Parameterized SQL query in Azure ML

Question

Background: There seems to be a way to parameterize DataPath with PipelineParameter https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-showcasing-datapath-and-pipelineparameter.ipynb

But I'd like to parameterize my SQL query with PipelineParameter, for example, with this query

sql_query = """
SELECT id, foo, bar FROM baz
WHERE baz.id BETWEEN 10 AND 20
"""
dataset = Dataset.Tabular.from_sql_query((sql_datastore, sql_query))

I'd like to use PipelineParameter to parameterize 10 and 20 as param_1 and param_2. Is this possible?

Answer 1

Found a way to do this:

Pass your params to PythonScriptStep

param_1 = PipelineParameter(name='min_id', default_value=5)
param_2 = PipelineParameter(name='max_id', default_value=10)
sql_datastore = "sql_datastore"
step = PythonScriptStep(script_name='script.py', arguments=[param_1, param_2, 
sql_datastore])

In script.py

min_id_param = sys.argv[1]
max_id_param = sys.argv[2]
sql_datastore_name = sys.argv[3]
query = """
SELECT id, foo, bar FROM baz
WHERE baz.id BETWEEN {} AND {}
""".format(min_id_param, max_id_param)
run = Run.get_context()
sql_datastore = Datastore.get(run.experiment.workspace, sql_datastore_name)
dataset = Dataset.Tabular.from_sql_query((sql_datastore, query))