Glen Aultman-Bettridge
02/21/2024, 4:37 PMScout
02/21/2024, 4:37 PMRunRequest
objects that include the necessary run configuration for the job.
2. Define the Job: The job would consist of multiple steps (ops) that perform the file transfer to S3 and execute the Snowflake SQL script.
3. Transfer Files to S3: One of the ops in your job would handle the transfer of files from the SFTP server to the S3 bucket "my-bucket".
4. Run Snowflake SQL Script: Another op would execute the Snowflake SQL script to import the file into the "my-table" table.
Here is an example of what the sensor might look like, based on the documentation:
python
from dagster import sensor, RunRequest, SensorEvaluationContext
from dagster_aws.s3.sensor import get_s3_keys
@sensor(job=my_job)
def my_sftp_sensor(context: SensorEvaluationContext):
# Logic to check for new files on the SFTP server
# This is a placeholder and would need to be replaced with actual SFTP checking logic
new_files = check_sftp_for_new_files()
if not new_files:
return SkipReason("No new files found on the SFTP server.")
# Generate RunRequests for each new file
run_requests = [
RunRequest(
run_key=file_name,
run_config={
# Include necessary configuration for the job
}
)
for file_name in new_files
]
return run_requests
And here is a high-level example of what the job might look like:
python
from dagster import job, op
@op
def transfer_file_to_s3(context, file_name):
# Logic to transfer file from SFTP to S3
pass
@op
def run_snowflake_sql(context, file_name):
# Logic to run Snowflake SQL script
pass
@job
def my_job():
file_name = transfer_file_to_s3()
run_snowflake_sql(file_name)
Please note that the above examples are high-level and do not include actual implementation details for interacting with SFTP, S3, or Snowflake. You would need to fill in the logic for check_sftp_for_new_files
, transfer_file_to_s3
, and run_snowflake_sql
with the appropriate code to interact with these services.
Additionally, the run_config
in the RunRequest
would need to be populated with the necessary configuration for the job ops, such as credentials and file paths.
FScout
02/21/2024, 4:38 PMGlen Aultman-Bettridge
02/21/2024, 5:03 PMScout
02/21/2024, 5:03 PMDefinitions
call.
Here's an example of how you might define a sensor that uses a resource:
python
from dagster import sensor, RunRequest, SensorEvaluationContext, ResourceDefinition, Definitions
# Define your resource here
my_resource = ResourceDefinition(...)
@sensor(job=my_job, required_resource_keys={"my_resource_key"})
def my_sensor_with_resources(context: SensorEvaluationContext):
# You can access the resource using the context
my_resource_instance = context.resources.my_resource_key
# Logic to check for new files and create run requests
...
# When defining your repository, you attach the resource to the sensor
defs = Definitions(
jobs=[my_job],
sensors=[my_sensor_with_resources],
resources={"my_resource_key": my_resource},
)
In this example, my_resource
is a ResourceDefinition
that you would define based on your needs (e.g., a resource for interacting with SFTP or S3). The my_sensor_with_resources
sensor is defined with the required_resource_keys
parameter, which tells Dagster that this sensor requires the specified resource.
When you define your repository using the Definitions
class, you include the resource in the resources
parameter, mapping the resource key to the actual resource definition.
Please note that the actual implementation of the resource and how it is used within the sensor will depend on the specifics of your use case, such as the APIs or libraries you are using to interact with external systems like SFTP or S3. Resources in asset_sensor button Troubleshooting: Getting a KeyError when... button Sensors | Dagster Docs button Dagster UI | Dagster button Thank you for your feedback!