Source code for tests.system.databricks.example_databricks_workflow

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"""Example DAG for using the DatabricksWorkflowTaskGroup and DatabricksNotebookOperator."""

from __future__ import annotations

import os
from datetime import timedelta

from airflow.models.dag import DAG
from airflow.providers.databricks.operators.databricks import (
    DatabricksNotebookOperator,
    DatabricksTaskOperator,
)
from airflow.providers.databricks.operators.databricks_workflow import DatabricksWorkflowTaskGroup
from airflow.utils.timezone import datetime

[docs]EXECUTION_TIMEOUT = int(os.getenv("EXECUTION_TIMEOUT", 6))

[docs]DATABRICKS_CONN_ID = os.getenv("DATABRICKS_CONN_ID", "databricks_default")
[docs]DATABRICKS_NOTIFICATION_EMAIL = os.getenv("DATABRICKS_NOTIFICATION_EMAIL", "your_email@serviceprovider.com")

[docs]GROUP_ID = os.getenv("DATABRICKS_GROUP_ID", "1234").replace(".", "_")
[docs]USER = os.environ.get("USER")

[docs]QUERY_ID = os.environ.get("QUERY_ID", "d3773b5a-56f9-422c-ae60-048eaa90aa33")
[docs]WAREHOUSE_ID = os.environ.get("WAREHOUSE_ID", "368fe30b92228713")

# job_cluster_spec example for Databricks on Azure
[docs]job_cluster_spec = [
    {
        "job_cluster_key": "Shared_job_cluster",
        "new_cluster": {
            "cluster_name": "",
            "spark_version": "11.3.x-scala2.12",
            "azure_attributes": {
                "availability": "ON_DEMAND_AZURE",
                "spot_bid_max_price": -1,
            },
            "num_workers": 1,
            "spark_conf": {},
            "node_type_id": "Standard_D3_v2",
            "ssh_public_keys": [],
            "custom_tags": {},
            "spark_env_vars": {"PYSPARK_PYTHON": "/databricks/python3/bin/python3"},
            "cluster_source": "JOB",
            "init_scripts": [],
        },
    }
]

[docs]dag = DAG(
    dag_id="example_databricks_workflow",
    start_date=datetime(2022, 1, 1),
    schedule=None,
    catchup=False,
    tags=["example", "databricks"],
)
with dag:
    # [START howto_databricks_workflow_notebook]
[docs]    task_group = DatabricksWorkflowTaskGroup(
        group_id=f"test_workflow_{USER}_{GROUP_ID}",
        databricks_conn_id=DATABRICKS_CONN_ID,
        job_clusters=job_cluster_spec,
        notebook_params={"ts": "{{ ts }}"},
        notebook_packages=[
            {
                "pypi": {
                    "package": "simplejson==3.18.0",  # Pin specification version of a package like this.
                    "repo": "https://pypi.org/simple",  # You can specify your required Pypi index here.
                }
            },
        ],
        extra_job_params={
            "email_notifications": {
                "on_start": [DATABRICKS_NOTIFICATION_EMAIL],
            },
        },
    )
    with task_group:
        notebook_1 = DatabricksNotebookOperator(
            task_id="workflow_notebook_1",
            databricks_conn_id=DATABRICKS_CONN_ID,
            notebook_path="/Shared/Notebook_1",
            notebook_packages=[{"pypi": {"package": "Faker"}}],
            source="WORKSPACE",
            job_cluster_key="Shared_job_cluster",
            execution_timeout=timedelta(seconds=600),
        )

        notebook_2 = DatabricksNotebookOperator(
            task_id="workflow_notebook_2",
            databricks_conn_id=DATABRICKS_CONN_ID,
            notebook_path="/Shared/Notebook_2",
            source="WORKSPACE",
            job_cluster_key="Shared_job_cluster",
            notebook_params={"foo": "bar", "ds": "{{ ds }}"},
        )

        task_operator_nb_1 = DatabricksTaskOperator(
            task_id="nb_1",
            databricks_conn_id=DATABRICKS_CONN_ID,
            job_cluster_key="Shared_job_cluster",
            task_config={
                "notebook_task": {
                    "notebook_path": "/Shared/Notebook_1",
                    "source": "WORKSPACE",
                },
                "libraries": [
                    {"pypi": {"package": "Faker"}},
                ],
            },
        )

        sql_query = DatabricksTaskOperator(
            task_id="sql_query",
            databricks_conn_id=DATABRICKS_CONN_ID,
            task_config={
                "sql_task": {
                    "query": {
                        "query_id": QUERY_ID,
                    },
                    "warehouse_id": WAREHOUSE_ID,
                }
            },
        )

        notebook_1 >> notebook_2 >> task_operator_nb_1 >> sql_query
    # [END howto_databricks_workflow_notebook]

    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: tests/system/README.md#run_via_pytest)
[docs]test_run = get_test_run(dag)