Z",
"state": "stopped"
},
{
"id": "classifier_job_5",
"type": "classification",
"create_time": "2020-02-12T11:49:21.349Z",
"state": "stopped"
}
]All methods and paths for this operation:
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.
monitor_mlSpecifies what to do when the request:
_all string or no identifiers and there are no 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.
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.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.The unit used to display time values.
Values are nanos, micros, ms, s, m, h, or d.
GET _cat/ml/datafeeds?v=true&format=json
resp = client.cat.ml_datafeeds(
v=True,
format="json",
)const response = await client.cat.mlDatafeeds({
v: "true",
format: "json",
});response = client.cat.ml_datafeeds(
v: "true",
format: "json"
)$resp = $client->cat()->mlDatafeeds([
"v" => "true",
"format" => "json",
]);curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_cat/ml/datafeeds?v=true&format=json"client.cat().mlDatafeeds();
[
{
"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"
}
]All methods and paths for this operation:
Get configuration and usage information for anomaly detection jobs.
This API returns a maximum of 10,000 jobs.
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 anomaly detection job statistics API.
monitor_mlSpecifies what to do when the request:
_all string or no identifiers and there are no matches.If true, the API returns an empty jobs 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.
The unit used to display byte values.
Values are b, kb, mb, gb, tb, or pb.
Comma-separated list of column names to display.
Supported values include:
assignment_explanation (or ae): For open anomaly detection jobs only, contains messages relating to the
selection of a node to run the job.buckets.count (or bc, bucketsCount): The number of bucket results produced by the job.buckets.time.exp_avg (or btea, bucketsTimeExpAvg): Exponential moving average of all bucket processing times, in milliseconds.buckets.time.exp_avg_hour (or bteah, bucketsTimeExpAvgHour): Exponentially-weighted moving average of bucket processing times calculated
in a 1 hour time window, in milliseconds.buckets.time.max (or btmax, bucketsTimeMax): Maximum among all bucket processing times, in milliseconds.buckets.time.min (or btmin, bucketsTimeMin): Minimum among all bucket processing times, in milliseconds.buckets.time.total (or btt, bucketsTimeTotal): Sum of all bucket processing times, in milliseconds.data.buckets (or db, dataBuckets): The number of buckets processed.data.earliest_record (or der, dataEarliestRecord): The timestamp of the earliest chronologically input document.data.empty_buckets (or deb, dataEmptyBuckets): The number of buckets which did not contain any data.data.input_bytes (or dib, dataInputBytes): The number of bytes of input data posted to the anomaly detection job.data.input_fields (or dif, dataInputFields): The total number of fields in input documents posted to the anomaly
detection job. This count includes fields that are not used in the analysis.
However, be aware that if you are using a datafeed, it extracts only the
required fields from the documents it retrieves before posting them to the job.data.input_records (or dir, dataInputRecords): The number of input documents posted to the anomaly detection job.data.invalid_dates (or did, dataInvalidDates): The number of input documents with either a missing date field or a date
that could not be parsed.data.last (or dl, dataLast): The timestamp at which data was last analyzed, according to server time.data.last_empty_bucket (or dleb, dataLastEmptyBucket): The timestamp of the last bucket that did not contain any data.data.last_sparse_bucket (or dlsb, dataLastSparseBucket): The timestamp of the last bucket that was considered sparse.data.latest_record (or dlr, dataLatestRecord): The timestamp of the latest chronologically input document.data.missing_fields (or dmf, dataMissingFields): The number of input documents that are missing a field that the anomaly
detection job is configured to analyze. Input documents with missing fields
are still processed because it is possible that not all fields are missing.data.out_of_order_timestamps (or doot, dataOutOfOrderTimestamps): The number of input documents that have a timestamp chronologically
preceding the start of the current anomaly detection bucket offset by the
latency window. This information is applicable only when you provide data
to the anomaly detection job by using the post data API. These out of order
documents are discarded, since jobs require time series data to be in
ascending chronological order.data.processed_fields (or dpf, dataProcessedFields): The total number of fields in all the documents that have been processed by
the anomaly detection job. Only fields that are specified in the detector
configuration object contribute to this count. The timestamp is not
included in this count.data.processed_records (or dpr, dataProcessedRecords): The number of input documents that have been processed by the anomaly
detection job. This value includes documents with missing fields, since
they are nonetheless analyzed. If you use datafeeds and have aggregations
in your search query, the processed record count is the number of
aggregation results processed, not the number of Elasticsearch documents.data.sparse_buckets (or dsb, dataSparseBuckets): The number of buckets that contained few data points compared to the
expected number of data points.forecasts.memory.avg (or fmavg, forecastsMemoryAvg): The average memory usage in bytes for forecasts related to the anomaly
detection job.forecasts.memory.max (or fmmax, forecastsMemoryMax): The maximum memory usage in bytes for forecasts related to the anomaly
detection job.forecasts.memory.min (or fmmin, forecastsMemoryMin): The minimum memory usage in bytes for forecasts related to the anomaly
detection job.forecasts.memory.total (or fmt, forecastsMemoryTotal): The total memory usage in bytes for forecasts related to the anomaly
detection job.forecasts.records.avg (or fravg, forecastsRecordsAvg): The average number of model_forecast` documents written for forecasts
related to the anomaly detection job.forecasts.records.max (or frmax, forecastsRecordsMax): The maximum number of model_forecast documents written for forecasts
related to the anomaly detection job.forecasts.records.min (or frmin, forecastsRecordsMin): The minimum number of model_forecast documents written for forecasts
related to the anomaly detection job.forecasts.records.total (or frt, forecastsRecordsTotal): The total number of model_forecast documents written for forecasts
related to the anomaly detection job.forecasts.time.avg (or ftavg, forecastsTimeAvg): The average runtime in milliseconds for forecasts related to the anomaly
detection job.forecasts.time.max (or ftmax, forecastsTimeMax): The maximum runtime in milliseconds for forecasts related to the anomaly
detection job.forecasts.time.min (or ftmin, forecastsTimeMin): The minimum runtime in milliseconds for forecasts related to the anomaly
detection job.forecasts.time.total (or ftt, forecastsTimeTotal): The total runtime in milliseconds for forecasts related to the anomaly
detection job.forecasts.total (or ft, forecastsTotal): The number of individual forecasts currently available for the job.id: Identifier for the anomaly detection job.model.bucket_allocation_failures (or mbaf, modelBucketAllocationFailures): The number of buckets for which new entities in incoming data were not
processed due to insufficient model memory.model.by_fields (or mbf, modelByFields): The number of by field values that were analyzed by the models. This value
is cumulative for all detectors in the job.model.bytes (or mb, modelBytes): The number of bytes of memory used by the models. This is the maximum value
since the last time the model was persisted. If the job is closed, this
value indicates the latest size.model.bytes_exceeded (or mbe, modelBytesExceeded): The number of bytes over the high limit for memory usage at the last
allocation failure.model.categorization_status (or mcs, modelCategorizationStatus): The status of categorization for the job: ok or warn. If ok,
categorization is performing acceptably well (or not being used at all). If
warn, categorization is detecting a distribution of categories that
suggests the input data is inappropriate for categorization. Problems could
be that there is only one category, more than 90% of categories are rare,
the number of categories is greater than 50% of the number of categorized
documents, there are no frequently matched categories, or more than 50% of
categories are dead.model.categorized_doc_count (or mcdc, modelCategorizedDocCount): The number of documents that have had a field categorized.model.dead_category_count (or mdcc, modelDeadCategoryCount): The number of categories created by categorization that will never be
assigned again because another category’s definition makes it a superset of
the dead category. Dead categories are a side effect of the way
categorization has no prior training.model.failed_category_count (or mdcc, modelFailedCategoryCount): The number of times that categorization wanted to create a new category but
couldn’t because the job had hit its model memory limit. This count does
not track which specific categories failed to be created. Therefore, you
cannot use this value to determine the number of unique categories that
were missed.model.frequent_category_count (or mfcc, modelFrequentCategoryCount): The number of categories that match more than 1% of categorized documents.model.log_time (or mlt, modelLogTime): The timestamp when the model stats were gathered, according to server time.model.memory_limit (or mml, modelMemoryLimit): The timestamp when the model stats were gathered, according to server time.model.memory_status (or mms, modelMemoryStatus): The status of the mathematical models: ok, soft_limit, or hard_limit.
