def test_lakeadmin_2_image_with_apps(kube: TestClient) -> None:
lake_admin_job_mage_with_apps = LAKE_ADMIN_JOB
lake_admin_job_mage_with_apps["metadata"]["generateName"]= "test-orbit-job-lake-admin-image-with-apps-"
lake_admin_job_mage_with_apps["spec"]["tasks"]= [{
"notebookName": "2-Image_with_apps.ipynb",
"sourcePath": "shared/samples/notebooks/M-Admin",
"targetPath": "shared/regression/notebooks/M-Admin",
"params": {}
}]
logger.info(lake_admin_job_mage_with_apps)
lakeadmin = OrbitJobCustomApiObject(lake_admin_job_mage_with_apps)
lakeadmin.create(namespace="lake-admin")
# Logic to wait till OrbitJob creates
lakeadmin.wait_until_ready(timeout=120)
# Logic to pass or fail the pytest
lakeadmin.wait_until_job_completes(timeout=7200, interval=30)
current_status = lakeadmin.get_status().get("orbitJobOperator").get("jobStatus")
logger.info(f"current_status={current_status}")
#Cleanup
lakeadmin.delete()
assert current_status == JOB_COMPLETION_STATUS
def test_lakecreator_extractor(zip_file, kube: TestClient):
# Extract Zip Files in Parallel
bucketName = lake_creator_config.get("bucketName")
extractedFolder = lake_creator_config.get("extractedFolder")
schemas = get_schemas(bucketName, 'landing/cms/schema/')
# for key in s3.list_objects_v2(Bucket=bucketName, Prefix=sourceFolder)['Contents']:
file = zip_file['Key']
schema = get_schema(schemas, file)
s3_data_folder = os.path.join(extractedFolder,
schema[0] if schema[0] else "")
notebook_to_run = {
"apiVersion": "orbit.aws/v1",
"kind": "OrbitJob",
"metadata": {
"generateName": f"test-orbit-job-lake-creator-"
},
"spec": {
"taskType":
"jupyter",
"compute": {
"nodeType": "ec2",
"container": {
"concurrentProcesses": 1
},
"podSetting": "orbit-runner-support-small"
},
"tasks": [{
"notebookName": "Example-2-Extract-Files.ipynb",
"sourcePath":
"/home/jovyan/shared/samples/notebooks/A-LakeCreator",
"targetPath":
"/home/jovyan/shared/regression/notebooks/A-LakeCreator",
"params": {
"bucketName": bucketName,
"zipFileName": file,
"targetFolder": s3_data_folder,
"use_subdirs": "False" if schema[0] else "True"
}
}]
}
}
logger.info(notebook_to_run)
lakecreator = OrbitJobCustomApiObject(notebook_to_run)
lakecreator.create(namespace="lake-creator")
# Logic to wait till OrbitJob creates
lakecreator.wait_until_ready(timeout=60)
# Logic to pass or fail the pytest
lakecreator.wait_until_job_completes(timeout=600)
current_status = lakecreator.get_status().get("orbitJobOperator").get(
"jobStatus")
logger.info(f"current_status={current_status}")
# Cleanup
lakecreator.delete()
assert current_status == JOB_COMPLETION_STATUS
def test_lakecreator_lf(kube: TestClient):
notebook_to_run = {
"apiVersion": "orbit.aws/v1",
"kind": "OrbitJob",
"metadata": {
"generateName": f"test-orbit-job-lake-creator-"
},
"spec": {
"taskType":
"jupyter",
"compute": {
"nodeType": "ec2",
"container": {
"concurrentProcesses": 1
},
"podSetting": "orbit-runner-support-large",
},
"tasks": [{
"notebookName":
"Example-4-LakeFormation-Secured-DB.ipynb",
"sourcePath":
"/home/jovyan/shared/samples/notebooks/A-LakeCreator",
"targetPath":
"/home/jovyan/shared/regression/notebooks/A-LakeCreator",
}]
}
}
logger.info(f"notebook_to_run={notebook_to_run}")
lakecreator = OrbitJobCustomApiObject(notebook_to_run)
lakecreator.create(namespace="lake-creator")
# Logic to wait till OrbitJob creates
lakecreator.wait_until_ready(timeout=60)
# Logic to pass or fail the pytest
lakecreator.wait_until_job_completes(timeout=1800)
current_status = lakecreator.get_status().get("orbitJobOperator").get(
"jobStatus")
logger.info(f"current_status={current_status}")
# Cleanup
lakecreator.delete()
assert current_status == JOB_COMPLETION_STATUS
def test_lakecreator_glue_table_creator(datafile, kube: TestClient):
region = workspace.get("region")
bucket_name = lake_creator_config.get("bucketName")
database_name = lake_creator_config.get("database_name")
schemas = get_schemas(bucket_name, 'landing/cms/schema/')
