google_cloud_pipeline_components.experimental.bigquery module

Google Cloud Pipeline Bigquery components.

google_cloud_pipeline_components.experimental.bigquery.BigqueryCreateModelJobOp()

bigquery_create_model_job Launch a BigQuery create model job and waits for it to finish.

Args:

project (str):
Required. Project to run BigQuery model creation job.

location (Optional[str]):
Location of the job to create the BigQuery model. If not set, default to US multi-region.

For more details, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location

query (str):
Required. SQL query text to execute. Only standard SQL is supported.

If query are both specified in here and in job_configuration_query, the value in here will override the other one.

query_parameters (Optional[Sequence]):
jobs.query parameters for standard SQL queries.

If query_parameters are both specified in here and in job_configuration_query, the value in here will override the other one.

job_configuration_query (Optional[dict]):
A json formatted string describing the rest of the job configuration.

For more details, see https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery

labels (Optional[dict]):
The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only containlowercase 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.

Example: { “name”: “wrench”, “mass”: “1.3kg”, “count”: “3” }.

Returns:

model (google.BQMLModel):
Describes the model which is created.

gcp_resources (str):
Serialized gcp_resources proto tracking the BigQuery job. For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.

google_cloud_pipeline_components.experimental.bigquery.BigqueryDetectAnomaliesModelJobOp()

bigquery_detect_anomalies_job Launch a BigQuery detect anomalies model job and waits for it to finish.

Args:

project (str):
Required. Project to run BigQuery model prediction job.

location (Optional[str]):
Location to run the BigQuery model prediction job. If not set, default to US multi-region. For more details, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location

model (google.BQMLModel):
Required. BigQuery ML model for prediction. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-detect-anomalies#model_name

table_name (Optional[str]):
BigQuery table id of the input table that contains the data. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-detect-anomalies#table_name

query_statement (Optional[str]):
Query statement string used to generate the data. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-detect-anomalies#query_statement

contamination (Optional[float]):
Contamination is the proportion of anomalies in the training dataset that are used to create the AUTOENCODER, KMEANS, or PCA input models. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-detect-anomalies#contamination

anomaly_prob_threshold (Optional[float]):
anomaly_prob_threshold: The ARIMA_PLUS model supports the anomaly_prob_threshold custom threshold for anomaly detection. The value of the anomaly probability at each timestamp is calculated using the actual time-series data value and the values of the predicted time-series data and the variance from the model training. The actual time-series data value at a specific timestamp is identified as anomalous if the anomaly probability exceeds the anomaly_prob_threshold value. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-detect-anomalies#anomaly_prob_threshold

query_parameters (Optional[Sequence]):
jobs.query parameters for standard SQL queries. If query_parameters are both specified in here and in job_configuration_query, the value in here will override the other one.

job_configuration_query (Optional[dict]):
A json formatted string describing the rest of the job configuration. For more details, see https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery

labels (Optional[dict]):
The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only containlowercase 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.

Example: { “name”: “wrench”, “mass”: “1.3kg”, “count”: “3” }.

encryption_spec_key_name(Optional[List[str]]):
Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key. If encryption_spec_key_name are both specified in here and in job_configuration_query, the value in here will override the other one.

Returns:

destination_table (google.BQTable):
Describes the table where the model prediction results should be stored. This property must be set for large results that exceed the maximum response size. For queries that produce anonymous (cached) results, this field will be populated by BigQuery.

gcp_resources (str):
Serialized gcp_resources proto tracking the BigQuery job. For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.

google_cloud_pipeline_components.experimental.bigquery.BigqueryDropModelJobOp()

bigquery_drop_model_job Launch a BigQuery drop model job and waits for it to finish.

Args:

project (str):
Required. Project to run BigQuery model drop job.

location (Optional[str]):
Location of the job to drop the BigQuery model. If not set, default to US multi-region.

For more details, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location

model (google.BQMLModel):
Required. BigQuery ML model to drop.

query_parameters (Optional[Sequence]):
jobs.query parameters for standard SQL queries. If query_parameters are both specified in here and in job_configuration_query, the value in here will override the other one.

job_configuration_query (Optional[dict]):
A json formatted string describing the rest of the job configuration. For more details, see https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery

labels (Optional[dict]):
The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only containlowercase 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. Example: { “name”: “wrench”, “mass”: “1.3kg”, “count”: “3” }.

encryption_spec_key_name(Optional[List[str]]):
Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key. If encryption_spec_key_name are both specified in here and in job_configuration_query, the value in here will override the other one.

Returns:

gcp_resources (str):
Serialized gcp_resources proto tracking the BigQuery job. For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.

google_cloud_pipeline_components.experimental.bigquery.BigqueryEvaluateModelJobOp()

bigquery_evaluate_model_job Launch a BigQuery evaluate model job and waits for it to finish.