If ok, the models stayed below the configured value. If soft_limit, the
models used more than 60% of the configured memory limit and older unused
models will be pruned to free up space. Additionally, in categorization jobs
no further category examples will be stored. If hard_limit, the models
used more space than the configured memory limit. As a result, not all
incoming data was processed.model.over_fields (or mof, modelOverFields): The number of over field values that were analyzed by the models. This
value is cumulative for all detectors in the job.model.partition_fields (or mpf, modelPartitionFields): The number of partition field values that were analyzed by the models. This
value is cumulative for all detectors in the job.model.rare_category_count (or mrcc, modelRareCategoryCount): The number of categories that match just one categorized document.model.timestamp (or mt, modelTimestamp): The timestamp of the last record when the model stats were gathered.model.total_category_count (or mtcc, modelTotalCategoryCount): The number of categories created by categorization.node.address (or na, nodeAddress): The network address of the node that runs the job. This information is
available only for open jobs.node.ephemeral_id (or ne, nodeEphemeralId): The ephemeral ID of the node that runs the job. This information is
available only for open jobs.node.id (or ni, nodeId): The unique identifier of the node that runs the job. This information is
available only for open jobs.node.name (or nn, nodeName): The name of the node that runs the job. This information is available only
for open jobs.opened_time (or ot): For open jobs only, the elapsed time for which the job has been open.state (or s): The status of the anomaly detection job: closed, closing, failed,
opened, or opening. If closed, the job finished successfully with its
model state persisted. The job must be opened before it can accept further
data. If closing, the job close action is in progress and has not yet
completed. A closing job cannot accept further data. If failed, the job
did not finish successfully due to an error. This situation can occur due
to invalid input data, a fatal error occurring during the analysis, or an
external interaction such as the process being killed by the Linux out of
memory (OOM) killer. If the job had irrevocably failed, it must be force
closed and then deleted. If the datafeed can be corrected, the job can be
closed and then re-opened. If opened, the job is available to receive and
process data. If opening, the job open action is in progress and has not
yet completed.Comma-separated list of column names or column aliases used to sort the response.
Supported values include:
assignment_explanation (or ae): For open anomaly detection jobs only, contains messages relating to the
selection of a node to run the job.buckets.count (or bc, bucketsCount): The number of bucket results produced by the job.buckets.time.exp_avg (or btea, bucketsTimeExpAvg): Exponential moving average of all bucket processing times, in milliseconds.buckets.time.exp_avg_hour (or bteah, bucketsTimeExpAvgHour): Exponentially-weighted moving average of bucket processing times calculated
in a 1 hour time window, in milliseconds.buckets.time.max (or btmax, bucketsTimeMax): Maximum among all bucket processing times, in milliseconds.buckets.time.min (or btmin, bucketsTimeMin): Minimum among all bucket processing times, in milliseconds.buckets.time.total (or btt, bucketsTimeTotal): Sum of all bucket processing times, in milliseconds.data.buckets (or db, dataBuckets): The number of buckets processed.data.earliest_record (or der, dataEarliestRecord): The timestamp of the earliest chronologically input document.data.empty_buckets (or deb, dataEmptyBuckets): The number of buckets which did not contain any data.data.input_bytes (or dib, dataInputBytes): The number of bytes of input data posted to the anomaly detection job.data.input_fields (or dif, dataInputFields): The total number of fields in input documents posted to the anomaly
detection job. This count includes fields that are not used in the analysis.
However, be aware that if you are using a datafeed, it extracts only the
required fields from the documents it retrieves before posting them to the job.data.input_records (or dir, dataInputRecords): The number of input documents posted to the anomaly detection job.data.invalid_dates (or did, dataInvalidDates): The number of input documents with either a missing date field or a date
that could not be parsed.data.last (or dl, dataLast): The timestamp at which data was last analyzed, according to server time.data.last_empty_bucket (or dleb, dataLastEmptyBucket): The timestamp of the last bucket that did not contain any data.data.last_sparse_bucket (or dlsb, dataLastSparseBucket): The timestamp of the last bucket that was considered sparse.data.latest_record (or dlr, dataLatestRecord): The timestamp of the latest chronologically input document.data.missing_fields (or dmf, dataMissingFields): The number of input documents that are missing a field that the anomaly
detection job is configured to analyze. Input documents with missing fields
are still processed because it is possible that not all fields are missing.data.out_of_order_timestamps (or doot, dataOutOfOrderTimestamps): The number of input documents that have a timestamp chronologically
preceding the start of the current anomaly detection bucket offset by the
latency window. This information is applicable only when you provide data
to the anomaly detection job by using the post data API. These out of order
documents are discarded, since jobs require time series data to be in
ascending chronological order.data.processed_fields (or dpf, dataProcessedFields): The total number of fields in all the documents that have been processed by
the anomaly detection job. Only fields that are specified in the detector
configuration object contribute to this count. The timestamp is not
included in this count.data.processed_records (or dpr, dataProcessedRecords): The number of input documents that have been processed by the anomaly
detection job. This value includes documents with missing fields, since
they are nonetheless analyzed. If you use datafeeds and have aggregations
in your search query, the processed record count is the number of
aggregation results processed, not the number of Elasticsearch documents.data.sparse_buckets (or dsb, dataSparseBuckets): The number of buckets that contained few data points compared to the
expected number of data points.forecasts.memory.avg (or fmavg, forecastsMemoryAvg): The average memory usage in bytes for forecasts related to the anomaly
detection job.forecasts.memory.max (or fmmax, forecastsMemoryMax): The maximum memory usage in bytes for forecasts related to the anomaly
detection job.forecasts.memory.min (or fmmin, forecastsMemoryMin): The minimum memory usage in bytes for forecasts related to the anomaly
detection job.forecasts.memory.total (or fmt, forecastsMemoryTotal): The total memory usage in bytes for forecasts related to the anomaly
detection job.forecasts.records.avg (or fravg, forecastsRecordsAvg): The average number of model_forecast` documents written for forecasts
related to the anomaly detection job.forecasts.records.max (or frmax, forecastsRecordsMax): The maximum number of model_forecast documents written for forecasts
related to the anomaly detection job.forecasts.records.min (or frmin, forecastsRecordsMin): The minimum number of model_forecast documents written for forecasts
related to the anomaly detection job.forecasts.records.total (or frt, forecastsRecordsTotal): The total number of model_forecast documents written for forecasts
related to the anomaly detection job.forecasts.time.avg (or ftavg, forecastsTimeAvg): The average runtime in milliseconds for forecasts related to the anomaly
detection job.forecasts.time.max (or ftmax, forecastsTimeMax): The maximum runtime in milliseconds for forecasts related to the anomaly
detection job.forecasts.time.min (or ftmin, forecastsTimeMin): The minimum runtime in milliseconds for forecasts related to the anomaly
detection job.forecasts.time.total (or ftt, forecastsTimeTotal): The total runtime in milliseconds for forecasts related to the anomaly
detection job.forecasts.total (or ft, forecastsTotal): The number of individual forecasts currently available for the job.id: Identifier for the anomaly detection job.model.bucket_allocation_failures (or mbaf, modelBucketAllocationFailures): The number of buckets for which new entities in incoming data were not
processed due to insufficient model memory.model.by_fields (or mbf, modelByFields): The number of by field values that were analyzed by the models. This value
is cumulative for all detectors in the job.model.bytes (or mb, modelBytes): The number of bytes of memory used by the models. This is the maximum value
since the last time the model was persisted. If the job is closed, this
value indicates the latest size.model.bytes_exceeded (or mbe, modelBytesExceeded): The number of bytes over the high limit for memory usage at the last
allocation failure.model.categorization_status (or mcs, modelCategorizationStatus): The status of categorization for the job: ok or warn. If ok,
categorization is performing acceptably well (or not being used at all). If
warn, categorization is detecting a distribution of categories that
suggests the input data is inappropriate for categorization. Problems could
be that there is only one category, more than 90% of categories are rare,
the number of categories is greater than 50% of the number of categorized
documents, there are no frequently matched categories, or more than 50% of
categories are dead.model.categorized_doc_count (or mcdc, modelCategorizedDocCount): The number of documents that have had a field categorized.model.dead_category_count (or mdcc, modelDeadCategoryCount): The number of categories created by categorization that will never be
assigned again because another category’s definition makes it a superset of
the dead category. Dead categories are a side effect of the way
categorization has no prior training.model.failed_category_count (or mdcc, modelFailedCategoryCount): The number of times that categorization wanted to create a new category but
couldn’t because the job had hit its model memory limit. This count does
not track which specific categories failed to be created. Therefore, you
cannot use this value to determine the number of unique categories that
were missed.model.frequent_category_count (or mfcc, modelFrequentCategoryCount): The number of categories that match more than 1% of categorized documents.model.log_time (or mlt, modelLogTime): The timestamp when the model stats were gathered, according to server time.model.memory_limit (or mml, modelMemoryLimit): The timestamp when the model stats were gathered, according to server time.model.memory_status (or mms, modelMemoryStatus): The status of the mathematical models: ok, soft_limit, or hard_limit.
