Get trained models | Elasticsearch API documentation (original) (raw)

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Query parameters

• Specifies 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.

Responses

• 200 application/json
  Hide response attributes Show response attributes object
  • Information about the creator of the model.
  • The estimated number of operations to use the model. This number helps to measure the computational complexity of the model.
  • The license level of the model.

  • create_time string | number

  A date and time, either as a string whose format can depend on the context (defaulting to ISO 8601), or a number of milliseconds since the Epoch. Elasticsearch accepts both as input, but will generally output a string representation.
  Time unit for milliseconds

  • A description of the model.
  • The number of pipelines that are referencing the model.
  • The total number of documents that are processed by the model.
  • The total time spent processing documents with thie model.
  • The total number of documents that are currently being handled by the model.
  • The total number of failed ingest attempts with the model.
  • The identifier for the data frame analytics job that created the model. Only displayed if the job is still available.
  • The time the data frame analytics job was created.
  • The source index used to train in the data frame analysis.
  • The analysis used by the data frame to build the model.