Args:

project (str):
Required. Project to run BigQuery model evaluation job.

location (Optional[str]):
Location to run the BigQuery model evaluation job. If not set, default to US multi-region. For more details, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location

model (google.BQMLModel):
Required. BigQuery ML model for evaluation. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-predict#predict_model_name

table_name (Optional[str]):
BigQuery table id of the input table that contains the evaluation data. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-predict#predict_table_name

query_statement (Optional[str]):
Query statement string used to generate the evaluation data. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-predict#predict_query_statement

threshold (Optional[float]):
A custom threshold for the binary logistic regression model used as the cutoff between two labels. Predictions above the threshold are treated as positive prediction. Predictions below the threshold are negative predictions. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-predict#threshold

query_parameters (Optional[Sequence]):
jobs.query parameters for standard SQL queries. If query_parameters are both specified in here and in job_configuration_query, the value in here will override the other one.

job_configuration_query (Optional[dict]):
A json formatted string describing the rest of the job configuration. For more details, see https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery

labels (Optional[dict]):
The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only containlowercase 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. Example: { “name”: “wrench”, “mass”: “1.3kg”, “count”: “3” }.

encryption_spec_key_name(Optional[List[str]]):
Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key. If encryption_spec_key_name are both specified in here and in job_configuration_query, the value in here will override the other one.

Returns:

evaluation_metrics (system.Artifact):
Describes common metrics applicable to the type of model supplied. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-evaluate#mlevaluate_output

gcp_resources (str):
Serialized gcp_resources proto tracking the BigQuery job. For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.

google_cloud_pipeline_components.experimental.bigquery.BigqueryExplainForecastModelJobOp()

bigquery_explain_forecast_model_job Launch a BigQuery ML.EXPLAIN_FORECAST job and let you explain forecast an ARIMA_PLUS or ARIMA model. This function only applies to the time-series ARIMA_PLUS and ARIMA models.

Args:

project (str):
Required. Project to run the BigQuery job.

location (Optional[str]):
Location to run the BigQuery job. If not set, default to US multi-region. For more details, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location

model (google.BQMLModel):
Required. BigQuery ML model for ML.EXPLAIN_FORECAST. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-explain-forecast

horizon (Optional[int]): Horizon is the number of time points to explain forecast. For more
details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-explain-forecast#horizon

confidence_level (Optional[float]): The percentage of the future values that fall in the
prediction interval. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-explain-forecast#confidence_level

query_parameters (Optional[Sequence]):
jobs.query parameters for standard SQL queries. If query_parameters are both specified in here and in job_configuration_query, the value in here will override the other one.

job_configuration_query (Optional[dict]):
A json formatted string describing the rest of the job configuration. For more details, see https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery

labels (Optional[dict]):
The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only containlowercase 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.

Example: { “name”: “wrench”, “mass”: “1.3kg”, “count”: “3” }.

encryption_spec_key_name(Optional[List[str]]):
Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key. If encryption_spec_key_name are both specified in here and in job_configuration_query, the value in here will override the other one.

Returns:

destination_table (google.BQTable):
Describes the table where the model explain forecast results should be stored. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-explain-forecast#mlexplain_forecast_output

gcp_resources (str):
Serialized gcp_resources proto tracking the BigQuery job. For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.

google_cloud_pipeline_components.experimental.bigquery.BigqueryExplainPredictModelJobOp()

bigquery_explain_predict_model_job Launch a BigQuery explain predict model job and waits for it to finish.

Args:

project (str):
Required. Project to run BigQuery model prediction job.

location (Optional[str]):
Location to run the BigQuery model prediction job. If not set, default to US multi-region. For more details, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location

model (google.BQMLModel):
Required. BigQuery ML model for explaining prediction. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-explain-predict#model_name

table_name (Optional[str]):
BigQuery table id of the input table that contains the prediction data. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-explain-predict#table_name

query_statement (Optional[str]):
Query statement string used to generate the prediction data. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-explain-predict#query_statement

top_k_features (Optional[int]): This argument specifies how many top feature attribution
pairs are generated per row of input data. The features are ranked by the absolute values of their attributions. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-explain-predict#top_k_features

threshold (Optional[float]):
A custom threshold for the binary logistic regression model used as the cutoff between two labels. Predictions above the threshold are treated as positive prediction. Predictions below the threshold are negative predictions. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-predict#threshold

num_integral_steps (Optional[int]): This argument specifies the number of steps to sample
between the example being explained and its baseline for approximating the integral in integrated gradients attribution methods. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-explain-predict#num_integral_steps

query_parameters (Optional[Sequence]):
jobs.query parameters for standard SQL queries. If query_parameters are both specified in here and in job_configuration_query, the value in here will override the other one.

job_configuration_query (Optional[dict]):
A json formatted string describing the rest of the job configuration. For more details, see https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery

labels (Optional[dict]):
The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only containlowercase 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. Example: { “name”: “wrench”, “mass”: “1.3kg”, “count”: “3” }.

encryption_spec_key_name(Optional[List[str]]):
Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key. If encryption_spec_key_name are both specified in here and in job_configuration_query, the value in here will override the other one.