If ok, the models stayed below the configured value. If soft_limit, the
models used more than 60% of the configured memory limit and older unused
models will be pruned to free up space. Additionally, in categorization jobs
no further category examples will be stored. If hard_limit, the models
used more space than the configured memory limit. As a result, not all
incoming data was processed.model.over_fields (or mof, modelOverFields): The number of over field values that were analyzed by the models. This
value is cumulative for all detectors in the job.model.partition_fields (or mpf, modelPartitionFields): The number of partition field values that were analyzed by the models. This
value is cumulative for all detectors in the job.model.rare_category_count (or mrcc, modelRareCategoryCount): The number of categories that match just one categorized document.model.timestamp (or mt, modelTimestamp): The timestamp of the last record when the model stats were gathered.model.total_category_count (or mtcc, modelTotalCategoryCount): The number of categories created by categorization.node.address (or na, nodeAddress): The network address of the node that runs the job. This information is
available only for open jobs.node.ephemeral_id (or ne, nodeEphemeralId): The ephemeral ID of the node that runs the job. This information is
available only for open jobs.node.id (or ni, nodeId): The unique identifier of the node that runs the job. This information is
available only for open jobs.node.name (or nn, nodeName): The name of the node that runs the job. This information is available only
for open jobs.opened_time (or ot): For open jobs only, the elapsed time for which the job has been open.state (or s): The status of the anomaly detection job: closed, closing, failed,
opened, or opening. If closed, the job finished successfully with its
model state persisted. The job must be opened before it can accept further
data. If closing, the job close action is in progress and has not yet
completed. A closing job cannot accept further data. If failed, the job
did not finish successfully due to an error. This situation can occur due
to invalid input data, a fatal error occurring during the analysis, or an
external interaction such as the process being killed by the Linux out of
memory (OOM) killer. If the job had irrevocably failed, it must be force
closed and then deleted. If the datafeed can be corrected, the job can be
closed and then re-opened. If opened, the job is available to receive and
process data. If opening, the job open action is in progress and has not
yet completed.The unit used to display time values.
Values are nanos, micros, ms, s, m, h, or d.
GET _cat/ml/anomaly_detectors?h=id,s,dpr,mb&v=true&format=json
resp = client.cat.ml_jobs(
h="id,s,dpr,mb",
v=True,
format="json",
)const response = await client.cat.mlJobs({
h: "id,s,dpr,mb",
v: "true",
format: "json",
});response = client.cat.ml_jobs(
h: "id,s,dpr,mb",
v: "true",
format: "json"
)$resp = $client->cat()->mlJobs([
"h" => "id,s,dpr,mb",
"v" => "true",
"format" => "json",
]);curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_cat/ml/anomaly_detectors?h=id,s,dpr,mb&v=true&format=json"client.cat().mlJobs();
[
{
"id": "high_sum_total_sales",
"s": "closed",
"dpr": "14022",
"mb": "1.5mb"
},
{
"id": "low_request_rate",
"s": "closed",
"dpr": "1216",
"mb": "40.5kb"
},
{
"id": "response_code_rates",
"s": "closed",
"dpr": "28146",
"mb": "132.7kb"
},
{
"id": "url_scanning",
"s": "closed",
"dpr": "28146",
"mb": "501.6kb"
}
]All methods and paths for this operation:
Get configuration and usage information about inference trained models.
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 trained models statistics API.
monitor_mlSpecifies what to do when the request: contains wildcard expressions and there are no models 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 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.
The unit used to display byte values.
Values are b, kb, mb, gb, tb, or pb.
A comma-separated list of column names to display.
Supported values include:
create_time (or ct): The time when the trained model was created.created_by (or c, createdBy): Information on the creator of the trained model.data_frame_analytics_id (or df, dataFrameAnalytics, dfid): Identifier for the data frame analytics job that created the model. Only
displayed if it is still available.description (or d): The description of the trained model.heap_size (or hs, modelHeapSize): The estimated heap size to keep the trained model in memory.id: Identifier for the trained model.ingest.count (or ic, ingestCount): The total number of documents that are processed by the model.ingest.current (or icurr, ingestCurrent): The total number of document that are currently being handled by the
trained model.ingest.failed (or if, ingestFailed): The total number of failed ingest attempts with the trained model.ingest.pipelines (or ip, ingestPipelines): The total number of ingest pipelines that are referencing the trained
model.ingest.time (or it, ingestTime): The total time that is spent processing documents with the trained model.license (or l): The license level of the trained model.operations (or o, modelOperations): The estimated number of operations to use the trained model. This number
helps measuring the computational complexity of the model.version (or v): The Elasticsearch version number in which the trained model was created.A comma-separated list of column names or aliases used to sort the response.
Supported values include:
create_time (or ct): The time when the trained model was created.created_by (or c, createdBy): Information on the creator of the trained model.data_frame_analytics_id (or df, dataFrameAnalytics, dfid): Identifier for the data frame analytics job that created the model. Only
displayed if it is still available.description (or d): The description of the trained model.heap_size (or hs, modelHeapSize): The estimated heap size to keep the trained model in memory.id: Identifier for the trained model.ingest.count (or ic, ingestCount): The total number of documents that are processed by the model.ingest.current (or icurr, ingestCurrent): The total number of document that are currently being handled by the
trained model.ingest.failed (or if, ingestFailed): The total number of failed ingest attempts with the trained model.ingest.pipelines (or ip, ingestPipelines): The total number of ingest pipelines that are referencing the trained
model.ingest.time (or it, ingestTime): The total time that is spent processing documents with the trained model.license (or l): The license level of the trained model.operations (or o, modelOperations): The estimated number of operations to use the trained model. This number
helps measuring the computational complexity of the model.version (or v): The Elasticsearch version number in which the trained model was created.Skips the specified number of transforms.
The maximum number of transforms to display.
Unit used to display time values.
Values are nanos, micros, ms, s, m, h, or d.
GET _cat/ml/trained_models?v=true&format=json
resp = client.cat.ml_trained_models(
v=True,
format="json",
)const response = await client.cat.mlTrainedModels({
v: "true",
format: "json",
});response = client.cat.ml_trained_models(
v: "true",
format: "json"
)$resp = $client->cat()->mlTrainedModels([
"v" => "true",
"format" => "json",
]);curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_cat/ml/trained_models?v=true&format=json"client.cat().mlTrainedModels();
[
{
"id": "ddddd-1580216177138",
"heap_size": "0b",
"operations": "196",
"create_time": "2025-03-25T00:01:38.662Z",
"type": "pytorch",
"ingest.pipelines": "0",
"data_frame.id": "__none__"
},
{
"id": "lang_ident_model_1",
"heap_size": "1mb",
"operations": "39629",
"create_time": "2019-12-05T12:28:34.594Z",
"type": "lang_ident",
"ingest.pipelines": "0",
"data_frame.id": "__none__"
}
]List of columns to appear in the response. Supports simple wildcards.
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.
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.
GET /_cat/nodeattrs?v=true&format=json
resp = client.cat.nodeattrs(
v=True,
format="json",
)const response = await client.cat.nodeattrs({
v: "true",
format: "json",
});response = client.cat.nodeattrs(
v: "true",
format: "json"
)$resp = $client->cat()->nodeattrs([
"v" => "true",
"format" => "json",
]);curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_cat/nodeattrs?v=true&format=json"client.cat().nodeattrs();
[
{
"node": "node-0",
"host": "127.0.0.1",
"ip": "127.0.0.1",
"attr": "testattr",
"value": "test"
}
][
{
"name": "node-0",
"pid": "19566",
"attr": "testattr",
"value": "test"
}
]The unit used to display byte values.
Values are b, kb, mb, gb, tb, or pb.
If true, return the full node ID. If false, return the shortened node ID.
If true, the response includes information from segments that are not loaded into memory.
A comma-separated list of columns names to display. It supports simple wildcards.
