class Google::Apis::MlV1::GoogleCloudMlV1RequestLoggingConfig
Configuration for logging request-response pairs to a BigQuery table. Online prediction requests to a model version and the responses to these requests are converted to raw strings and saved to the specified BigQuery table. Logging is constrained by [BigQuery quotas and limits](/bigquery/quotas). If your project exceeds BigQuery quotas or limits, AI Platform Prediction does not log request- response pairs, but it continues to serve predictions. If you are using [ continuous evaluation](/ml-engine/docs/continuous-evaluation/), you do not need to specify this configuration manually. Setting up continuous evaluation automatically enables logging of request-response pairs.
Attributes
Required. Fully qualified BigQuery table name in the following format: “ project_id.dataset_name.table_name” The specified table must already exist, and the “Cloud ML Service Agent” for your project must have permission to write to it. The table must have the following [schema](/bigquery/docs/schemas) : Field nameType Mode model STRING REQUIRED model_version STRING REQUIRED time TIMESTAMP REQUIRED raw_data STRING REQUIRED raw_prediction STRING NULLABLE groundtruth STRING NULLABLE Corresponds to the JSON property `bigqueryTableName` @return [String]
Percentage of requests to be logged, expressed as a fraction from 0 to 1. For example, if you want to log 10% of requests, enter `0.1`. The sampling window is the lifetime of the model version. Defaults to 0. Corresponds to the JSON property `samplingPercentage` @return [Float]
Public Class Methods
# File lib/google/apis/ml_v1/classes.rb, line 2247 def initialize(**args) update!(**args) end
Public Instance Methods
Update properties of this object
# File lib/google/apis/ml_v1/classes.rb, line 2252 def update!(**args) @bigquery_table_name = args[:bigquery_table_name] if args.key?(:bigquery_table_name) @sampling_percentage = args[:sampling_percentage] if args.key?(:sampling_percentage) end