Returns:

destination_table (google.BQTable):
Describes the table where the model prediction results should be stored. This property must be set for large results that exceed the maximum response size. For queries that produce anonymous (cached) results, this field will be populated by BigQuery.

gcp_resources (str):
Serialized gcp_resources proto tracking the BigQuery job. For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.

google_cloud_pipeline_components.experimental.bigquery.BigqueryExportModelJobOp()

bigquery_export_model_job Launch a BigQuery export model job and waits for it to finish.

Args:

project (str):
Required. Project to run BigQuery model export job.

location (Optional[str]):
Location of the job to export the BigQuery model. If not set, default to US multi-region.

For more details, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location

model (google.BQMLModel):
Required. BigQuery ML model to export.

model_destination_path(str):
Required. The gcs bucket to export the model to.

job_configuration_extract (Optional[dict]):
A json formatted string describing the rest of the job configuration.

For more details, see https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery

labels (Optional[dict]):
The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only containlowercase 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.

Example: { “name”: “wrench”, “mass”: “1.3kg”, “count”: “3” }.

Returns:

gcp_resources (str):
Serialized gcp_resources proto tracking the BigQuery job. For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.

google_cloud_pipeline_components.experimental.bigquery.BigqueryForecastModelJobOp()

bigquery_forecast_model_job Launch a BigQuery ML.FORECAST job and let you forecast an ARIMA_PLUS or ARIMA model. This function only applies to the time-series ARIMA_PLUS and ARIMA models.

Args:

project (str):
Required. Project to run the BigQuery job.

location (Optional[str]):
Location to run the BigQuery job. If not set, default to US multi-region. For more details, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location

model (google.BQMLModel):
Required. BigQuery ML model for ML.FORECAST. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-forecast

horizon (Optional[int]): Horizon is the number of time points to forecast. For more
details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-forecast#horizon

confidence_level (Optional[float]): The percentage of the future values that fall in the
prediction interval. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-forecast#confidence_level

query_parameters (Optional[Sequence]):
jobs.query parameters for standard SQL queries. If query_parameters are both specified in here and in job_configuration_query, the value in here will override the other one.

job_configuration_query (Optional[dict]):
A json formatted string describing the rest of the job configuration. For more details, see https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery

labels (Optional[dict]):
The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only containlowercase 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.

Example: { “name”: “wrench”, “mass”: “1.3kg”, “count”: “3” }.

encryption_spec_key_name(Optional[List[str]]):
Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key. If encryption_spec_key_name are both specified in here and in job_configuration_query, the value in here will override the other one.

Returns:

destination_table (google.BQTable):
Describes the table where the model forecast results should be stored. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-forecast#mlforecast_output

gcp_resources (str):
Serialized gcp_resources proto tracking the BigQuery job. For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.

google_cloud_pipeline_components.experimental.bigquery.BigqueryMLAdvancedWeightsJobOp()

bigquery_ml_advanced_weights_job Launch a BigQuery ml advanced weights job and waits for it to finish.

Args:

project (str):
Required. Project to run BigQuery ml advanced weights job.

location (Optional[str]):
Location of the job to create the BigQuery model. If not set, default to US multi-region.

For more details, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location

query (str):
Required. SQL query text to execute. Only standard SQL is supported.

If query are both specified in here and in job_configuration_query, the value in here will override the other one.

query_parameters (Optional[Sequence]):
jobs.query parameters for standard SQL queries.

If query_parameters are both specified in here and in job_configuration_query, the value in here will override the other one.

job_configuration_query (Optional[dict]):
A json formatted string describing the rest of the job configuration.

For more details, see https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery

labels (Optional[dict]):
The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only containlowercase 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.

Example: { “name”: “wrench”, “mass”: “1.3kg”, “count”: “3” }.

Returns:

weights (system.Artifact):
Describes different output columns for different models. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-advanced-weights#mladvanced_weights_output.

gcp_resources (str):
Serialized gcp_resources proto tracking the BigQuery job. For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.

google_cloud_pipeline_components.experimental.bigquery.BigqueryMLArimaCoefficientsJobOp(project: str, model: google.BQMLModel, location: str = 'us-central1', query_parameters: list = '[]', job_configuration_query: dict = '{}', labels: list = '[]', encryption_spec_key_name: str = None)

bigquery_ml_arima_coefficients Launch a BigQuery ML.ARIMA_COEFFICIENTS job and let you see the ARIMA coefficients. This function only applies to the time-series ARIMA_PLUS and ARIMA models.

