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Add new fields supporting BQ Python UDF to bigquery_routine resource. (#15786)
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‎mmv1/products/bigquery/Routine.yaml‎

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@@ -79,6 +79,12 @@ examples:
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connection_id: 'connection_id'
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routine_id: 'routine_id'
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exclude_test: true
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- name: 'bigquery_routine_python_function'
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primary_resource_id: 'python_function'
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vars:
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dataset_id: 'dataset_id'
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routine_id: 'routine_id'
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min_version: beta
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parameters:
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properties:
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- name: 'routineReference'
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description: |
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Max number of rows in each batch sent to the remote service. If absent or if 0,
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BigQuery dynamically decides the number of rows in a batch.
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- name: 'pythonOptions'
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type: NestedObject
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description: |
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Options for a user-defined Python function.
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min_version: beta
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properties:
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- name: 'entryPoint'
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type: String
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description: |
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The name of the function defined in Python code as the entry point when the
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Python UDF is invoked.
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required: true
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- name: 'packages'
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type: Array
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description: |
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A list of Python package names along with versions to be installed.
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Example: ["pandas>=2.1", "google-cloud-translate==3.11"]. For more
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information, see [Use third-party
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packages](https://cloud.google.com/bigquery/docs/user-defined-functions-python#third-party-packages).
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item_type:
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type: String
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- name: 'externalRuntimeOptions'
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type: NestedObject
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description: |
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Options for the runtime of the external system.
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This field is only applicable for Python UDFs.
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min_version: beta
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properties:
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- name: 'containerMemory'
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type: String
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description: |
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Amount of memory provisioned for a Python UDF container instance. Format:
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{number}{unit} where unit is one of "M", "G", "Mi" and "Gi" (e.g. 1G,
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512Mi). If not specified, the default value is 512Mi. For more information,
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see [Configure container limits for Python
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UDFs](https://cloud.google.com/bigquery/docs/user-defined-functions-python#configure-container-limits)
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- name: 'containerCpu'
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type: Double
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description: |
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Amount of CPU provisioned for a Python UDF container instance. For more
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information, see [Configure container limits for Python
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UDFs](https://cloud.google.com/bigquery/docs/user-defined-functions-python#configure-container-limits)
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- name: 'runtimeConnection'
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type: String
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description: |
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Fully qualified name of the connection whose service account will be used
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to execute the code in the container. Format:
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`"projects/{project_id}/locations/{location_id}/connections/{connection_id}"`
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- name: 'maxBatchingRows'
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type: String
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description: |
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Maximum number of rows in each batch sent to the external runtime. If
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absent or if 0, BigQuery dynamically decides the number of rows in a batch.
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- name: 'runtimeVersion'
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type: String
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description: |
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Language runtime version. Example: `python-3.11`.

‎mmv1/templates/terraform/examples/bigquery_routine_python_function.tf.tmpl‎

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resource "google_bigquery_dataset" "test" {
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provider = google-beta
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dataset_id = "{{index $.Vars "dataset_id"}}"
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}
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resource "google_bigquery_routine" "{{$.PrimaryResourceId}}" {
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provider = google-beta
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dataset_id = google_bigquery_dataset.test.dataset_id
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routine_id = "{{index $.Vars "routine_id"}}"
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routine_type = "SCALAR_FUNCTION"
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language = "PYTHON"
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arguments {
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name = "x"
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data_type = "{\"typeKind\" : \"FLOAT64\"}"
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}
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arguments {
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name = "y"
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data_type = "{\"typeKind\" : \"FLOAT64\"}"
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}
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definition_body = <<-EOS
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def multiply(x, y):
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return x * y
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EOS
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return_type = "{\"typeKind\" : \"FLOAT64\"}"
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python_options {
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entry_point = "multiply"
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}
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external_runtime_options {
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container_memory = "512Mi"
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container_cpu = 0.5
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runtime_version = "python-3.11"
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}
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}

mmv1/third_party/terraform/services/bigquery/resource_bigquery_routine_test.go renamed to mmv1/third_party/terraform/services/bigquery/resource_bigquery_routine_test.go.tmpl

