Source code for tests.system.providers.google.cloud.bigtable.example_bigtable

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"""
Example Airflow DAG that creates and performs following operations on Cloud Bigtable:
- creates an Instance
- creates a Table
- updates Cluster
- waits for Table replication completeness
- deletes the Table
- deletes the Instance

This DAG relies on the following environment variables:

* GCP_PROJECT_ID - Google Cloud project
* CBT_INSTANCE_ID - desired ID of a Cloud Bigtable instance
* CBT_INSTANCE_DISPLAY_NAME - desired human-readable display name of the Instance
* CBT_INSTANCE_TYPE - type of the Instance, e.g. 1 for DEVELOPMENT
    See https://googleapis.github.io/google-cloud-python/latest/bigtable/instance.html#google.cloud.bigtable.instance.Instance
* CBT_INSTANCE_LABELS - labels to add for the Instance
* CBT_CLUSTER_ID - desired ID of the main Cluster created for the Instance
* CBT_CLUSTER_ZONE - zone in which main Cluster will be created. e.g. europe-west1-b
    See available zones: https://cloud.google.com/bigtable/docs/locations
* CBT_CLUSTER_NODES - initial amount of nodes of the Cluster
* CBT_CLUSTER_NODES_UPDATED - amount of nodes for BigtableClusterUpdateOperator
* CBT_CLUSTER_STORAGE_TYPE - storage for the Cluster, e.g. 1 for SSD
    See https://googleapis.github.io/google-cloud-python/latest/bigtable/instance.html#google.cloud.bigtable.instance.Instance.cluster
* CBT_TABLE_ID - desired ID of the Table
* CBT_POKE_INTERVAL - number of seconds between every attempt of Sensor check
"""
from __future__ import annotations

import os
from datetime import datetime

from google.cloud.bigtable import enums

from airflow.decorators import task_group
from airflow.models.dag import DAG
from airflow.providers.google.cloud.operators.bigtable import (
    BigtableCreateInstanceOperator,
    BigtableCreateTableOperator,
    BigtableDeleteInstanceOperator,
    BigtableDeleteTableOperator,
    BigtableUpdateClusterOperator,
    BigtableUpdateInstanceOperator,
)
from airflow.providers.google.cloud.sensors.bigtable import BigtableTableReplicationCompletedSensor
from airflow.utils.trigger_rule import TriggerRule