Args:

project (str):
Required. Project to run the BigQuery job.

location (Optional[str]):
Location to run the BigQuery job. If not set, default to US multi-region. For more details, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location

model (google.BQMLModel):
Required. BigQuery ML model for ML.ARIMA_COEFFICIENTS. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-arima-coefficients

query_parameters (Optional[Sequence]):
jobs.query parameters for standard SQL queries. If query_parameters are both specified in here and in job_configuration_query, the value in here will override the other one.

job_configuration_query (Optional[dict]):
A json formatted string describing the rest of the job configuration. For more details, see https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery

encryption_spec_key_name(Optional[List[str]]):
Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key. If encryption_spec_key_name are both specified in here and in job_configuration_query, the value in here will override the other one.

Returns:

arima_coefficients (system.Artifact):
Describes arima_coefficients to the type of model supplied. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-arima-coefficients#mlarima_coefficients_output

gcp_resources (str):
Serialized gcp_resources proto tracking the BigQuery job. For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.

google_cloud_pipeline_components.experimental.bigquery.BigqueryMLArimaEvaluateJobOp()

bigquery_ml_arima_evaluate_job Launch a BigQuery ML.ARIMA_EVALUATE job and waits for it to finish.

Args:

project (str):
Required. Project to run BigQuery model evaluation job.

location (Optional[str]):
Location to run the BigQuery model evaluation job. If not set, default to US multi-region. For more details, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location

model (google.BQMLModel):
Required. BigQuery ML model for ML.ARIMA_EVALUATE. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-arima-evaluate#model_name

show_all_candidate_models (Optional[bool]):
You can use show_all_candidate_models to show evaluation metrics or an error message for either all candidate models or for only the best model with the lowest AIC. The value is type BOOL and is part of the settings STRUCT. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-arima-evaluate#show_all_candidate_models

query_parameters (Optional[Sequence]):
jobs.query parameters for standard SQL queries. If query_parameters are both specified in here and in job_configuration_query, the value in here will override the other one.

job_configuration_query (Optional[dict]):
A json formatted string describing the rest of the job configuration. For more details, see https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery

labels (Optional[dict]):
The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only containlowercase 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. Example: { “name”: “wrench”, “mass”: “1.3kg”, “count”: “3” }.

encryption_spec_key_name(Optional[List[str]]):
Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key. If encryption_spec_key_name are both specified in here and in job_configuration_query, the value in here will override the other one.

Returns:

arima_evaluation_metrics (system.Artifact):
Describes arima metrics. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-arima-evaluate#mlarima_evaluate_output

gcp_resources (str):
Serialized gcp_resources proto tracking the BigQuery job. For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.

google_cloud_pipeline_components.experimental.bigquery.BigqueryMLCentroidsJobOp()

bigquery_ml_centroids_job Launch a BigQuery ML.CENTROIDS job and waits for it to finish.

Args:

project (str):
Required. Project to run BigQuery ML.CENTROIDS job.

location (Optional[str]):
Location to run the BigQuery ML.CENTROIDS job. If not set, default to US multi-region. For more details, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location

model (google.BQMLModel):
Required. BigQuery ML model for ML.CENTROIDS. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-centroids#mlcentroids_syntax

standardize (Optional[bool]):
Determines whether the centroid features should be standardized to assume that all features have a mean of zero and a standard deviation of one. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-centroids#mlcentroids_syntax

query_parameters (Optional[Sequence]):
jobs.query parameters for standard SQL queries. If query_parameters are both specified in here and in job_configuration_query, the value in here will override the other one.

job_configuration_query (Optional[dict]):
A json formatted string describing the rest of the job configuration. For more details, see https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery

labels (Optional[dict]):
The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only containlowercase 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. Example: { “name”: “wrench”, “mass”: “1.3kg”, “count”: “3” }.

encryption_spec_key_name(Optional[List[str]]):
Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key. If encryption_spec_key_name are both specified in here and in job_configuration_query, the value in here will override the other one.

Returns:

centroids (system.Artifact):
Information about the centroids in a k-means model. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-centroids#mlcentroids_output

gcp_resources (str):
Serialized gcp_resources proto tracking the BigQuery job. For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.

google_cloud_pipeline_components.experimental.bigquery.BigqueryMLConfusionMatrixJobOp()

bigquery_ml_confusion_matrix_job Launch a BigQuery confusion matrix job and waits for it to finish.

