Get machine learning memory usage info

  • GET /_ml/memory/{node_id}/_stats
  • GET /_ml/memory/_stats
Auth

Get information about how machine learning jobs and trained models are using memory, on each node, both within the JVM heap, and natively, outside of the JVM.

Required authorization

Cluster privileges monitor_ml

Path parameters

node_id string optional

The names of particular nodes in the cluster to target. For example, nodeId1,nodeId2 or ml:true

Leave it out to use /_ml/memory/_stats.

Query parameters

master_timeout string · default: 30s

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.

timeout string · default: 30s

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

Response

application/json
_nodes object required
failures object[]
type string required

The type of error

reason union string nullable

A human-readable explanation of the error, in English.

One of: string
stack_trace string

The server stack trace. Present only if the error_trace=true parameter was sent with the request.

caused_by object
Same fields as failures in _nodes
root_cause object[]
Same fields as failures in _nodes
suppressed object[]
Same fields as failures in _nodes
total number required

Total number of nodes selected by the request.

successful number required

Number of nodes that responded successfully to the request.

failed number required

Number of nodes that rejected the request or failed to respond. If this value is not 0, a reason for the rejection or failure is included in the response.

cluster_name string required
nodes map string to object required
<string> object
attributes map string to string required
jvm object required

Contains Java Virtual Machine (JVM) statistics for the node.

heap_max number | string

Maximum amount of memory available for use by the heap.

heap_max_in_bytes number required

Maximum amount of memory, in bytes, available for use by the heap.

java_inference number | string

Amount of Java heap currently being used for caching inference models.

java_inference_in_bytes number required

Amount of Java heap, in bytes, currently being used for caching inference models.

java_inference_max number | string

Maximum amount of Java heap to be used for caching inference models.

java_inference_max_in_bytes number required

Maximum amount of Java heap, in bytes, to be used for caching inference models.

mem object required

Contains statistics about memory usage for the node.

adjusted_total number | string

If the amount of physical memory has been overridden using the es.total_memory_bytes system property then this reports the overridden value. Otherwise it reports the same value as total.

adjusted_total_in_bytes number required

If the amount of physical memory has been overridden using the es.total_memory_bytes system property then this reports the overridden value in bytes. Otherwise it reports the same value as total_in_bytes.

total number | string

Total amount of physical memory.

total_in_bytes number required

Total amount of physical memory in bytes.

ml object required

Contains statistics about machine learning use of native memory on the node.

anomaly_detectors number | string

Amount of native memory set aside for anomaly detection jobs.

anomaly_detectors_in_bytes number required

Amount of native memory, in bytes, set aside for anomaly detection jobs.

data_frame_analytics number | string

Amount of native memory set aside for data frame analytics jobs.

data_frame_analytics_in_bytes number required

Amount of native memory, in bytes, set aside for data frame analytics jobs.

max number | string

Maximum amount of native memory (separate to the JVM heap) that may be used by machine learning native processes.

max_in_bytes number required

Maximum amount of native memory (separate to the JVM heap), in bytes, that may be used by machine learning native processes.

native_code_overhead number | string

Amount of native memory set aside for loading machine learning native code shared libraries.

native_code_overhead_in_bytes number required

Amount of native memory, in bytes, set aside for loading machine learning native code shared libraries.

native_inference number | string

Amount of native memory set aside for trained models that have a PyTorch model_type.

native_inference_in_bytes number required

Amount of native memory, in bytes, set aside for trained models that have a PyTorch model_type.

name string required

Human-readable identifier for the node. Based on the Node name setting setting.

roles string[] required

Roles assigned to the node.

transport_address string required

The host and port where transport HTTP connections are accepted.

ephemeral_id string required