table

@JvmName(name = "fjetkshqlylyldni")
suspend fun table(value: Output<GooglePrivacyDlpV2BigQueryTableArgs>)
@JvmName(name = "gcdcgoyxxhdjtrtf")
suspend fun table(value: GooglePrivacyDlpV2BigQueryTableArgs?)

Parameters

value

Store findings in an existing table or a new table in an existing dataset. If table_id is not set a new one will be generated for you with the following format: dlp_googleapis_yyyy_mm_dd_dlp_job_id. Pacific time zone will be used for generating the date details. For Inspect, each column in an existing output table must have the same name, type, and mode of a field in the Finding object. For Risk, an existing output table should be the output of a previous Risk analysis job run on the same source table, with the same privacy metric and quasi-identifiers. Risk jobs that analyze the same table but compute a different privacy metric, or use different sets of quasi-identifiers, cannot store their results in the same table.


@JvmName(name = "rjvvkwxbtgqrekhc")
suspend fun table(argument: suspend GooglePrivacyDlpV2BigQueryTableArgsBuilder.() -> Unit)

Parameters

argument

Store findings in an existing table or a new table in an existing dataset. If table_id is not set a new one will be generated for you with the following format: dlp_googleapis_yyyy_mm_dd_dlp_job_id. Pacific time zone will be used for generating the date details. For Inspect, each column in an existing output table must have the same name, type, and mode of a field in the Finding object. For Risk, an existing output table should be the output of a previous Risk analysis job run on the same source table, with the same privacy metric and quasi-identifiers. Risk jobs that analyze the same table but compute a different privacy metric, or use different sets of quasi-identifiers, cannot store their results in the same table.