Args:

project (str):
Required. Project to run BigQuery confusion matrix job.

location (Optional[str]):
Location to run the BigQuery confusion matrix job. If not set, default to US multi-region. For more details, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location

model (google.BQMLModel):
Required. BigQuery ML model for confusion matrix. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-confusion#eval_model_name

table_name (Optional[str]):
BigQuery table id of the input table that contains the evaluation data. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-confusion#eval_table_name

query_statement (Optional[str]):
Query statement string used to generate the evaluation data. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-confusion#eval_query_statement

threshold (Optional[float]):
A custom threshold for your binary classification model used for evaluation. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-confusion#eval_threshold

query_parameters (Optional[Sequence]):
jobs.query parameters for standard SQL queries. If query_parameters are both specified in here and in job_configuration_query, the value in here will override the other one.

job_configuration_query (Optional[dict]):
A json formatted string describing the rest of the job configuration. For more details, see https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery

labels (Optional[dict]):
The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only containlowercase 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. Example: { “name”: “wrench”, “mass”: “1.3kg”, “count”: “3” }.

Returns:

confusion_matrix (system.Artifact):
Describes common metrics applicable to the type of model supplied. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-confusion#mlconfusion_matrix_output

gcp_resources (str):
Serialized gcp_resources proto tracking the BigQuery job. For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.

google_cloud_pipeline_components.experimental.bigquery.BigqueryMLFeatureImportanceJobOp()

bigquery_ml_feature_importance_job Launch a BigQuery feature importance fetching job and waits for it to finish.

Args:

project (str):
Required. Project to run BigQuery model creation job.

location (Optional[str]):
Location of the job to create the BigQuery model. If not set, default to US multi-region. For more details, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location

model (google.BQMLModel):
Required. BigQuery ML model for feature importance. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-predict#predict_model_name

query_parameters (Optional[Sequence]):
jobs.query parameters for standard SQL queries. If query_parameters are both specified in here and in job_configuration_query, the value in here will override the other one.

job_configuration_query (Optional[dict]):
A json formatted string describing the rest of the job configuration.

For more details, see https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery

Returns:

feature_importance (system.Artifact):
Describes common metrics applicable to the type of model supplied. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-importance

gcp_resources (str):
Serialized gcp_resources proto tracking the BigQuery job. For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.

google_cloud_pipeline_components.experimental.bigquery.BigqueryMLFeatureInfoJobOp()

bigquery_ml_feature_info_job Launch a BigQuery feature info job and waits for it to finish.

Args:

project (str):
Required. Project to run BigQuery feature info job.

location (Optional[str]):
Location of the job to run BigQuery feature info job. If not set, default to US multi-region.

For more details, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location

model (google.BQMLModel):
Required. BigQuery ML model for evaluation. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-predict#predict_model_name

query_parameters (Optional[Sequence]):
jobs.query parameters for standard SQL queries.

If query_parameters are both specified in here and in job_configuration_query, the value in here will override the other one.

job_configuration_query (Optional[dict]):
A json formatted string describing the rest of the job configuration.

For more details, see https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery

labels (Optional[dict]):
The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only containlowercase 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.

Example: { “name”: “wrench”, “mass”: “1.3kg”, “count”: “3” }.

Returns:

feature_info (system.Artifact):
Describes common metrics applicable to the type of model supplied. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-feature#mlfeature_info_output

gcp_resources (str):
Serialized gcp_resources proto tracking the BigQuery job. For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.

google_cloud_pipeline_components.experimental.bigquery.BigqueryMLGlobalExplainJobOp(project: str, model: google.BQMLModel, location: str = 'us-central1', class_level_explain: bool = False, query_parameters: list = '[]', job_configuration_query: dict = '{}', labels: dict = '{}', encryption_spec_key_name: str = None)

bigquery_ml_global_explain_job Launch a BigQuery global explain fetching job and waits for it to finish.

Args:

project (str):
Required. Project to run BigQuery model creation job.

location (Optional[str]):
Location of the job to create the BigQuery model. If not set, default to US multi-region.

For more details, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location

model (google.BQMLModel):
Required. BigQuery ML model for global explain. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-predict#predict_model_name

class_level_explain (Optional[bool])
Optional. For classification models, if class_level_explain is set to TRUE then global feature importances are returned for each class. Otherwise, the global feature importance of the entire model is returned rather than that of each class. By default, class_level_explain is set to FALSE. This option only applies to classification models. Regression models only have model-level global feature importance.

Returns:

destination_table (google.BQTable):
Describes the table where the global explain results should be stored.

gcp_resources (str):
Serialized gcp_resources proto tracking the BigQuery job. For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.

google_cloud_pipeline_components.experimental.bigquery.BigqueryMLPrincipalComponentInfoJobOp()

bigquery_ml_principal_component_info_job Launch a BigQuery ML.principal_component_info job and waits for it to finish.