Supported values include:
build (or b): The Elasticsearch build hash. For example: 5c03844.completion.size (or cs, completionSize): The size of completion. For example: 0b.cpu: The percentage of recent system CPU used.disk.avail (or d, disk, diskAvail): The available disk space. For example: 198.4gb.disk.total (or dt, diskTotal): The total disk space. For example: 458.3gb.disk.used (or du, diskUsed): The used disk space. For example: 259.8gb.disk.used_percent (or dup, diskUsedPercent): The percentage of disk space used.fielddata.evictions (or fe, fielddataEvictions): The number of fielddata cache evictions.fielddata.memory_size (or fm, fielddataMemory): The fielddata cache memory used. For example: 0b.file_desc.current (or fdc, fileDescriptorCurrent): The number of file descriptors used.file_desc.max (or fdm, fileDescriptorMax): The maximum number of file descriptors.file_desc.percent (or fdp, fileDescriptorPercent): The percentage of file descriptors used.flush.total (or ft, flushTotal): The number of flushes.flush.total_time (or ftt, flushTotalTime): The amount of time spent in flush.get.current (or gc, getCurrent): The number of current get operations.get.exists_time (or geti, getExistsTime): The time spent in successful get operations. For example: 14ms.get.exists_total (or geto, getExistsTotal): The number of successful get operations.get.missing_time (or gmti, getMissingTime): The time spent in failed get operations. For example: 0s.get.missing_total (or gmto, getMissingTotal): The number of failed get operations.get.time (or gti, getTime): The amount of time spent in get operations. For example: 14ms.get.total (or gto, getTotal): The number of get operations.heap.current (or hc, heapCurrent): The used heap size. For example: 311.2mb.heap.max (or hm, heapMax): The total heap size. For example: 4gb.heap.percent (or hp, heapPercent): The used percentage of total allocated Elasticsearch JVM heap.
This value reflects only the Elasticsearch process running within the operating system and is the most direct indicator of its JVM, heap, or memory resource performance.http_address (or http): The bound HTTP address.id (or nodeId): The identifier for the node.indexing.delete_current (or idc, indexingDeleteCurrent): The number of current deletion operations.indexing.delete_time (or idti, indexingDeleteTime): The time spent in deletion operations. For example: 2ms.indexing.delete_total (or idto, indexingDeleteTotal): The number of deletion operations.indexing.index_current (or iic, indexingIndexCurrent): The number of current indexing operations.indexing.index_failed (or iif, indexingIndexFailed): The number of failed indexing operations.indexing.index_failed_due_to_version_conflict (or iifvc, indexingIndexFailedDueToVersionConflict): The number of indexing operations that failed due to version conflict.indexing.index_time (or iiti, indexingIndexTime): The time spent in indexing operations. For example: 134ms.indexing.index_total (or iito, indexingIndexTotal): The number of indexing operations.ip (or i): The IP address.jdk (or j): The Java version. For example: 1.8.0.load_1m (or l): The most recent load average. For example: 0.22.load_5m (or l): The load average for the last five minutes. For example: 0.78.load_15m (or l): The load average for the last fifteen minutes. For example: 1.24.mappings.total_count (or mtc, mappingsTotalCount): The number of mappings, including runtime and object fields.mappings.total_estimated_overhead_in_bytes (or mteo, mappingsTotalEstimatedOverheadInBytes): The estimated heap overhead, in bytes, of mappings on this node, which allows for 1KiB of heap for every mapped field.master (or m): Indicates whether the node is the elected master node.
Returned values include * (elected master) and - (not elected master).merges.current (or mc, mergesCurrent): The number of current merge operations.merges.current_docs (or mcd, mergesCurrentDocs): The number of current merging documents.merges.current_size (or mcs, mergesCurrentSize): The size of current merges. For example: 0b.merges.total (or mt, mergesTotal): The number of completed merge operations.merges.total_docs (or mtd, mergesTotalDocs): The number of merged documents.merges.total_size (or mts, mergesTotalSize): The total size of merges. For example: 0b.merges.total_time (or mtt, mergesTotalTime): The time spent merging documents. For example: 0s.name (or n): The node name.node.role (or r, role, nodeRole): The roles of the node.
Returned values include c (cold node), d (data node), f (frozen node), h (hot node), i (ingest node), l (machine learning node), m (master-eligible node), r (remote cluster client node), s (content node), t (transform node), v (voting-only node), w (warm node), and - (coordinating node only).
For example, dim indicates a master-eligible data and ingest node.pid (or p): The process identifier.port (or po): The bound transport port number.query_cache.memory_size (or qcm, queryCacheMemory): The used query cache memory. For example: 0b.query_cache.evictions (or qce, queryCacheEvictions): The number of query cache evictions.query_cache.hit_count (or qchc, queryCacheHitCount): The query cache hit count.query_cache.miss_count (or qcmc, queryCacheMissCount): The query cache miss count.ram.current (or rc, ramCurrent): The used total memory. For example: 513.4mb.ram.max (or rm, ramMax): The total memory. For example: 2.9gb.ram.percent (or rp, ramPercent): The used percentage of the total operating system memory.
This reflects all processes running on the operating system instead of only Elasticsearch and is not guaranteed to correlate to its performance.refresh.total (or rto, refreshTotal): The number of refresh operations.refresh.time (or rti, refreshTime): The time spent in refresh operations. For example: 91ms.request_cache.memory_size (or rcm, requestCacheMemory): The used request cache memory. For example: 0b.request_cache.evictions (or rce, requestCacheEvictions): The number of request cache evictions.request_cache.hit_count (or rchc, requestCacheHitCount): The request cache hit count.request_cache.miss_count (or rcmc, requestCacheMissCount): The request cache miss count.script.compilations (or scrcc, scriptCompilations): The number of total script compilations.script.cache_evictions (or scrce, scriptCacheEvictions): The number of total compiled scripts evicted from cache.search.fetch_current (or sfc, searchFetchCurrent): The number of current fetch phase operations.search.fetch_time (or sfti, searchFetchTime): The time spent in fetch phase. For example: 37ms.search.fetch_total (or sfto, searchFetchTotal): The number of fetch operations.search.open_contexts (or so, searchOpenContexts): The number of open search contexts.search.query_current (or sqc, searchQueryCurrent): The number of current query phase operations.search.query_time (or sqti, searchQueryTime): The time spent in query phase. For example: 43ms.search.query_total (or sqto, searchQueryTotal): The number of query operations.search.scroll_current (or scc, searchScrollCurrent): The number of open scroll contexts.search.scroll_time (or scti, searchScrollTime): The amount of time scroll contexts were held open. For example: 2m.search.scroll_total (or scto, searchScrollTotal): The number of completed scroll contexts.segments.count (or sc, segmentsCount): The number of segments.segments.fixed_bitset_memory (or sfbm, fixedBitsetMemory): The memory used by fixed bit sets for nested object field types and type filters for types referred in join fields.
For example: 1.0kb.segments.index_writer_memory (or siwm, segmentsIndexWriterMemory): The memory used by the index writer. For example: 18mb.segments.memory (or sm, segmentsMemory): The memory used by segments. For example: 1.4kb.segments.version_map_memory (or svmm, segmentsVersionMapMemory): The memory used by the version map. For example: 1.0kb.shard_stats.total_count (or sstc, shards, shardStatsTotalCount): The number of shards assigned.suggest.current (or suc, suggestCurrent): The number of current suggest operations.suggest.time (or suti, suggestTime): The time spent in suggest operations.suggest.total (or suto, suggestTotal): The number of suggest operations.uptime (or u): The amount of node uptime. For example: 17.3m.version (or v): The Elasticsearch version. For example: 9.0.0.A comma-separated list of column names or aliases that determines the sort order.
Sorting defaults to ascending and can be changed by setting :asc
or :desc as a suffix to the column name.
The period to wait for a connection to the master node.
Values are -1 or 0.
The unit used to display time values.
Values are nanos, micros, ms, s, m, h, or d.
GET /_cat/nodes?v=true&h=id,ip,port,v,m&format=json
resp = client.cat.nodes(
v=True,
h="id,ip,port,v,m",
format="json",
)const response = await client.cat.nodes({
v: "true",
h: "id,ip,port,v,m",
format: "json",
});response = client.cat.nodes(
v: "true",
h: "id,ip,port,v,m",
format: "json"
)$resp = $client->cat()->nodes([
"v" => "true",
"h" => "id,ip,port,v,m",
"format" => "json",
]);curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_cat/nodes?v=true&h=id,ip,port,v,m&format=json"client.cat().nodes();
[
{
"ip": "127.0.0.1",
"heap.percent": "65",
"ram.percent": "99",
"cpu": "42",
"load_1m": "3.07",
"load_5m": null,
"load_15m": null,
"node.role": "cdfhilmrstw",
"master": "*",
"name": "mJw06l1"
}
][
{
"id": "veJR",
"ip": "127.0.0.1",
"port": "59938",
"v": "9.0.0",
"m": "*"
}
]Get information about cluster-level changes that have not yet taken effect. IMPORTANT: cat APIs are only intended for human consumption using the command line or Kibana console. They are not intended for use by applications. For application consumption, use the pending cluster tasks API.
monitorList of columns to appear in the response. Supports simple wildcards.
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.
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.
Unit used to display time values.
Values are nanos, micros, ms, s, m, h, or d.
