Module google_api_proto::google::privacy::dlp::v2

source ·

Modules§

Structs§

Enums§

  • Attributes evaluated to determine if a schema has been modified. New values may be added at a later time.
  • Attributes evaluated to determine if a table has been modified. New values may be added at a later time.
  • Over time new types may be added. Currently VIEW, MATERIALIZED_VIEW, SNAPSHOT, and non-BigLake external tables are not supported.
  • Over time new types may be added. Currently VIEW, MATERIALIZED_VIEW, and SNAPSHOT are not supported.
  • State of the connection. New values may be added over time.
  • Deprecated and unused.
  • How frequently data profiles can be updated. New options can be added at a later time.
  • An enum to represent the various types of DLP jobs.
  • How a resource is encrypted.
  • Definitions of file type groups to scan. New types will be added to this list.
  • Parts of the APIs which use certain infoTypes.
  • Coarse-grained confidence level of how well a particular finding satisfies the criteria to match a particular infoType.
  • Type of the match which can be applied to different ways of matching, like Dictionary, regular expression and intersecting with findings of another info type.
  • Type of metadata containing the finding.
  • Bucketized nullness percentage levels. A higher level means a higher percentage of the column is null.
  • Whether a profile being created is the first generation or an update.
  • Operators available for comparing the value of fields.
  • How broadly the data in the resource has been shared. New items may be added over time. A higher number means more restricted.
  • State of a StoredInfoType version.
  • Describes functionality of a given container in its original format.
  • Enum of possible outcomes of transformations. SUCCESS if transformation and storing of transformation was successful, otherwise, reason for not transforming.
  • An enum of rules that can be used to transform a value. Can be a record suppression, or one of the transformation rules specified under PrimitiveTransformation.
  • Bucketized uniqueness score levels. A higher uniqueness score is a strong signal that the column may contain a unique identifier like user id. A low value indicates that the column contains few unique values like booleans or other classifiers.