Args:

project (str):
Required. Project to run BigQuery ML.principal_component_info job.

location (Optional[str]):
Location to run the BigQuery ML.principal_component_info job. If not set, default to US multi-region. For more details, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location

model (google.BQMLModel):
Required. BigQuery ML model for ML.principal_component_info. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-principal-component-info#mlprincipal_component_info_syntax

query_parameters (Optional[Sequence]):
jobs.query parameters for standard SQL queries. If query_parameters are both specified in here and in job_configuration_query, the value in here will override the other one.

job_configuration_query (Optional[dict]):
A json formatted string describing the rest of the job configuration. For more details, see https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery

labels (Optional[dict]):
The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only containlowercase 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. Example: { “name”: “wrench”, “mass”: “1.3kg”, “count”: “3” }.

encryption_spec_key_name(Optional[List[str]]):
Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key. If encryption_spec_key_name are both specified in here and in job_configuration_query, the value in here will override the other one.

Returns:

destination_table (google.BQTable):
Describes the table which stores common metrics applicable to the type of model supplied. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-principal-component-info#mlprincipal_component_info_output

gcp_resources (str):
Serialized gcp_resources proto tracking the BigQuery job. For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.

google_cloud_pipeline_components.experimental.bigquery.BigqueryMLPrincipalComponentsJobOp()

bigquery_ml_principal_components_job Launch a BigQuery ML.principal_components job and waits for it to finish.

Args:

project (str):
Required. Project to run BigQuery ML.principal_components job.

location (Optional[str]):
Location to run the BigQuery ML.principal_components job. If not set, default to US multi-region. For more details, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location

model (google.BQMLModel):
Required. BigQuery ML model for ML.principal_components. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-principal-components#mlprincipal_components_syntax

query_parameters (Optional[Sequence]):
jobs.query parameters for standard SQL queries. If query_parameters are both specified in here and in job_configuration_query, the value in here will override the other one.

job_configuration_query (Optional[dict]):
A json formatted string describing the rest of the job configuration. For more details, see https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery

labels (Optional[dict]):
The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only containlowercase 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. Example: { “name”: “wrench”, “mass”: “1.3kg”, “count”: “3” }.

encryption_spec_key_name(Optional[List[str]]):
Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key. If encryption_spec_key_name are both specified in here and in job_configuration_query, the value in here will override the other one.

Returns:

destination_table (google.BQTable):
Describes the table which stores common metrics applicable to the type of model supplied. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-principal-components#mlprincipal_components_output

gcp_resources (str):
Serialized gcp_resources proto tracking the BigQuery job. For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.

google_cloud_pipeline_components.experimental.bigquery.BigqueryMLRecommendJobOp()

bigquery_ml_recommend_job Launch a BigQuery ML.Recommend job and waits for it to finish.

Args:

project (str):
Required. Project to run BigQuery ML.Recommend job.

location (Optional[str]):
Location to run the BigQuery ML.Recommend job. If not set, default to US multi-region. For more details, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location

model (google.BQMLModel):
Required. BigQuery ML model for ML.Recoomend. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-recommend#recommend_model_name

table_name (Optional[str]):
BigQuery table id of the input table that contains the the user and/or item data. For more details, see

https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-recommend#recommend_table_name query_statement (Optional[str]):

query statement string used to generate the evaluation data. For more details, see

https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-recommend#recommend_query_statement query_parameters (Optional[Sequence]):

jobs.query parameters for standard SQL queries. If query_parameters are both specified in here and in job_configuration_query, the value in here will override the other one.

job_configuration_query (Optional[dict]):
A json formatted string describing the rest of the job configuration. For more details, see https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery

labels (Optional[dict]):
The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only containlowercase 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. Example: { “name”: “wrench”, “mass”: “1.3kg”, “count”: “3” }.

encryption_spec_key_name(Optional[List[str]]):
Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key. If encryption_spec_key_name are both specified in here and in job_configuration_query, the value in here will override the other one.

Returns:

destination_table (google.BQTable):
Describes the table where the recommendation results should be stored. This property must be set for large results that exceed the maximum response size. For queries that produce anonymous (cached) results, this field will be populated by BigQuery.

gcp_resources (str):
Serialized gcp_resources proto tracking the BigQuery job. For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.

google_cloud_pipeline_components.experimental.bigquery.BigqueryMLReconstructionLossJobOp()

bigquery_ml_reconstruction_loss_job Launch a BigQuery ml reconstruction loss job and waits for it to finish.