GET /_cat/pending_tasks?v=trueh=insertOrder,timeInQueue,priority,source&format=json
resp = client.cat.pending_tasks(
v="trueh=insertOrder,timeInQueue,priority,source",
format="json",
)const response = await client.cat.pendingTasks({
v: "trueh=insertOrder,timeInQueue,priority,source",
format: "json",
});response = client.cat.pending_tasks(
v: "trueh=insertOrder,timeInQueue,priority,source",
format: "json"
)$resp = $client->cat()->pendingTasks([
"v" => "trueh=insertOrder,timeInQueue,priority,source",
"format" => "json",
]);curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_cat/pending_tasks?v=trueh=insertOrder,timeInQueue,priority,source&format=json"client.cat().pendingTasks();
[
{ "insertOrder": "1685", "timeInQueue": "855ms", "priority": "HIGH", "source": "update-mapping [foo][t]"},
{ "insertOrder": "1686", "timeInQueue": "843ms", "priority": "HIGH", "source": "update-mapping [foo][t]"},
{ "insertOrder": "1693", "timeInQueue": "753ms", "priority": "HIGH", "source": "refresh-mapping [foo][[t]]"},
{ "insertOrder": "1688", "timeInQueue": "816ms", "priority": "HIGH", "source": "update-mapping [foo][t]"},
{ "insertOrder": "1689", "timeInQueue": "802ms", "priority": "HIGH", "source": "update-mapping [foo][t]"},
{ "insertOrder": "1690", "timeInQueue": "787ms", "priority": "HIGH", "source": "update-mapping [foo][t]"},
{ "insertOrder": "1691", "timeInQueue": "773ms", "priority": "HIGH", "source": "update-mapping [foo][t]"}
]Get a list of plugins running on each node of a cluster. IMPORTANT: cat APIs are only intended for human consumption using the command line or Kibana console. They are not intended for use by applications. For application consumption, use the nodes info API.
monitorList of columns to appear in the response. Supports simple wildcards.
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.
Include bootstrap plugins in the response
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.
GET /_cat/plugins?v=true&s=component&h=name,component,version,description&format=json
resp = client.cat.plugins(
v=True,
s="component",
h="name,component,version,description",
format="json",
)const response = await client.cat.plugins({
v: "true",
s: "component",
h: "name,component,version,description",
format: "json",
});response = client.cat.plugins(
v: "true",
s: "component",
h: "name,component,version,description",
format: "json"
)$resp = $client->cat()->plugins([
"v" => "true",
"s" => "component",
"h" => "name,component,version,description",
"format" => "json",
]);curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_cat/plugins?v=true&s=component&h=name,component,version,description&format=json"client.cat().plugins();
[
{ "name": "U7321H6", "component": "analysis-icu", "version": "8.17.0", "description": "The ICU Analysis plugin integrates the Lucene ICU module into Elasticsearch, adding ICU-related analysis components."},
{"name": "U7321H6", "component": "analysis-kuromoji", "verison": "8.17.0", description: "The Japanese (kuromoji) Analysis plugin integrates Lucene kuromoji analysis module into elasticsearch."},
{"name" "U7321H6", "component": "analysis-nori", "version": "8.17.0", "description": "The Korean (nori) Analysis plugin integrates Lucene nori analysis module into elasticsearch."},
{"name": "U7321H6", "component": "analysis-phonetic", "verison": "8.17.0", "description": "The Phonetic Analysis plugin integrates phonetic token filter analysis with elasticsearch."},
{"name": "U7321H6", "component": "analysis-smartcn", "verison": "8.17.0", "description": "Smart Chinese Analysis plugin integrates Lucene Smart Chinese analysis module into elasticsearch."},
{"name": "U7321H6", "component": "analysis-stempel", "verison": "8.17.0", "description": "The Stempel (Polish) Analysis plugin integrates Lucene stempel (polish) analysis module into elasticsearch."},
{"name": "U7321H6", "component": "analysis-ukrainian", "verison": "8.17.0", "description": "The Ukrainian Analysis plugin integrates the Lucene UkrainianMorfologikAnalyzer into elasticsearch."},
{"name": "U7321H6", "component": "discovery-azure-classic", "verison": "8.17.0", "description": "The Azure Classic Discovery plugin allows to use Azure Classic API for the unicast discovery mechanism"},
{"name": "U7321H6", "component": "discovery-ec2", "verison": "8.17.0", "description": "The EC2 discovery plugin allows to use AWS API for the unicast discovery mechanism."},
{"name": "U7321H6", "component": "discovery-gce", "verison": "8.17.0", "description": "The Google Compute Engine (GCE) Discovery plugin allows to use GCE API for the unicast discovery mechanism."},
{"name": "U7321H6", "component": "mapper-annotated-text", "verison": "8.17.0", "description": "The Mapper Annotated_text plugin adds support for text fields with markup used to inject annotation tokens into the index."},
{"name": "U7321H6", "component": "mapper-murmur3", "verison": "8.17.0", "description": "The Mapper Murmur3 plugin allows to compute hashes of a field's values at index-time and to store them in the index."},
{"name": "U7321H6", "component": "mapper-size", "verison": "8.17.0", "description": "The Mapper Size plugin allows document to record their uncompressed size at index time."},
{"name": "U7321H6", "component": "store-smb", "verison": "8.17.0", "description": "The Store SMB plugin adds support for SMB stores."}
]All methods and paths for this operation:
Get information about ongoing and completed shard recoveries. Shard recovery is the process of initializing a shard copy, such as restoring a primary shard from a snapshot or syncing a replica shard from a primary shard. When a shard recovery completes, the recovered shard is available for search and indexing. For data streams, the API returns information about the stream’s backing indices. IMPORTANT: cat APIs are only intended for human consumption using the command line or Kibana console. They are not intended for use by applications. For application consumption, use the index recovery API.
monitormonitorA 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.
If true, the response only includes ongoing shard recoveries.
The unit used to display byte values.
Values are b, kb, mb, gb, tb, or pb.
If true, the response includes detailed information about shard recoveries.
Comma-separated list or wildcard expression of index names to limit the returned information
A comma-separated list of columns names to display. It supports simple wildcards.
Supported values include:
index (or i, idx): The name of the index.shard (or s, sh): The name of the shard.time (or t, ti, primaryOrReplica): The recovery time elasped.type: The type of recovery, from a peer or a snapshot.stage (or st): The stage of the recovery. Returned values are: INIT, INDEX: recovery of lucene files, either reusing local ones are copying new ones, VERIFY_INDEX: potentially running check index, TRANSLOG: starting up the engine, replaying the translog, FINALIZE: performing final task after all translog ops have been done, DONEsource_host (or shost): The host address the index is moving from.source_node (or snode): The node name the index is moving from.target_host (or thost): The host address the index is moving to.target_node (or tnode): The node name the index is moving to.repository (or tnode): The name of the repository being used. if not relevant 'n/a'.snapshot (or snap): The name of the snapshot being used. if not relevant 'n/a'.files (or f): The total number of files to recover.files_recovered (or fr): The number of files currently recovered.files_percent (or fp): The percentage of files currently recovered.files_total (or tf): The total number of files.bytes (or b): The total number of bytes to recover.bytes_recovered (or br): Total number of bytes currently recovered.bytes_percent (or bp): The percentage of bytes currently recovered.bytes_total (or tb): The total number of bytes.translog_ops (or to): The total number of translog ops to recover.translog_ops_recovered (or tor): The total number of translog ops currently recovered.translog_ops_percent (or top): The percentage of translog ops currently recovered.start_time (or start): The start time of the recovery operation.start_time_millis (or start_millis): The start time of the recovery operation in eopch milliseconds.stop_time (or stop): The end time of the recovery operation. If ongoing '1970-01-01T00:00:00.000Z'stop_time_millis (or stop_millis): The end time of the recovery operation in eopch milliseconds. If ongoing '0'Values are index, i, idx, shard, s, sh, time, t, ti, primaryOrReplica, type, stage, st, source_host, shost, source_node, snode, target_host, thost, target_node, tnode, repository, snapshot, snap, files, f, files_recovered, fr, files_percent, fp, files_total, tf, bytes, b, bytes_recovered, br, bytes_percent, bp, bytes_total, tb, translog_ops, to, translog_ops_recovered, tor, translog_ops_percent, top, start_time, start, start_time_millis, start_millis, stop_time, stop, stop_time_millis, or stop_millis.
A comma-separated list of column names or aliases that determines the sort order.
Sorting defaults to ascending and can be changed by setting :asc
or :desc as a suffix to the column name.
The unit used to display time values.
Values are nanos, micros, ms, s, m, h, or d.
