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from __future__ import annotations

import os
from datetime import datetime, timedelta

from airflow import DAG
from import AzureSynapseRunSparkBatchOperator

[docs]AIRFLOW_HOME = os.getenv("AIRFLOW_HOME", "/usr/local/airflow")
[docs]EXECUTION_TIMEOUT = int(os.getenv("EXECUTION_TIMEOUT", 6))
[docs]default_args = { "execution_timeout": timedelta(hours=EXECUTION_TIMEOUT), "retries": int(os.getenv("DEFAULT_TASK_RETRIES", 2)), "retry_delay": timedelta(seconds=int(os.getenv("DEFAULT_RETRY_DELAY_SECONDS", 60))), }
[docs]SPARK_JOB_PAYLOAD = { "name": "SparkJob", "file": "abfss://", "args": [ "abfss://", "abfss://", ], "jars": [], "pyFiles": [], "files": [], "conf": { "spark.dynamicAllocation.enabled": "false", "spark.dynamicAllocation.minExecutors": "1", "spark.dynamicAllocation.maxExecutors": "2", }, "numExecutors": 2, "executorCores": 4, "executorMemory": "28g", "driverCores": 4, "driverMemory": "28g", }
with DAG( dag_id="example_synapse_spark_job", start_date=datetime(2022, 1, 1), schedule=None, catchup=False, default_args=default_args, tags=["example", "synapse"], ) as dag: # [START howto_operator_azure_synapse]
[docs] run_spark_job = AzureSynapseRunSparkBatchOperator( task_id="run_spark_job", spark_pool="provsparkpool", payload=SPARK_JOB_PAYLOAD, # type: ignore )
# [END howto_operator_azure_synapse] from tests.system.utils import get_test_run # noqa: E402 # Needed to run the example DAG with pytest (see: tests/system/
[docs]test_run = get_test_run(dag)

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