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@@ -5,6 +5,9 @@ import (
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"testing"
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"github.com/hashicorp/terraform-plugin-testing/helper/resource"
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{{- if ne $.TargetVersionName "ga" }}
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"github.com/hashicorp/terraform-plugin-testing/plancheck"
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{{- end }}
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"github.com/hashicorp/terraform-provider-google/google/acctest"
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)
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@@ -343,3 +346,128 @@ resource "google_bigquery_routine" "remote_function_routine" {
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}
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`, context)
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}
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{{if ne $.TargetVersionName "ga" }}
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func TestAccBigQueryRoutine_bigqueryRoutinePythonFunction_update(t *testing.T) {
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t.Parallel()
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context := map[string]interface{}{
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"random_suffix": acctest.RandString(t, 10),
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}
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acctest.VcrTest(t, resource.TestCase{
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PreCheck: func() { acctest.AccTestPreCheck(t) },
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ProtoV5ProviderFactories: acctest.ProtoV5ProviderBetaFactories(t),
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CheckDestroy: testAccCheckBigQueryRoutineDestroyProducer(t),
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Steps: []resource.TestStep{
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{
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Config: testAccBigQueryRoutine_bigqueryRoutinePythonFunction_basic(context),
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},
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{
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ResourceName: "google_bigquery_routine.python_function",
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ImportState: true,
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ImportStateVerify: true,
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},
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{
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Config: testAccBigQueryRoutine_bigqueryRoutinePythonFunction_update(context),
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ConfigPlanChecks: resource.ConfigPlanChecks{
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PreApply: []plancheck.PlanCheck{
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plancheck.ExpectResourceAction("google_bigquery_routine.python_function", plancheck.ResourceActionUpdate),
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},
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},
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},
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{
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ResourceName: "google_bigquery_routine.python_function",
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ImportState: true,
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ImportStateVerify: true,
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},
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},
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})
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}
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func testAccBigQueryRoutine_bigqueryRoutinePythonFunction_basic(context map[string]interface{}) string {
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return acctest.Nprintf(`
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resource "google_bigquery_dataset" "test" {
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provider = google-beta
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dataset_id = "tf_test_dataset_id%{random_suffix}"
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}
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resource "google_bigquery_routine" "python_function" {
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provider = google-beta
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dataset_id = google_bigquery_dataset.test.dataset_id
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routine_id = "tf_test_routine_id%{random_suffix}"
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routine_type = "SCALAR_FUNCTION"
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language = "PYTHON"
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arguments {
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name = "x"
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data_type = "{\"typeKind\" : \"FLOAT64\"}"
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}
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arguments {
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name = "y"
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data_type = "{\"typeKind\" : \"FLOAT64\"}"
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}
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definition_body = <<-EOS
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def multiply(x, y):
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return x * y
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EOS
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return_type = "{\"typeKind\" : \"FLOAT64\"}"
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python_options {
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entry_point = "multiply"
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}
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external_runtime_options {
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runtime_version = "python-3.11"
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}
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}
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`, context)
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}
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func testAccBigQueryRoutine_bigqueryRoutinePythonFunction_update(context map[string]interface{}) string {
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return acctest.Nprintf(`
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resource "google_bigquery_dataset" "test" {
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provider = google-beta
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dataset_id = "tf_test_dataset_id%{random_suffix}"
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}
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resource "google_bigquery_connection" "test" {
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provider = google-beta
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connection_id = "tf_test_connection_id%{random_suffix}"
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location = "US"
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cloud_resource {}
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}
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resource "google_bigquery_routine" "python_function" {
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provider = google-beta
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dataset_id = google_bigquery_dataset.test.dataset_id
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routine_id = "tf_test_routine_id%{random_suffix}"
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routine_type = "SCALAR_FUNCTION"
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language = "PYTHON"
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arguments {
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name = "x"
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data_type = "{\"typeKind\" : \"FLOAT64\"}"
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}
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arguments {
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name = "y"
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data_type = "{\"typeKind\" : \"FLOAT64\"}"
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}
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definition_body = <<-EOS
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def multiply(x, y):
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return x * y
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EOS
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return_type = "{\"typeKind\" : \"FLOAT64\"}"
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python_options {
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entry_point = "multiply"
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packages = ["requests"]
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}
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external_runtime_options {
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container_memory = "512Mi"
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container_cpu = 0.5
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runtime_connection = "${google_bigquery_connection.test.name}"
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runtime_version = "python-3.11"
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max_batching_rows = "10"
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}
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}
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`, context)
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}
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{{- end }}

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