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variables.tf
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variables.tf
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/**
* Copyright 2023 Google LLC
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
variable "data" {
description = "The data source for DataScan. The source can be either a Dataplex `entity` or a BigQuery `resource`."
type = object({
entity = optional(string)
resource = optional(string)
})
validation {
condition = length([for k, v in var.data : v if contains(["resource", "entity"], k) && v != null]) == 1
error_message = "Datascan data must specify one of 'entity', 'resource'."
}
}
variable "data_profile_spec" {
description = "DataProfileScan related setting. Variable descriptions are provided in https://cloud.google.com/dataplex/docs/reference/rest/v1/DataProfileSpec."
default = null
type = object({
sampling_percent = optional(number)
row_filter = optional(string)
})
}
variable "data_quality_spec" {
description = "DataQualityScan related setting. Variable descriptions are provided in https://cloud.google.com/dataplex/docs/reference/rest/v1/DataQualitySpec."
default = null
type = object({
sampling_percent = optional(number)
row_filter = optional(string)
post_scan_actions = optional(object({
bigquery_export = optional(object({
results_table = optional(string)
}))
}))
rules = list(object({
column = optional(string)
ignore_null = optional(bool, null)
dimension = string
threshold = optional(number)
non_null_expectation = optional(object({}))
range_expectation = optional(object({
min_value = optional(number)
max_value = optional(number)
strict_min_enabled = optional(bool)
strict_max_enabled = optional(bool)
}))
regex_expectation = optional(object({
regex = string
}))
set_expectation = optional(object({
values = list(string)
}))
uniqueness_expectation = optional(object({}))
statistic_range_expectation = optional(object({
statistic = string
min_value = optional(number)
max_value = optional(number)
strict_min_enabled = optional(bool)
strict_max_enabled = optional(bool)
}))
row_condition_expectation = optional(object({
sql_expression = string
}))
table_condition_expectation = optional(object({
sql_expression = string
}))
sql_assertion = optional(object({
sql_statement = string
}))
}))
})
}
variable "description" {
description = "Custom description for DataScan."
default = null
type = string
}
variable "execution_schedule" {
description = "Schedule DataScan to run periodically based on a cron schedule expression. If not specified, the DataScan is created with `on_demand` schedule, which means it will not run until the user calls `dataScans.run` API."
type = string
default = null
}
variable "factories_config" {
description = "Paths to data files and folders that enable factory functionality."
type = object({
data_quality_spec = optional(string)
})
nullable = false
default = {}
}
variable "incremental_field" {
description = "The unnested field (of type Date or Timestamp) that contains values which monotonically increase over time. If not specified, a data scan will run for all data in the table."
type = string
default = null
}
variable "labels" {
description = "Resource labels."
type = map(string)
default = {}
nullable = false
}
variable "name" {
description = "Name of Dataplex Scan."
type = string
}
variable "prefix" {
description = "Optional prefix used to generate Dataplex DataScan ID."
type = string
default = null
}
variable "project_id" {
description = "The ID of the project where the Dataplex DataScan will be created."
type = string
}
variable "region" {
description = "Region for the Dataplex DataScan."
type = string
}