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"""
Example use of Teradata Compute Cluster Provision Operator
"""
from __future__ import annotations
import datetime
import os
import pytest
from airflow import DAG
from airflow.models import Param
try:
from airflow.providers.teradata.operators.teradata_compute_cluster import (
TeradataComputeClusterDecommissionOperator,
TeradataComputeClusterProvisionOperator,
TeradataComputeClusterResumeOperator,
TeradataComputeClusterSuspendOperator,
)
except ImportError:
pytest.skip("TERADATA provider not available", allow_module_level=True)
# [START teradata_vantage_lake_compute_cluster_howto_guide]
ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")
DAG_ID = "example_teradata_computer_cluster"
# The operators below build Teradata DDL by interpolating these names into SQL text.
# Object names cannot be passed as bind parameters, so anything reaching them must be
# constrained where it is declared. Params are settable by whoever triggers the Dag --
# a lower-trust role than the Dag author -- so every Param here is either restricted to
# a closed set of values (`enum`) or to an identifier shape (`pattern`).
#
# `teradata_conn_id` and `compute_attribute` are deliberately NOT Params: the first
# selects which credentials the task runs under, and the second is a free-form option
# string with no safe identifier shape. Neither belongs under trigger-time control.
TERADATA_CONN_ID = "teradata_lake"
COMPUTE_ATTRIBUTE = "MIN_COMPUTE_COUNT(1) MAX_COMPUTE_COUNT(5) INITIALLY_SUSPENDED('FALSE')"
# Unquoted Teradata object name: a letter followed by letters, digits or underscores.
OBJECT_NAME_PATTERN = "^[A-Za-z][A-Za-z0-9_]{0,127}$"
with DAG(
dag_id=DAG_ID,
start_date=datetime.datetime(2020, 2, 2),
schedule="@once",
catchup=False,
default_args={"teradata_conn_id": TERADATA_CONN_ID},
render_template_as_native_obj=True,
params={
"compute_group_name": Param(
"compute_group_test",
type="string",
pattern=OBJECT_NAME_PATTERN,
title="Compute cluster group Name:",
description="Enter compute cluster group name.",
),
"compute_profile_name": Param(
"compute_profile_test",
type="string",
pattern=OBJECT_NAME_PATTERN,
title="Compute cluster profile Name:",
description="Enter compute cluster profile name.",
),
"query_strategy": Param(
"STANDARD",
type="string",
enum=["STANDARD", "ANALYTIC"],
title="Compute cluster instance type:",
description="Enter compute cluster instance type. Valid values are STANDARD, ANALYTIC",
),
"compute_map": Param(
"TD_COMPUTE_XSMALL",
type="string",
pattern=OBJECT_NAME_PATTERN,
title="Compute Map Name:",
description="Enter compute cluster compute map name.",
),
"delete_compute_group": Param(
False,
type="boolean",
title="Delete the compute group on decommission:",
description="Whether decommissioning also deletes the compute group.",
),
"timeout": Param(
20,
type="integer",
minimum=1,
title="Timeout:",
description="Time elapsed before the task times out and fails. Timeout is in minutes.",
),
},
) as dag:
# [START teradata_vantage_lake_compute_cluster_provision_howto_guide]
compute_cluster_provision_operation = TeradataComputeClusterProvisionOperator(
task_id="compute_cluster_provision_operation",
compute_profile_name="{{ params.compute_profile_name }}",
compute_group_name="{{ params.compute_group_name }}",
teradata_conn_id=TERADATA_CONN_ID,
timeout="{{ params.timeout }}",
query_strategy="{{ params.query_strategy }}",
compute_map="{{ params.compute_map }}",
compute_attribute=COMPUTE_ATTRIBUTE,
)
# [END teradata_vantage_lake_compute_cluster_provision_howto_guide]
# [START teradata_vantage_lake_compute_cluster_suspend_howto_guide]
compute_cluster_suspend_operation = TeradataComputeClusterSuspendOperator(
task_id="compute_cluster_suspend_operation",
compute_profile_name="{{ params.compute_profile_name }}",
compute_group_name="{{ params.compute_group_name }}",
teradata_conn_id=TERADATA_CONN_ID,
timeout="{{ params.timeout }}",
)
# [END teradata_vantage_lake_compute_cluster_suspend_howto_guide]
# [START teradata_vantage_lake_compute_cluster_resume_howto_guide]
compute_cluster_resume_operation = TeradataComputeClusterResumeOperator(
task_id="compute_cluster_resume_operation",
compute_profile_name="{{ params.compute_profile_name }}",
compute_group_name="{{ params.compute_group_name }}",
teradata_conn_id=TERADATA_CONN_ID,
timeout="{{ params.timeout }}",
)
# [END teradata_vantage_lake_compute_cluster_resume_howto_guide]
# [START teradata_vantage_lake_compute_cluster_decommission_howto_guide]
compute_cluster_decommission_operation = TeradataComputeClusterDecommissionOperator(
task_id="compute_cluster_decommission_operation",
compute_profile_name="{{ params.compute_profile_name }}",
compute_group_name="{{ params.compute_group_name }}",
delete_compute_group="{{ params.delete_compute_group }}", # type: ignore[arg-type]
teradata_conn_id=TERADATA_CONN_ID,
timeout="{{ params.timeout }}",
)
# [END teradata_vantage_lake_compute_cluster_decommission_howto_guide]
(
compute_cluster_provision_operation
>> compute_cluster_suspend_operation
>> compute_cluster_resume_operation
>> compute_cluster_decommission_operation
)
# [END teradata_vantage_lake_compute_cluster_howto_guide]
from tests_common.test_utils.watcher import watcher
# This test needs watcher in order to properly mark success/failure
# when "tearDown" task with trigger rule is part of the DAG
list(dag.tasks) >> watcher()
from tests_common.test_utils.system_tests import get_test_run # noqa: E402
# Needed to run the example DAG with pytest (see: contributing-docs/testing/system_tests.rst)
test_run = get_test_run(dag)