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user5-0616-02-spark-0616015236.py
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user5-0616-02-spark-0616015236.py
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from airflow import DAG
from airflow_notebook.pipeline import NotebookOp
from airflow.utils.dates import days_ago
# Setup default args with older date to automatically trigger when uploaded
args = {
"project_id": "user5-0616-02-spark-0616015236",
}
dag = DAG(
"user5-0616-02-spark-0616015236",
default_args=args,
schedule_interval="@once",
start_date=days_ago(1),
description="Created with Elyra 2.2.4 pipeline editor using user5-0616-02-spark.pipeline.",
is_paused_upon_creation=False,
)
notebook_op_d5009697_771e_4f71_bc20_e52d905c9f9d = NotebookOp(
name="start_spark_cluster",
namespace="ml-workshop",
task_id="start_spark_cluster",
notebook="ml-workshop/src/automation/deploy_spark_jobs/start-spark-cluster.py",
cos_endpoint="http://minio-ml-workshop:9000",
cos_bucket="airflow",
cos_directory="user5-0616-02-spark-0616015236",
cos_dependencies_archive="start-spark-cluster-d5009697-771e-4f71-bc20-e52d905c9f9d.tar.gz",
pipeline_outputs=["spark-info.txt"],
pipeline_inputs=[],
image="quay.io/ml-aml-workshop/airflow-python-runner:0.0.8",
in_cluster=True,
env_vars={
"AWS_ACCESS_KEY_ID": "minio",
"AWS_SECRET_ACCESS_KEY": "minio123",
"ELYRA_ENABLE_PIPELINE_INFO": "True",
"SPARK_CLUSTER": "user5-cluster",
"WORKER_NODES": "2",
"S3_ENDPOINT_URL": "http://minio-ml-workshop:9000",
},
config_file="None",
dag=dag,
)
notebook_op_d5009697_771e_4f71_bc20_e52d905c9f9d.image_pull_policy = "IfNotPresent"
notebook_op_91a3738b_783b_4eb6_823c_1b8b013a4d51 = NotebookOp(
name="Merge_Data",
namespace="ml-workshop",
task_id="Merge_Data",
notebook="ml-workshop/src/notebooks/Merge_Data.ipynb",
cos_endpoint="http://minio-ml-workshop:9000",
cos_bucket="airflow",
cos_directory="user5-0616-02-spark-0616015236",
cos_dependencies_archive="Merge_Data-91a3738b-783b-4eb6-823c-1b8b013a4d51.tar.gz",
pipeline_outputs=[],
pipeline_inputs=["spark-info.txt"],
image="quay.io/ml-aml-workshop/elyra-spark:0.0.4",
in_cluster=True,
env_vars={
"AWS_ACCESS_KEY_ID": "minio",
"AWS_SECRET_ACCESS_KEY": "minio123",
"ELYRA_ENABLE_PIPELINE_INFO": "True",
"SPARK_CLUSTER": "opentlc-mgr-cluster",
"WORKER_NODES": "2",
"S3_ENDPOINT_URL": "http://minio-ml-workshop:9000",
},
config_file="None",
dag=dag,
)
notebook_op_91a3738b_783b_4eb6_823c_1b8b013a4d51.image_pull_policy = "IfNotPresent"
(
notebook_op_91a3738b_783b_4eb6_823c_1b8b013a4d51
<< notebook_op_d5009697_771e_4f71_bc20_e52d905c9f9d
)
notebook_op_b6d6a9d3_65b6_4ef6_9ce8_4d713bea5e2f = NotebookOp(
name="stop_spark_cluster",
namespace="ml-workshop",
task_id="stop_spark_cluster",
notebook="ml-workshop/src/automation/deploy_spark_jobs/stop-spark-cluster.py",
cos_endpoint="http://minio-ml-workshop:9000",
cos_bucket="airflow",
cos_directory="user5-0616-02-spark-0616015236",
cos_dependencies_archive="stop-spark-cluster-b6d6a9d3-65b6-4ef6-9ce8-4d713bea5e2f.tar.gz",
pipeline_outputs=[],
pipeline_inputs=["spark-info.txt"],
image="quay.io/ml-aml-workshop/airflow-python-runner:0.0.8",
in_cluster=True,
env_vars={
"AWS_ACCESS_KEY_ID": "minio",
"AWS_SECRET_ACCESS_KEY": "minio123",
"ELYRA_ENABLE_PIPELINE_INFO": "True",
},
config_file="None",
dag=dag,
)
notebook_op_b6d6a9d3_65b6_4ef6_9ce8_4d713bea5e2f.image_pull_policy = "IfNotPresent"
(
notebook_op_b6d6a9d3_65b6_4ef6_9ce8_4d713bea5e2f
<< notebook_op_91a3738b_783b_4eb6_823c_1b8b013a4d51
)