Manage models
This page shows you how to manage BigQuery ML models including copying models and renaming models.
Required roles
To get the permissions that you need to to read and create BigQuery models,
ask your administrator to grant you the
BigQuery Data Editor (roles/bigquery.dataEditor
) IAM role on the project.
For more information about granting roles, see Manage access to projects, folders, and organizations.
This predefined role contains the permissions required to to read and create BigQuery models. To see the exact permissions that are required, expand the Required permissions section:
Required permissions
The following permissions are required to to read and create BigQuery models:
-
To read information from models:
bigquery.models.getData
-
To create models:
bigquery.models.create
You might also be able to get these permissions with custom roles or other predefined roles.
Rename models
You cannot change the name of an existing model. If you need to change the model's name, follow the steps to copy the model. When you specify the destination in the copy operation, use the new model name.
Copy models
You can copy one or more models from a source dataset to a destination dataset by:
- Using the Google Cloud console.
- Using the bq command-line tool's
bq cp
command. - Calling the jobs.insert API method directly and configuring a copy job or by using the client libraries.
Limitations on copying models
Model copy jobs are subject to the following limitations:
- When you copy a model, the name of the destination model must adhere to the same naming conventions as when you create a model.
- Model copies are subject to BigQuery limits on copy jobs.
- Copying a model is not supported by the Google Cloud console.
- Copying multiple source models in a single command is not supported.
- When you copy a model by using the CLI, the
--destination_kms_key
flag is not supported.
Copy a model
You can copy a model by:
- Using the command-line tool's
bq cp
command - Calling the
jobs.insert
API method and configuring a copy job or by using the client libraries
To copy a model:
Console
The Google Cloud console does not support copying models.
bq
Issue the bq cp
command. Optional flags:
-f
or--force
overwrites an existing model in the destination dataset and doesn't prompt you for confirmation.-n
or--no_clobber
returns the following error message if the model exists in the destination dataset:'[PROJECT_ID]:[DATASET].[MODEL]' already exists, skipping
.If
-n
is not specified, the default behavior is to prompt you to choose whether to replace the destination model.
If the source or destination dataset is in a project other than your default
project, add the project ID to the dataset names in the following format:
PROJECT_ID:DATASET
.
Supply the
--location
flag and set the value to your
location.
bq --location=LOCATION cp -f -n PROJECT_ID:DATASET.SOURCE_MODEL PROJECT_ID:DATASET.DESTINATION_MODEL
Replace the following:
- LOCATION:
the name of your location. The
--location
flag is optional. For example, if you are using BigQuery in the Tokyo region, you can set the flag's value toasia-northeast1
. You can set a default value for the location using the .bigqueryrc file. For a full list of locations, see BigQuery locations. - PROJECT_ID: your project ID.
- DATASET: the name of the source or destination dataset.
- SOURCE_MODEL: the model you're copying.
- DESTINATION_MODEL: the name of the model in the destination dataset.
Examples:
Enter the following command to copy mydataset.mymodel
to
mydataset2
.
Both datasets are in your default project and were
created in the US
multi-region location.
bq --location=US cp mydataset.mymodel mydataset2.mymodel
Enter the following command to copy mydataset.mymodel
and to overwrite a
destination model with the same name. The source dataset is in your default
project. The destination dataset is in myotherproject
. The -f
shortcut is
used to overwrite the destination model without a prompt.
mydataset
and
myotherdataset
were created in the US
multi-region
location.
bq --location=US cp -f mydataset.mymodel myotherproject:myotherdataset.mymodel
Enter the following command to copy mydataset.mymodel
and to return an error
if the destination dataset contains a model with the same name. The source
dataset is in your default project. The destination dataset is in
myotherproject
. The -n
shortcut is used to prevent overwriting a model with
the same name.
Both
datasets were created in the US
multi-region location.
bq --location=US cp -n mydataset.mymodel myotherproject:myotherdataset.mymodel
Enter the following command to copy mydataset.mymodel
to mydataset2
and
to rename the model mymodel2
. Both datasets are in your default project.
Both datasets were created in the asia-northeast1
region.
bq --location=asia-northeast1 cp mydataset.mymodel mydataset2.mymodel2
API
To copy a model by using the API, call the
bigquery.jobs.insert
method and configure a copy
job. Specify your location in the
location
property in the jobReference
section of the
job resource.
You must specify the following values in your job configuration:
"copy": { "sourceTable": { // Required "projectId": string, // Required "datasetId": string, // Required "tableId": string // Required }, "destinationTable": { // Required "projectId": string, // Required "datasetId": string, // Required "tableId": string // Required }, "createDisposition": string, // Optional "writeDisposition": string, // Optional },
Where:
sourceTable
: provides information about the model to be copied.destinationTable
: provides information about the new model.createDisposition
: specifies whether to create the model if it doesn't exist.writeDisposition
: specifies whether to overwrite an existing model.
Encrypt models
For more information about using a customer-managed encryption key (CMEK) to encrypt a model, see Use CMEK to protect BigQuery ML models.
What's next
- For an overview of BigQuery ML, see Introduction to BigQuery ML.
- To get started using BigQuery ML, see Create machine learning models in BigQuery ML.
- To learn more about working with models, see: