Method: projects.locations.datasets.exportData

Exports dataset's data to the provided output location. Returns an empty response in the response field when it completes.

HTTP request

POST https://automl.googleapis.com/v1beta1/{name}:exportData

Path parameters

Parameters
name

string

Required. The resource name of the dataset.

Authorization requires the following Google IAM permission on the specified resource name:

  • automl.datasets.export

Request body

The request body contains data with the following structure:

JSON representation
{
  "outputConfig": {
    object(OutputConfig)
  }
}
Fields
outputConfig

object(OutputConfig)

Required. The desired output location.

Response body

If successful, the response body contains an instance of Operation.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

OutputConfig

Output configuration for datasets.exportData.

As destination the gcsDestination must be set unless specified otherwise for a domain. Only ground truth annotations are exported (not approved annotations are not exported).

The outputs correspond to how the data was imported, and may be used as input to import data. The output formats are represented as EBNF with literal commas and same non-terminal symbol definitions as in InputConfig, which is a CSV file(s) with each line in formats:

AutoML Natural Language Classification

ML_USE,GCS_FILE_PATH,LABEL(S)
  • ML_USE - Identifies the data set that the current row (file) applies to. This value can be one of the following:

    • TRAIN - Rows in this file are used to train the model.
    • TEST - Rows in this file are used to test the model during training.
    • UNASSIGNED - Rows in this file are not categorized. They are Automatically divided into train and test data. 80% for training and 20% for testing.
  • GCS_FILE_PATH - Identifies a text file that contains the content of the example.

  • LABEL(S) - The classification label(s) for the sample.

AutoML Natural Language Entity Extraction

ML_USE,GCS_FILE_PATH
  • ML_USE - Identifies the data set that the current row (file) applies to. This value can be one of the following:

    • TRAIN - Rows in this file are used to train the model.
    • TEST - Rows in this file are used to test the model during training.
    • UNASSIGNED - Rows in this file are not categorized. They are Automatically divided into train and test data. 80% for training and 20% for testing.
  • GCS_FILE_PATH - Identifies a JSON Lines (.JSONL) file stored in Google Cloud Storage that contains in-line text in-line as documents for model training.

AutoML Natural Language Sentiment Analysis

ML_USE,GCS_FILE_PATH,SENTIMENT
  • ML_USE - Identifies the data set that the current row (file) applies to. This value can be one of the following:

    • TRAIN - Rows in this file are used to train the model.
    • TEST - Rows in this file are used to test the model during training.
    • UNASSIGNED - Rows in this file are not categorized. They are Automatically divided into train and test data. 80% for training and 20% for testing.
  • GCS_FILE_PATH - Identifies a text file that contains the content of the example.

  • SENTIMENT - The sentiment score for the sample.

JSON representation
{
  "gcsDestination": {
    object(GcsDestination)
  }
}
Fields
gcsDestination

object(GcsDestination)

The Google Cloud Storage location where the output is to be written to. In the given directory a new directory will be created with name: export_data-<dataset-display-name>-<timestamp-of-export-call> where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. All export output will be written into that directory.

Was this page helpful? Let us know how we did:

Send feedback about...

AutoML Natural Language Sentiment Analysis