bigtable

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

Big Data & Analytics


Providers:

Run this DAG

1. Install Astronomer CLISkip if you already have the CLI

2. Initate the project:

3. Copy and paste the code below into a file in the

dags
directory.

4. Add the following to your requirements.txt file:

5. Run the DAG:

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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 # noqa E501 # pylint: disable=line-too-long
* 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 # noqa E501 # pylint: disable=line-too-long
* CBT_TABLE_ID - desired ID of the Table
* CBT_POKE_INTERVAL - number of seconds between every attempt of Sensor check
"""
import json
from os import getenv
from airflow import models
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.dates import days_ago
GCP_PROJECT_ID = getenv('GCP_PROJECT_ID', 'example-project')
CBT_INSTANCE_ID = getenv('GCP_BIG_TABLE_INSTANCE_ID', 'some-instance-id')
CBT_INSTANCE_DISPLAY_NAME = getenv('GCP_BIG_TABLE_INSTANCE_DISPLAY_NAME', 'Human-readable name')
CBT_INSTANCE_DISPLAY_NAME_UPDATED = getenv(
"GCP_BIG_TABLE_INSTANCE_DISPLAY_NAME_UPDATED", f"{CBT_INSTANCE_DISPLAY_NAME} - updated"
)
CBT_INSTANCE_TYPE = getenv('GCP_BIG_TABLE_INSTANCE_TYPE', '2')
CBT_INSTANCE_TYPE_PROD = getenv('GCP_BIG_TABLE_INSTANCE_TYPE_PROD', '1')
CBT_INSTANCE_LABELS = getenv('GCP_BIG_TABLE_INSTANCE_LABELS', '{}')
CBT_INSTANCE_LABELS_UPDATED = getenv('GCP_BIG_TABLE_INSTANCE_LABELS_UPDATED', '{"env": "prod"}')
CBT_CLUSTER_ID = getenv('GCP_BIG_TABLE_CLUSTER_ID', 'some-cluster-id')
CBT_CLUSTER_ZONE = getenv('GCP_BIG_TABLE_CLUSTER_ZONE', 'europe-west1-b')
CBT_CLUSTER_NODES = getenv('GCP_BIG_TABLE_CLUSTER_NODES', '3')
CBT_CLUSTER_NODES_UPDATED = getenv('GCP_BIG_TABLE_CLUSTER_NODES_UPDATED', '5')
CBT_CLUSTER_STORAGE_TYPE = getenv('GCP_BIG_TABLE_CLUSTER_STORAGE_TYPE', '2')
CBT_TABLE_ID = getenv('GCP_BIG_TABLE_TABLE_ID', 'some-table-id')
CBT_POKE_INTERVAL = getenv('GCP_BIG_TABLE_POKE_INTERVAL', '60')
with models.DAG(
'example_gcp_bigtable_operators',
schedule_interval=None, # Override to match your needs
start_date=days_ago(1),
tags=['example'],
) as dag:
# [START howto_operator_gcp_bigtable_instance_create]
create_instance_task = BigtableCreateInstanceOperator(
project_id=GCP_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=int(CBT_INSTANCE_TYPE),
instance_labels=json.loads(CBT_INSTANCE_LABELS),
cluster_nodes=None,
cluster_storage_type=int(CBT_CLUSTER_STORAGE_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=int(CBT_INSTANCE_TYPE),
instance_labels=json.loads(CBT_INSTANCE_LABELS),
cluster_nodes=int(CBT_CLUSTER_NODES),
cluster_storage_type=int(CBT_CLUSTER_STORAGE_TYPE),
task_id='create_instance_task2',
)
create_instance_task >> create_instance_task2
# [END howto_operator_gcp_bigtable_instance_create]
# [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=int(CBT_INSTANCE_TYPE_PROD),
instance_labels=json.loads(CBT_INSTANCE_LABELS_UPDATED),
task_id='update_instance_task',
)
# [END howto_operator_gcp_bigtable_instance_update]
# [START howto_operator_gcp_bigtable_cluster_update]
cluster_update_task = BigtableUpdateClusterOperator(
project_id=GCP_PROJECT_ID,
instance_id=CBT_INSTANCE_ID,
cluster_id=CBT_CLUSTER_ID,
nodes=int(CBT_CLUSTER_NODES_UPDATED),
task_id='update_cluster_task',
)
cluster_update_task2 = BigtableUpdateClusterOperator(
instance_id=CBT_INSTANCE_ID,
cluster_id=CBT_CLUSTER_ID,
nodes=int(CBT_CLUSTER_NODES_UPDATED),
task_id='update_cluster_task2',
)
cluster_update_task >> cluster_update_task2
# [END howto_operator_gcp_bigtable_cluster_update]
# [START howto_operator_gcp_bigtable_instance_delete]
delete_instance_task = BigtableDeleteInstanceOperator(
project_id=GCP_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]
# [START howto_operator_gcp_bigtable_table_create]
create_table_task = BigtableCreateTableOperator(
project_id=GCP_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',
)
create_table_task >> create_table_task2
# [END howto_operator_gcp_bigtable_table_create]
# [START howto_operator_gcp_bigtable_table_wait_for_replication]
wait_for_table_replication_task = BigtableTableReplicationCompletedSensor(
project_id=GCP_PROJECT_ID,
instance_id=CBT_INSTANCE_ID,
table_id=CBT_TABLE_ID,
poke_interval=int(CBT_POKE_INTERVAL),
timeout=180,
task_id='wait_for_table_replication_task',
)
wait_for_table_replication_task2 = BigtableTableReplicationCompletedSensor(
instance_id=CBT_INSTANCE_ID,
table_id=CBT_TABLE_ID,
poke_interval=int(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=GCP_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]
wait_for_table_replication_task >> delete_table_task
wait_for_table_replication_task2 >> delete_table_task
wait_for_table_replication_task >> delete_table_task2
wait_for_table_replication_task2 >> delete_table_task2
create_instance_task >> create_table_task >> cluster_update_task
cluster_update_task >> update_instance_task >> delete_table_task
create_instance_task2 >> create_table_task2 >> cluster_update_task2 >> delete_table_task2
# Only delete instances after all tables are deleted
[delete_table_task, delete_table_task2] >> delete_instance_task >> delete_instance_task2