#file = datafile
p = Path(datafile).parent
print(f"Path={str(p)}")
schema = get_schema(schemas, datafile)
from datetime import datetime
datetimestring = datetime.now().strftime("%m%d%Y%H%M%S%f")
notebook_to_run = {
"apiVersion": "orbit.aws/v1",
"kind": "OrbitJob",
"metadata": {
"generateName": f"test-orbit-job-lake-creator-"
},
"spec": {
"taskType":
"jupyter",
"compute": {
"nodeType": "ec2",
"container": {
"concurrentProcesses": 1
},
"podSetting": "orbit-runner-support-small",
"env": [{
'name': 'AWS_ORBIT_S3_BUCKET',
'value': bucket_name
}]
},
"tasks": [{
"notebookName": "Example-3-Load-Database-Athena.ipynb",
"sourcePath":
"/home/jovyan/shared/samples/notebooks/A-LakeCreator",
"targetPath":
"/home/jovyan/shared/regression/notebooks/A-LakeCreator",
"targetPrefix": f"unsecured-{datetimestring}",
"params": {
"source_bucket_name": bucket_name,
"target_bucket_name": bucket_name,
"database_name": database_name,
"schema_dir": "landing/cms/schema",
"file_path": str(p),
"region": region
}
}]
}
}
print(notebook_to_run)
lakecreator = OrbitJobCustomApiObject(notebook_to_run)
lakecreator.create(namespace="lake-creator")
# Logic to wait till OrbitJob creates
lakecreator.wait_until_ready(timeout=60)
# Logic to pass or fail the pytest
lakecreator.wait_until_job_completes(timeout=1200)
current_status = lakecreator.get_status().get("orbitJobOperator").get(
"jobStatus")
logger.info(f"current_status={current_status}")
# Cleanup
lakecreator.delete()
assert current_status == JOB_COMPLETION_STATUS
def test_lakeuser_notebooks_xfail(kube: TestClient) -> None:
notebook_to_run={
"name": "Example-90-Failure-Behavior.ipynb",
"folder": "B-DataAnalyst"
}
podsetting_name = "orbit-runner-support-small"
body = {
"apiVersion": "orbit.aws/v1",
"kind": "OrbitJob",
"metadata": {
"generateName": "test-orbit-job-lake-user-"
},
"spec": {
"taskType": "jupyter",
"compute": {
"nodeType": "ec2",
"container": {
"concurrentProcesses": 1
},
"podSetting": podsetting_name
},
"tasks": [{
"notebookName": notebook_to_run['name'],
"sourcePath": f"shared/samples/notebooks/{notebook_to_run['folder']}",
"targetPath": f"shared/regression/notebooks/{notebook_to_run['folder']}",
"params": {}
}]
}
}
logger.info(body)
lakeuser = OrbitJobCustomApiObject(body)
lakeuser.create(namespace="lake-user")
# Logic to wait till OrbitJob creates
lakeuser.wait_until_ready(timeout=120)
# Logic to pass or fail the pytest
lakeuser.wait_until_job_completes(timeout=1200)
current_status = lakeuser.get_status().get("orbitJobOperator").get("jobStatus")
logger.info(f"current_status={current_status}")
#Cleanup
lakeuser.delete()
assert current_status == JOB_FAILED_STATUS
def test_lakeuser_notebooks(notebook_to_run, kube: TestClient) -> None:
logger.info(f"notebook_to_run={notebook_to_run}")
notebook_file_name = notebook_to_run['name'].split(".")[0]
podsetting_name = "orbit-runner-support-xlarge" if notebook_file_name in lake_creator_list_of_files['sagemaker_notebooks_list'] else "orbit-runner-support-large"
body = {
"apiVersion": "orbit.aws/v1",
"kind": "OrbitJob",
"metadata": {
"generateName": "test-orbit-job-lake-user-"
},
"spec": {
"taskType": "jupyter",
"compute": {
"nodeType": "ec2",
"container": {
"concurrentProcesses": 1
},
"podSetting": podsetting_name
},
"tasks": [{
"notebookName": notebook_to_run['name'],
"sourcePath": f"shared/samples/notebooks/{notebook_to_run['folder']}",
"targetPath": f"shared/regression/notebooks/{notebook_to_run['folder']}",
"params": {}
}]
}
}
logger.info(body)
lakeuser = OrbitJobCustomApiObject(body)
lakeuser.create(namespace="lake-user")
# Logic to wait till OrbitJob creates
lakeuser.wait_until_ready(timeout=120)
# Logic to pass or fail the pytest
lakeuser.wait_until_job_completes(timeout=7200)
current_status = lakeuser.get_status().get("orbitJobOperator").get("jobStatus")
logger.info(f"current_status={current_status}")
#Cleanup
lakeuser.delete()
assert current_status == JOB_COMPLETION_STATUS