GET _cat/recovery?v=true&format=json
resp = client.cat.recovery(
v=True,
format="json",
)const response = await client.cat.recovery({
v: "true",
format: "json",
});response = client.cat.recovery(
v: "true",
format: "json"
)$resp = $client->cat()->recovery([
"v" => "true",
"format" => "json",
]);curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_cat/recovery?v=true&format=json"client.cat().recovery();
[
{
"index": "my-index-000001 ",
"shard": "0",
"time": "13ms",
"type": "store",
"stage": "done",
"source_host": "n/a",
"source_node": "n/a",
"target_host": "127.0.0.1",
"target_node": "node-0",
"repository": "n/a",
"snapshot": "n/a",
"files": "0",
"files_recovered": "0",
"files_percent": "100.0%",
"files_total": "13",
"bytes": "0b",
"bytes_recovered": "0b",
"bytes_percent": "100.0%",
"bytes_total": "9928b",
"translog_ops": "0",
"translog_ops_recovered": "0",
"translog_ops_percent": "100.0%"
}
][
{
"i": "my-index-000001",
"s": "0",
"t": "1252ms",
"ty": "peer",
"st": "done",
"shost": "192.168.1.1",
"thost": "192.168.1.1",
"f": "0",
"fp": "100.0%",
"b": "0b",
"bp": "100.0%",
}
][
{
"i": "my-index-000001",
"s": "0",
"t": "1978ms",
"ty": "snapshot",
"st": "done",
"rep": "my-repo",
"snap": "snap-1",
"f": "79",
"fp": "8.0%",
"b": "12086",
"bp": "9.0%"
}
]Get a list of snapshot repositories for a cluster. IMPORTANT: cat APIs are only intended for human consumption using the command line or Kibana console. They are not intended for use by applications. For application consumption, use the get snapshot repository API.
monitor_snapshotList of columns to appear in the response. Supports simple wildcards.
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.
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.
GET /_cat/repositories?v=true&format=json
resp = client.cat.repositories(
v=True,
format="json",
)const response = await client.cat.repositories({
v: "true",
format: "json",
});response = client.cat.repositories(
v: "true",
format: "json"
)$resp = $client->cat()->repositories([
"v" => "true",
"format" => "json",
]);curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_cat/repositories?v=true&format=json"client.cat().repositories();
[
{
"id": "repo1",
"type": "fs"
},
{
"id": "repo2",
"type": "s3"
}
]All methods and paths for this operation:
Get low-level information about the Lucene segments in index shards. For data streams, the API returns information about the backing indices. IMPORTANT: cat APIs are only intended for human consumption using the command line or Kibana console. They are not intended for use by applications. For application consumption, use the index segments API.
monitormonitorA 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.
The unit used to display byte values.
Values are b, kb, mb, gb, tb, or pb.
A comma-separated list of columns names to display. It supports simple wildcards.
Supported values include:
index (or i, idx): The name of the index.shard (or s, sh): The name of the shard.prirep (or p, pr, primaryOrReplica): The shard type. Returned values are 'primary' or 'replica'.ip: IP address of the segment’s shard, such as '127.0.1.1'.segment: The name of the segment, such as '_0'. The segment name is derived from the segment generation and used internally to create file names in the directory of the shard.generation: Generation number, such as '0'. Elasticsearch increments this generation number for each segment written. Elasticsearch then uses this number to derive the segment name.docs.count: The number of documents as reported by Lucene. This excludes deleted documents and counts any nested documents separately from their parents. It also excludes documents which were indexed recently and do not yet belong to a segment.docs.deleted: The number of deleted documents as reported by Lucene, which may be higher or lower than the number of delete operations you have performed. This number excludes deletes that were performed recently and do not yet belong to a segment. Deleted documents are cleaned up by the automatic merge process if it makes sense to do so. Also, Elasticsearch creates extra deleted documents to internally track the recent history of operations on a shard.size: The disk space used by the segment, such as '50kb'.size.memory: The bytes of segment data stored in memory for efficient search, such as '1264'. A value of '-1' indicates Elasticsearch was unable to compute this number.committed: If 'true', the segments is synced to disk. Segments that are synced can survive a hard reboot. If 'false', the data from uncommitted segments is also stored in the transaction log so that Elasticsearch is able to replay changes on the next start.searchable: If 'true', the segment is searchable. If 'false', the segment has most likely been written to disk but needs a refresh to be searchable.version: The version of Lucene used to write the segment.compound: If 'true', the segment is stored in a compound file. This means Lucene merged all files from the segment in a single file to save file descriptors.id: The ID of the node, such as 'k0zy'.Values are index, i, idx, shard, s, sh, prirep, p, pr, primaryOrReplica, ip, segment, generation, docs.count, docs.deleted, size, size.memory, committed, searchable, version, compound, or id.
A comma-separated list of column names or aliases that determines the sort order.
Sorting defaults to ascending and can be changed by setting :asc
or :desc as a suffix to the column name.
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.
GET /_cat/segments?v=true&format=json
resp = client.cat.segments(
v=True,
format="json",
)const response = await client.cat.segments({
v: "true",
format: "json",
});response = client.cat.segments(
v: "true",
format: "json"
)$resp = $client->cat()->segments([
"v" => "true",
"format" => "json",
]);curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_cat/segments?v=true&format=json"client.cat().segments();
[
{
"index": "test",
"shard": "0",
"prirep": "p",
"ip": "127.0.0.1",
"segment": "_0",
"generation": "0",
"docs.count": "1",
"docs.deleted": "0",
"size": "3kb",
"size.memory": "0",
"committed": "false",
"searchable": "true",
"version": "9.12.0",
"compound": "true"
},
{
"index": "test1",
"shard": "0",
"prirep": "p",
"ip": "127.0.0.1",
"segment": "_0",
"generation": "0",
"docs.count": "1",
"docs.deleted": "0",
"size": "3kb",
"size.memory": "0",
"committed": "false",
"searchable": "true",
"version": "9.12.0",
"compound": "true"
}
]All methods and paths for this operation:
Get information about the shards in a cluster. For data streams, the API returns information about the backing indices. IMPORTANT: cat APIs are only intended for human consumption using the command line or Kibana console. They are not intended for use by applications.
monitormonitorA 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.
The unit used to display byte values.
Values are b, kb, mb, gb, tb, or pb.
List of columns to appear in the response. Supports simple wildcards.
Supported values include:
completion.size (or cs, completionSize): Size of completion. For example: 0b.dataset.size: Disk space used by the shard’s dataset, which may or may not be the size on
disk, but includes space used by the shard on object storage. Reported as a size value for example: 5kb.dense_vector.value_count (or dvc, denseVectorCount): Number of indexed dense vectors.docs (or d, dc): Number of documents in shard, for example: 25.fielddata.evictions (or fe, fielddataEvictions): Fielddata cache evictions, for example: 0.fielddata.memory_size (or fm, fielddataMemory): Used fielddata cache memory, for example: 0b.flush.total (or ft, flushTotal): Number of flushes, for example: 1.flush.total_time (or ftt, flushTotalTime): Time spent in flush, for example: 1.get.current (or gc, getCurrent): Number of current get operations, for example: 0.get.exists_time (or geti, getExistsTime): Time spent in successful gets, for example: 14ms.get.exists_total (or geto, getExistsTotal): Number of successful get operations, for example: 2.get.missing_time (or gmti, getMissingTime): Time spent in failed gets, for example: 0s.get.missing_total (or gmto, getMissingTotal): Number of failed get operations, for example: 1.get.time (or gti, getTime): Time spent in get, for example: 14ms.get.total (or gto, getTotal): Number of get operations, for example: 2.id: ID of the node, for example: k0zy.index (or i, idx): Name of the index.indexing.delete_current (or idc, indexingDeleteCurrent): Number of current deletion operations, for example: 0.indexing.delete_time (or idti, indexingDeleteTime): Time spent in deletions, for example: 2ms.indexing.delete_total (or idto, indexingDeleteTotal): Number of deletion operations, for example: 2.indexing.index_current (or iic, indexingIndexCurrent): Number of current indexing operations, for example: 0.indexing.index_failed_due_to_version_conflict (or iifvc, indexingIndexFailedDueToVersionConflict): Number of failed indexing operations due to version conflict, for example: 0.indexing.index_failed (or iif, indexingIndexFailed): Number of failed indexing operations, for example: 0.indexing.index_time (or iiti, indexingIndexTime): Time spent in indexing, such as for example: 134ms.indexing.index_total (or iito, indexingIndexTotal): Number of indexing operations, for example: 1.ip: IP address of the node, for example: 127.0.1.1.merges.current (or mc, mergesCurrent): Number of current merge operations, for example: 0.merges.current_docs (or mcd, mergesCurrentDocs): Number of current merging documents, for example: 0.merges.current_size (or mcs, mergesCurrentSize): Size of current merges, for example: 0b.merges.total (or mt, mergesTotal): Number of completed merge operations, for example: 0.merges.total_docs (or mtd, mergesTotalDocs): Number of merged documents, for example: 0.merges.total_size (or mts, mergesTotalSize): Size of current merges, for example: 0b.merges.total_time (or mtt, mergesTotalTime): Time spent merging documents, for example: 0s.node (or n): Node name, for example: I8hydUG.prirep (or p, pr, primaryOrReplica): Shard type. Returned values are primary or replica.query_cache.evictions (or qce, queryCacheEvictions): Query cache evictions, for example: 0.query_cache.memory_size (or qcm, queryCacheMemory): Used query cache memory, for example: 0b.recoverysource.type (or rs): Type of recovery source.refresh.time (or rti, refreshTime): Time spent in refreshes, for example: 91ms.refresh.total (or rto, refreshTotal): Number of refreshes, for example: 16.search.fetch_current (or sfc, searchFetchCurrent): Current fetch phase operations, for example: 0.search.fetch_time (or sfti, searchFetchTime): Time spent in fetch phase, for example: 37ms.search.fetch_total (or sfto, searchFetchTotal): Number of fetch operations, for example: 7.search.open_contexts (or so, searchOpenContexts): Open search contexts, for example: 0.search.query_current (or sqc, searchQueryCurrent): Current query phase operations, for example: 0.search.query_time (or sqti, searchQueryTime): Time spent in query phase, for example: 43ms.search.query_total (or sqto, searchQueryTotal): Number of query operations, for example: 9.search.scroll_current (or scc, searchScrollCurrent): Open scroll contexts, for example: 2.search.scroll_time (or scti, searchScrollTime): Time scroll contexts held open, for example: 2m.search.scroll_total (or scto, searchScrollTotal): Completed scroll contexts, for example: 1.segments.count (or sc, segmentsCount): Number of segments, for example: 4.segments.fixed_bitset_memory (or sfbm, fixedBitsetMemory): Memory used by fixed bit sets for nested object field types and type filters for types referred in join fields, for example: 1.0kb.segments.index_writer_memory (or siwm, segmentsIndexWriterMemory): Memory used by index writer, for example: 18mb.segments.memory (or sm, segmentsMemory): Memory used by segments, for example: 1.4kb.segments.version_map_memory (or svmm, segmentsVersionMapMemory): Memory used by version map, for example: 1.0kb.seq_no.global_checkpoint (or sqg, globalCheckpoint): Global checkpoint.seq_no.local_checkpoint (or sql, localCheckpoint): Local checkpoint.seq_no.max (or sqm, maxSeqNo): Maximum sequence number.shard (or s, sh): Name of the shard.dsparse_vector.value_count (or svc, sparseVectorCount): Number of indexed sparse vectors.state (or st): State of the shard. Returned values are:
INITIALIZING: The shard is recovering from a peer shard or gateway.RELOCATING: The shard is relocating.STARTED: The shard has started.UNASSIGNED: The shard is not assigned to any node.store (or sto): Disk space used by the shard, for example: 5kb.suggest.current (or suc, suggestCurrent): Number of current suggest operations, for example: 0.suggest.time (or suti, suggestTime): Time spent in suggest, for example: 0.suggest.total (or suto, suggestTotal): Number of suggest operations, for example: 0.sync_id: Sync ID of the shard.unassigned.at (or ua): Time at which the shard became unassigned in Coordinated Universal Time (UTC).unassigned.details (or ud): Details about why the shard became unassigned. This does not explain why the shard is currently unassigned. To understand why a shard
is not assigned, use the Cluster allocation explain API.unassigned.for (or uf): Time at which the shard was requested to be unassigned in Coordinated Universal Time (UTC).unassigned.reason (or ur): Indicates the reason for the last change to the state of this unassigned shard. This does not explain why the shard is currently unassigned.
To understand why a shard is not assigned, use the Cluster allocation explain API. Returned values include:
ALLOCATION_FAILED: Unassigned as a result of a failed allocation of the shard.CLUSTER_RECOVERED: Unassigned as a result of a full cluster recovery.DANGLING_INDEX_IMPORTED: Unassigned as a result of importing a dangling index.EXISTING_INDEX_RESTORED: Unassigned as a result of restoring into a closed index.FORCED_EMPTY_PRIMARY: The shard’s allocation was last modified by forcing an empty primary using the Cluster reroute API.INDEX_CLOSED: Unassigned because the index was closed.INDEX_CREATED: Unassigned as a result of an API creation of an index.INDEX_REOPENED: Unassigned as a result of opening a closed index.MANUAL_ALLOCATION: The shard’s allocation was last modified by the Cluster reroute API.NEW_INDEX_RESTORED: Unassigned as a result of restoring into a new index.NODE_LEFT: Unassigned as a result of the node hosting it leaving the cluster.NODE_RESTARTING: Similar to NODE_LEFT, except that the node was registered as restarting using the Node shutdown API.PRIMARY_FAILED: The shard was initializing as a replica, but the primary shard failed before the initialization completed.REALLOCATED_REPLICA: A better replica location is identified and causes the existing replica allocation to be cancelled.REINITIALIZED: When a shard moves from started back to initializing.REPLICA_ADDED: Unassigned as a result of explicit addition of a replica.REROUTE_CANCELLED: Unassigned as a result of explicit cancel reroute command.Values are completion.size, cs, completionSize, dataset.size, dense_vector.value_count, dvc, denseVectorCount, docs, d, dc, fielddata.evictions, fe, fielddataEvictions, fielddata.memory_size, fm, fielddataMemory, flush.total, ft, flushTotal, flush.total_time, ftt, flushTotalTime, get.current, gc, getCurrent, get.exists_time, geti, getExistsTime, get.exists_total, geto, getExistsTotal, get.missing_time, gmti, getMissingTime, get.missing_total, gmto, getMissingTotal, get.time, gti, getTime, get.total, gto, getTotal, id, index, i, idx, indexing.delete_current, idc, indexingDeleteCurrent, indexing.delete_time, idti, indexingDeleteTime, indexing.delete_total, idto, indexingDeleteTotal, indexing.index_current, iic, indexingIndexCurrent, indexing.index_failed_due_to_version_conflict, iifvc, indexingIndexFailedDueToVersionConflict, indexing.index_failed, iif, indexingIndexFailed, indexing.index_time, iiti, indexingIndexTime, indexing.index_total, iito, indexingIndexTotal, ip, merges.current, mc, mergesCurrent, merges.current_docs, mcd, mergesCurrentDocs, merges.current_size, mcs, mergesCurrentSize, merges.total, mt, mergesTotal, merges.total_docs, mtd, mergesTotalDocs, merges.total_size, mts, mergesTotalSize, merges.total_time, mtt, mergesTotalTime, node, n, prirep, p, pr, primaryOrReplica, query_cache.evictions, qce, queryCacheEvictions, query_cache.memory_size, qcm, queryCacheMemory, recoverysource.type, rs, refresh.time, rti, refreshTime, refresh.total, rto, refreshTotal, search.fetch_current, sfc, searchFetchCurrent, search.fetch_time, sfti, searchFetchTime, search.fetch_total, sfto, searchFetchTotal, search.open_contexts, so, searchOpenContexts, search.query_current, sqc, searchQueryCurrent, search.query_time, sqti, searchQueryTime, search.query_total, sqto, searchQueryTotal, search.scroll_current, scc, searchScrollCurrent, search.scroll_time, scti, searchScrollTime, search.scroll_total, scto, searchScrollTotal, segments.count, sc, segmentsCount, segments.fixed_bitset_memory, sfbm, fixedBitsetMemory, segments.index_writer_memory, siwm, segmentsIndexWriterMemory, segments.memory, sm, segmentsMemory, segments.version_map_memory, svmm, segmentsVersionMapMemory, seq_no.global_checkpoint, sqg, globalCheckpoint, seq_no.local_checkpoint, sql, localCheckpoint, seq_no.max, sqm, maxSeqNo, shard, s, sh, dsparse_vector.value_count, svc, sparseVectorCount, state, st, store, sto, suggest.current, suc, suggestCurrent, suggest.time, suti, suggestTime, suggest.total, suto, suggestTotal, sync_id, unassigned.at, ua, unassigned.details, ud, unassigned.for, uf, unassigned.reason, or ur.
A comma-separated list of column names or aliases that determines the sort order.
Sorting defaults to ascending and can be changed by setting :asc
or :desc as a suffix to the column name.
The period to wait for a connection to the master node.
Values are -1 or 0.
The unit used to display time values.
Values are nanos, micros, ms, s, m, h, or d.
