BigQuery Model

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A BigQuery Model in Google Cloud is a managed machine learning resource that allows users to train, store, and use ML models directly within BigQuery using SQL. It supports various model types such as linear regression, logistic regression, and boosted trees, enabling large-scale data analysis and prediction without moving data outside BigQuery.

gcp.bigquery_model

Fields

ID	Type	Data Type	Description
_key	core	string
ancestors	core	array<string>
best_trial_id	core	int64	The best trial_id across all training runs.
creation_time	core	int64	Output only. The time when this model was created, in millisecs since the epoch.
datadog_display_name	core	string
default_trial_id	core	int64	Output only. The default trial_id to use in TVFs when the trial_id is not passed in. For single-objective [hyperparameter tuning](https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) models, this is the best trial ID. For multi-objective [hyperparameter tuning](https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) models, this is the smallest trial ID among all Pareto optimal trials.
description	core	string	Optional. A user-friendly description of this model.
encryption_configuration	core	json	Custom encryption configuration (e.g., Cloud KMS keys). This shows the encryption configuration of the model data while stored in BigQuery storage. This field can be used with PatchModel to update encryption key for an already encrypted model.
etag	core	string	Output only. A hash of this resource.
expiration_time	core	int64	Optional. The time when this model expires, in milliseconds since the epoch. If not present, the model will persist indefinitely. Expired models will be deleted and their storage reclaimed. The defaultTableExpirationMs property of the encapsulating dataset can be used to set a default expirationTime on newly created models.
feature_columns	core	json	Output only. Input feature columns for the model inference. If the model is trained with TRANSFORM clause, these are the input of the TRANSFORM clause.
friendly_name	core	string	Optional. A descriptive name for this model.
hparam_search_spaces	core	json	Output only. All hyperparameter search spaces in this model.
hparam_trials	core	json	Output only. Trials of a [hyperparameter tuning](https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) model sorted by trial_id.
label_columns	core	json	Output only. Label columns that were used to train this model. The output of the model will have a "predicted_" prefix to these columns.
labels	core	array<string>	The labels associated with this model. You can use these to organize and group your models. Label keys and values can be no longer than 63 characters, can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter and each label in the list must have a different key.
last_modified_time	core	int64	Output only. The time when this model was last modified, in millisecs since the epoch.
location	core	string	Output only. The geographic location where the model resides. This value is inherited from the dataset.
model_reference	core	json	Required. Unique identifier for this model.
model_type	core	string	Output only. Type of the model resource.
optimal_trial_ids	core	array<int64>	Output only. For single-objective [hyperparameter tuning](https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) models, it only contains the best trial. For multi-objective [hyperparameter tuning](https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) models, it contains all Pareto optimal trials sorted by trial_id.
organization_id	core	string
parent	core	string
project_id	core	string
project_number	core	string
region_id	core	string
remote_model_info	core	json	Output only. Remote model info
resource_name	core	string
tags	core	hstore_csv
training_runs	core	json	Information for all training runs in increasing order of start_time.
zone_id	core	string