Args:

project (str):
Required. Project to run BigQuery ml reconstruction loss job.

location (Optional[str]):
Location to run the BigQuery ml reconstruction loss job. If not set, default to US multi-region. For more details, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location

model (google.BQMLModel):
Required. BigQuery ML model. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-reconstruction-loss#reconstruction_loss_model_name

table_name (Optional[str]):
BigQuery table id of the input table that contains the input data. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-reconstruction-loss#reconstruction_loss_table_name

query_statement (Optional[str]):
Query statement string used to generate the input data. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-reconstruction-loss#reconstruction_loss_query_statement

query_parameters (Optional[Sequence]):
jobs.query parameters for standard SQL queries. If query_parameters are both specified in here and in job_configuration_query, the value in here will override the other one.

job_configuration_query (Optional[dict]):
A json formatted string describing the rest of the job configuration. For more details, see https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery

labels (Optional[dict]):
The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only containlowercase 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. Example: { “name”: “wrench”, “mass”: “1.3kg”, “count”: “3” }.

encryption_spec_key_name(Optional[List[str]]):
Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key. If encryption_spec_key_name are both specified in here and in job_configuration_query, the value in here will override the other one.

Returns:

destination_table (google.BQTable):
Describes the table where the ml reconstruction loss job results should be stored. This property must be set for large results that exceed the maximum response size. For queries that produce anonymous (cached) results, this field will be populated by BigQuery.

gcp_resources (str):
Serialized gcp_resources proto tracking the BigQuery job. For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.

google_cloud_pipeline_components.experimental.bigquery.BigqueryMLRocCurveJobOp()

bigquery_ml_roc_curve_job Launch a BigQuery roc curve job and waits for it to finish.

Args:

project (str):
Required. Project to run BigQuery roc curve job.

location (Optional[str]):
Location of the job to run BigQuery roc curve job. If not set, default to US multi-region.

For more details, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location

model (google.BQMLModel):
Required. BigQuery ML model for BigQuery roc curv job. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-roc#roc_model_name

table_name (Optional[str]):
BigQuery table id of the input table that contains the evaluation data. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-roc#roc_table_name

query_statement (Optional[str]):
Query statement string used to generate the evaluation data. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-roc#roc_query_statement

thresholds (Optional[str]):
Percentile values of the prediction output. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-roc#roc_thresholds

query_parameters (Optional[Sequence]):
jobs.query parameters for standard SQL queries. If query_parameters are both specified in here and in job_configuration_query, the value in here will override the other one.

job_configuration_query (Optional[dict]):
A json formatted string describing the rest of the job configuration. For more details, see https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery

labels (Optional[dict]):
The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only containlowercase 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. Example: { “name”: “wrench”, “mass”: “1.3kg”, “count”: “3” }.

Returns:

roc_curve (system.Artifact):
Describes common metrics applicable to the type of model supplied. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-roc#mlroc_curve_output

gcp_resources (str):
Serialized gcp_resources proto tracking the BigQuery job. For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.

google_cloud_pipeline_components.experimental.bigquery.BigqueryMLTrainingInfoJobOp()

bigquery_ml_training_info_job Launch a BigQuery ml training info fetching job and waits for it to finish.

Args:

project (str):
Required. Project to run BigQuery ML training info job.

location (Optional[str]):
Location of the job to create the BigQuery model. If not set, default to US multi-region.

For more details, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location

query (str):
Required. SQL query text to execute. Only standard SQL is supported.

If query are both specified in here and in job_configuration_query, the value in here will override the other one.

query_parameters (Optional[Sequence]):
jobs.query parameters for standard SQL queries.

If query_parameters are both specified in here and in job_configuration_query, the value in here will override the other one.

job_configuration_query (Optional[dict]):
A json formatted string describing the rest of the job configuration.

For more details, see https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery

labels (Optional[dict]):
The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only containlowercase 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.

Example: { “name”: “wrench”, “mass”: “1.3kg”, “count”: “3” }.

Returns:

ml_training_info (system.Artifact):
Describes common metrics applicable to the type of model supplied. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-evaluate#mlevaluate_output

gcp_resources (str):
Serialized gcp_resources proto tracking the BigQuery job. For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.

google_cloud_pipeline_components.experimental.bigquery.BigqueryMLTrialInfoJobOp()

bigquery_ml_trial_info_job Launch a BigQuery ml trial info job and waits for it to finish.

Args:

project (str):
Required. Project to run BigQuery ml trial info job.

location (Optional[str]):
Location to run the BigQuery ml trial info job. If not set, default to US multi-region. For more details, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location

model (google.BQMLModel):
Required. BigQuery ML model. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-trial-info#predict_model_name

query_parameters (Optional[Sequence]):
jobs.query parameters for standard SQL queries. If query_parameters are both specified in here and in job_configuration_query, the value in here will override the other one.

job_configuration_query (Optional[dict]):
A json formatted string describing the rest of the job configuration. For more details, see https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery

labels (Optional[dict]):
The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only containlowercase 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. Example: { “name”: “wrench”, “mass”: “1.3kg”, “count”: “3” }.

encryption_spec_key_name(Optional[List[str]]):
Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key. If encryption_spec_key_name are both specified in here and in job_configuration_query, the value in here will override the other one.

Returns:

trial_info (system.Artifact):
Describes the trial info applicable to the type of model supplied. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-trial-info

gcp_resources (str):
Serialized gcp_resources proto tracking the BigQuery job. For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.

google_cloud_pipeline_components.experimental.bigquery.BigqueryMLWeightsJobOp()

bigquery_ml_weights_job Launch a BigQuery ml weights job and waits for it to finish.

Args:

project (str):
Required. Project to run BigQuery ml weights job.

location (Optional[str]):
Location of the job to create the BigQuery model. If not set, default to US multi-region.

For more details, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location

query (str):
Required. SQL query text to execute. Only standard SQL is supported.

If query are both specified in here and in job_configuration_query, the value in here will override the other one.

query_parameters (Optional[Sequence]):
jobs.query parameters for standard SQL queries.

If query_parameters are both specified in here and in job_configuration_query, the value in here will override the other one.

job_configuration_query (Optional[dict]):
A json formatted string describing the rest of the job configuration.

For more details, see https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery

labels (Optional[dict]):
The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only containlowercase 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.

Example: { “name”: “wrench”, “mass”: “1.3kg”, “count”: “3” }.

Returns:

weights (system.Artifact):
Describes different output columns for different models. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-weights#mlweights_output.

gcp_resources (str):
Serialized gcp_resources proto tracking the BigQuery job. For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.

google_cloud_pipeline_components.experimental.bigquery.BigqueryPredictModelJobOp()

bigquery_predict_model_job Launch a BigQuery predict model job and waits for it to finish.

Args:

project (str):
Required. Project to run BigQuery model prediction job.

location (Optional[str]):
Location to run the BigQuery model prediction job. If not set, default to US multi-region. For more details, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location

model (google.BQMLModel):
Required. BigQuery ML model for prediction. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-predict#predict_model_name

table_name (Optional[str]):
BigQuery table id of the input table that contains the prediction data. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-predict#predict_table_name

query_statement (Optional[str]):
Query statement string used to generate the prediction data. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-predict#predict_query_statement

threshold (Optional[float]):
A custom threshold for the binary logistic regression model used as the cutoff between two labels. Predictions above the threshold are treated as positive prediction. Predictions below the threshold are negative predictions. For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-predict#threshold

query_parameters (Optional[Sequence]):
jobs.query parameters for standard SQL queries. If query_parameters are both specified in here and in job_configuration_query, the value in here will override the other one.

job_configuration_query (Optional[dict]):
A json formatted string describing the rest of the job configuration. For more details, see https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery

labels (Optional[dict]):
The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only containlowercase 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. Example: { “name”: “wrench”, “mass”: “1.3kg”, “count”: “3” }.

encryption_spec_key_name(Optional[List[str]]):
Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key. If encryption_spec_key_name are both specified in here and in job_configuration_query, the value in here will override the other one.

Returns:

destination_table (google.BQTable):
Describes the table where the model prediction results should be stored. This property must be set for large results that exceed the maximum response size. For queries that produce anonymous (cached) results, this field will be populated by BigQuery.

gcp_resources (str):
Serialized gcp_resources proto tracking the BigQuery job. For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.

google_cloud_pipeline_components.experimental.bigquery.BigqueryQueryJobOp()

bigquery_query_job Launch a BigQuery query job and waits for it to finish.

Args:

project (str):
Required. Project to run the BigQuery query job.

location (Optional[str]):
Location for creating the BigQuery job. If not set, default to US multi-region.

For more details, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location

query (str):
Required. SQL query text to execute. Only standard SQL is supported.

If query are both specified in here and in job_configuration_query, the value in here will override the other one.

query_parameters (Optional[Sequence]):
jobs.query parameters for standard SQL queries.

If query_parameters are both specified in here and in job_configuration_query, the value in here will override the other one.

job_configuration_query (Optional[dict]):
A json formatted string describing the rest of the job configuration.

For more details, see https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery

labels (Optional[dict]):
The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only containlowercase 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.

Example: { “name”: “wrench”, “mass”: “1.3kg”, “count”: “3” }.

encryption_spec_key_name(Optional[List[str]]):
Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key.

If encryption_spec_key_name are both specified in here and in job_configuration_query, the value in here will override the other one.

Returns:

destination_table (google.BQTable):
Describes the table where the query results should be stored. This property must be set for large results that exceed the maximum response size. For queries that produce anonymous (cached) results, this field will be populated by BigQuery.

gcp_resources (str):
Serialized gcp_resources proto tracking the BigQuery job. For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.