[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")
[docs]PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT")
[docs]DAG_ID = "bigtable"
[docs]CBT_INSTANCE_ID = f"bigtable-instance-id-{ENV_ID}"
[docs]CBT_INSTANCE_DISPLAY_NAME = "Instance-name"
[docs]CBT_INSTANCE_DISPLAY_NAME_UPDATED = f"{CBT_INSTANCE_DISPLAY_NAME} - updated"
[docs]CBT_INSTANCE_TYPE = enums.Instance.Type.DEVELOPMENT
[docs]CBT_INSTANCE_TYPE_PROD = 1
[docs]CBT_INSTANCE_LABELS: dict[str, str] = {}
[docs]CBT_INSTANCE_LABELS_UPDATED = {"env": "prod"}
[docs]CBT_CLUSTER_ID = f"bigtable-cluster-id-{ENV_ID}"
[docs]CBT_CLUSTER_ZONE = "europe-west1-b"
[docs]CBT_CLUSTER_NODES = 3
[docs]CBT_CLUSTER_NODES_UPDATED = 5
[docs]CBT_CLUSTER_STORAGE_TYPE = enums.StorageType.HDD
[docs]CBT_TABLE_ID = f"bigtable-table-id{ENV_ID}"
[docs]CBT_POKE_INTERVAL = 60
with DAG( DAG_ID, schedule="@once", start_date=datetime(2021, 1, 1), catchup=False, tags=["bigtable", "example"], ) as dag: # [START howto_operator_gcp_bigtable_instance_create]
[docs] create_instance_task = BigtableCreateInstanceOperator( project_id=PROJECT_ID, instance_id=CBT_INSTANCE_ID, main_cluster_id=CBT_CLUSTER_ID, main_cluster_zone=CBT_CLUSTER_ZONE, instance_display_name=CBT_INSTANCE_DISPLAY_NAME, instance_type=CBT_INSTANCE_TYPE, # type: ignore[arg-type] instance_labels=CBT_INSTANCE_LABELS, cluster_nodes=None, cluster_storage_type=CBT_CLUSTER_STORAGE_TYPE, # type: ignore[arg-type] task_id="create_instance_task", )
create_instance_task2 = BigtableCreateInstanceOperator( instance_id=CBT_INSTANCE_ID, main_cluster_id=CBT_CLUSTER_ID, main_cluster_zone=CBT_CLUSTER_ZONE, instance_display_name=CBT_INSTANCE_DISPLAY_NAME, instance_type=CBT_INSTANCE_TYPE, # type: ignore[arg-type] instance_labels=CBT_INSTANCE_LABELS, cluster_nodes=CBT_CLUSTER_NODES, cluster_storage_type=CBT_CLUSTER_STORAGE_TYPE, # type: ignore[arg-type] task_id="create_instance_task2", ) # [END howto_operator_gcp_bigtable_instance_create] @task_group() def create_tables(): # [START howto_operator_gcp_bigtable_table_create] create_table_task = BigtableCreateTableOperator( project_id=PROJECT_ID, instance_id=CBT_INSTANCE_ID, table_id=CBT_TABLE_ID, task_id="create_table", ) create_table_task2 = BigtableCreateTableOperator( instance_id=CBT_INSTANCE_ID, table_id=CBT_TABLE_ID, task_id="create_table_task2", ) # [END howto_operator_gcp_bigtable_table_create] create_table_task >> create_table_task2 @task_group() def update_clusters_and_instance(): # [START howto_operator_gcp_bigtable_cluster_update] cluster_update_task = BigtableUpdateClusterOperator( project_id=PROJECT_ID, instance_id=CBT_INSTANCE_ID, cluster_id=CBT_CLUSTER_ID, nodes=CBT_CLUSTER_NODES_UPDATED, task_id="update_cluster_task", ) cluster_update_task2 = BigtableUpdateClusterOperator( instance_id=CBT_INSTANCE_ID, cluster_id=CBT_CLUSTER_ID, nodes=CBT_CLUSTER_NODES_UPDATED, task_id="update_cluster_task2", ) # [END howto_operator_gcp_bigtable_cluster_update] # [START howto_operator_gcp_bigtable_instance_update] update_instance_task = BigtableUpdateInstanceOperator( instance_id=CBT_INSTANCE_ID, instance_display_name=CBT_INSTANCE_DISPLAY_NAME_UPDATED, instance_type=CBT_INSTANCE_TYPE_PROD, instance_labels=CBT_INSTANCE_LABELS_UPDATED, task_id="update_instance_task", ) # [END howto_operator_gcp_bigtable_instance_update] [cluster_update_task, cluster_update_task2] >> update_instance_task # [START howto_operator_gcp_bigtable_table_wait_for_replication] wait_for_table_replication_task = BigtableTableReplicationCompletedSensor( instance_id=CBT_INSTANCE_ID, table_id=CBT_TABLE_ID, poke_interval=CBT_POKE_INTERVAL, timeout=180, task_id="wait_for_table_replication_task2", ) # [END howto_operator_gcp_bigtable_table_wait_for_replication] # [START howto_operator_gcp_bigtable_table_delete] delete_table_task = BigtableDeleteTableOperator( project_id=PROJECT_ID, instance_id=CBT_INSTANCE_ID, table_id=CBT_TABLE_ID, task_id="delete_table_task", ) delete_table_task2 = BigtableDeleteTableOperator( instance_id=CBT_INSTANCE_ID, table_id=CBT_TABLE_ID, task_id="delete_table_task2", ) # [END howto_operator_gcp_bigtable_table_delete] delete_table_task.trigger_rule = TriggerRule.ALL_DONE delete_table_task2.trigger_rule = TriggerRule.ALL_DONE # [START howto_operator_gcp_bigtable_instance_delete] delete_instance_task = BigtableDeleteInstanceOperator( project_id=PROJECT_ID, instance_id=CBT_INSTANCE_ID, task_id="delete_instance_task", ) delete_instance_task2 = BigtableDeleteInstanceOperator( instance_id=CBT_INSTANCE_ID, task_id="delete_instance_task2", ) # [END howto_operator_gcp_bigtable_instance_delete] delete_instance_task.trigger_rule = TriggerRule.ALL_DONE delete_instance_task2.trigger_rule = TriggerRule.ALL_DONE ( [create_instance_task, create_instance_task2] >> create_tables() >> wait_for_table_replication_task >> update_clusters_and_instance() >> delete_table_task >> delete_table_task2 >> [delete_instance_task, delete_instance_task2] ) from tests.system.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.system.utils import get_test_run # noqa: E402 # Needed to run the example DAG with pytest (see: tests/system/README.md#run_via_pytest)
[docs]test_run = get_test_run(dag)

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