GET _cat/shards?format=json
resp = client.cat.shards(
format="json",
)const response = await client.cat.shards({
format: "json",
});response = client.cat.shards(
format: "json"
)$resp = $client->cat()->shards([
"format" => "json",
]);curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_cat/shards?format=json"client.cat().shards();
[
{
"index": "my-index-000001",
"shard": "0",
"prirep": "p",
"state": "STARTED",
"docs": "3014",
"store": "31.1mb",
"dataset": "249b",
"ip": "192.168.56.10",
"node": "H5dfFeA"
}
][
{
"index": "my-index-000001",
"shard": "0",
"prirep": "p",
"state": "STARTED",
"docs": "3014",
"store": "31.1mb",
"dataset": "249b",
"ip": "192.168.56.10",
"node": "H5dfFeA"
}
][
{
"index": "my-index-000001",
"shard": "0",
"prirep": "p",
"state": "RELOCATING",
"docs": "3014",
"store": "31.1mb",
"dataset": "249b",
"ip": "192.168.56.10",
"node": "H5dfFeA -> -> 192.168.56.30 bGG90GE"
}
][
{
"index": "my-index-000001",
"shard": "0",
"prirep": "p",
"state": "STARTED",
"docs": "3014",
"store": "31.1mb",
"dataset": "249b",
"ip": "192.168.56.10",
"node": "H5dfFeA"
},
{
"index": "my-index-000001",
"shard": "0",
"prirep": "r",
"state": "INITIALIZING",
"docs": "0",
"store": "14.3mb",
"dataset": "249b",
"ip": "192.168.56.30",
"node": "bGG90GE"
}
][
{
"index": "my-index-000001",
"shard": "0",
"prirep": "p",
"state": "STARTED",
"unassigned.reason": "3014 31.1mb 192.168.56.10 H5dfFeA"
},
{
"index": "my-index-000001",
"shard": "0",
"prirep": "r",
"state": "STARTED",
"unassigned.reason": "3014 31.1mb 192.168.56.30 bGG90GE"
},
{
"index": "my-index-000001",
"shard": "0",
"prirep": "r",
"state": "STARTED",
"unassigned.reason": "3014 31.1mb 192.168.56.20 I8hydUG"
},
{
"index": "my-index-000001",
"shard": "0",
"prirep": "r",
"state": "UNASSIGNED",
"unassigned.reason": "ALLOCATION_FAILED"
}
]All methods and paths for this operation:
Get information about the snapshots stored in one or more repositories. A snapshot is a backup of an index or running Elasticsearch cluster. IMPORTANT: cat APIs are only intended for human consumption using the command line or Kibana console. They are not intended for use by applications. For application consumption, use the get snapshot API.
monitor_snapshotA comma-separated list of snapshot repositories used to limit the request.
Accepts wildcard expressions.
_all returns all repositories.
If any repository fails during the request, Elasticsearch returns an error.
A comma-separated list of columns names to display. It supports simple wildcards.
Supported values include:
id (or snapshot): The ID of the snapshot, such as 'snap1'.repository (or re, repo): The name of the repository, such as 'repo1'.status (or s): State of the snapshot process. Returned values are: 'FAILED': The snapshot process failed. 'INCOMPATIBLE': The snapshot process is incompatible with the current cluster version. 'IN_PROGRESS': The snapshot process started but has not completed. 'PARTIAL': The snapshot process completed with a partial success. 'SUCCESS': The snapshot process completed with a full success.start_epoch (or ste, startEpoch): The unix epoch time at which the snapshot process started.start_time (or sti, startTime): 'HH:MM:SS' time at which the snapshot process started.end_epoch (or ete, endEpoch): The unix epoch time at which the snapshot process ended.end_time (or eti, endTime): 'HH:MM:SS' time at which the snapshot process ended.duration (or dur): The time it took the snapshot process to complete in time units.indices (or i): The number of indices in the snapshot.successful_shards (or ss): The number of successful shards in the snapshot.failed_shards (or fs): The number of failed shards in the snapshot.total_shards (or ts): The total number of shards in the snapshot.reason (or r): The reason for any snapshot failures.Values are id, snapshot, repository, re, repo, status, s, start_epoch, ste, startEpoch, start_time, sti, startTime, end_epoch, ete, endEpoch, end_time, eti, endTime, duration, dur, indices, i, successful_shards, ss, failed_shards, fs, total_shards, ts, reason, or r.
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.
Period to wait for a connection to the master node.
Values are -1 or 0.
Unit used to display time values.
Values are nanos, micros, ms, s, m, h, or d.
GET /_cat/snapshots/repo1?v=true&s=id&format=json
resp = client.cat.snapshots(
repository="repo1",
v=True,
s="id",
format="json",
)const response = await client.cat.snapshots({
repository: "repo1",
v: "true",
s: "id",
format: "json",
});response = client.cat.snapshots(
repository: "repo1",
v: "true",
s: "id",
format: "json"
)$resp = $client->cat()->snapshots([
"repository" => "repo1",
"v" => "true",
"s" => "id",
"format" => "json",
]);curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_cat/snapshots/repo1?v=true&s=id&format=json"client.cat().snapshots();
[
{
"id": "snap1",
"repository": "repo1",
"status": "FAILED",
"start_epoch": "1445616705",
"start_time": "18:11:45",
"end_epoch": "1445616978",
"end_time": "18:16:18",
"duration": "4.6m",
"indices": "1",
"successful_shards": "4",
"failed_shards": "1",
"total_shards": "5"
},
{
"id": "snap2",
"repository": "repo1",
"status": "SUCCESS",
"start_epoch": "1445634298",
"start_time": "23:04:58",
"end_epoch": "1445634672",
"end_time": "23:11:12",
"duration": "6.2m",
"indices": "2",
"successful_shards": "10",
"failed_shards": "0",
"total_shards": "10"
}
]Get information about tasks currently running in the cluster. IMPORTANT: cat APIs are only intended for human consumption using the command line or Kibana console. They are not intended for use by applications. For application consumption, use the task management API.
monitorThe task action names, which are used to limit the response.
If true, the response includes detailed information about shard recoveries.
Unique node identifiers, which are used to limit the response.
The parent task identifier, which is used to limit the response.
List of columns to appear in the response. Supports simple wildcards.
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.
Unit used to display time values.
Values are nanos, micros, ms, s, m, h, or d.
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.
If true, the request blocks until the task has completed.
GET _cat/tasks?v=true&format=json
resp = client.cat.tasks(
v=True,
format="json",
)const response = await client.cat.tasks({
v: "true",
format: "json",
});response = client.cat.tasks(
v: "true",
format: "json"
)$resp = $client->cat()->tasks([
"v" => "true",
"format" => "json",
]);curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_cat/tasks?v=true&format=json"client.cat().tasks();
[
{
"action": "cluster:monitor/tasks/lists[n]",
"task_id": "oTUltX4IQMOUUVeiohTt8A:124",
"parent_task_id": "oTUltX4IQMOUUVeiohTt8A:123",
"type": "direct",
"start_time": "1458585884904",
"timestamp": "01:48:24",
"running_time": "44.1micros",
"ip": "127.0.0.1:9300",
"node": "oTUltX4IQMOUUVeiohTt8A"
},
{
"action": "cluster:monitor/tasks/lists",
"task_id": "oTUltX4IQMOUUVeiohTt8A:123",
"parent_task_id": "-",
"type": "transport",
"start_time": "1458585884904",
"timestamp": "01:48:24",
"running_time": "186.2micros",
"ip": "127.0.0.1:9300",
"node": "oTUltX4IQMOUUVeiohTt8A"
}
]All methods and paths for this operation:
Get information about the index templates in a cluster. You can use index templates to apply index settings and field mappings to new indices at creation. IMPORTANT: cat APIs are only intended for human consumption using the command line or Kibana console. They are not intended for use by applications. For application consumption, use the get index template API.
monitorThe name of the template to return. Accepts wildcard expressions. If omitted, all templates are returned.
List of columns to appear in the response. Supports simple wildcards.
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.
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.
GET _cat/templates/my-template-*?v=true&s=name&format=json
resp = client.cat.templates(
name="my-template-*",
v=True,
s="name",
format="json",
)const response = await client.cat.templates({
name: "my-template-*",
v: "true",
s: "name",
format: "json",
});response = client.cat.templates(
name: "my-template-*",
v: "true",
s: "name",
format: "json"
)$resp = $client->cat()->templates([
"name" => "my-template-*",
"v" => "true",
"s" => "name",
"format" => "json",
]);curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_cat/templates/my-template-*?v=true&s=name&format=json"client.cat().templates();
[
{
"name": "my-template-0",
"index_patterns": "[te*]",
"order": "500",
"version": null,
"composed_of": "[]"
},
{
"name": "my-template-1",
"index_patterns": "[tea*]",
"order": "501",
"version": null,
"composed_of": "[]"
},
{
"name": "my-template-2",
"index_patterns": "[teak*]",
"order": "502",
"version": "7",
"composed_of": "[]"
}
]