SageMakerBaseSensor

Amazon

Contains general sensor behavior for SageMaker.

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Last Updated: Jan. 19, 2023

Access Instructions

Install the Amazon provider package into your Airflow environment.

Import the module into your DAG file and instantiate it with your desired params.

Parameters

soft_failSet to true to mark the task as SKIPPED on failure
poke_intervalTime in seconds that the job should wait in between each try
timeoutTime, in seconds before the task times out and fails.
modeHow the sensor operates. Options are: { poke | reschedule }, default is poke. When set to poke the sensor is taking up a worker slot for its whole execution time and sleeps between pokes. Use this mode if the expected runtime of the sensor is short or if a short poke interval is required. Note that the sensor will hold onto a worker slot and a pool slot for the duration of the sensor’s runtime in this mode. When set to reschedule the sensor task frees the worker slot when the criteria is not yet met and it’s rescheduled at a later time. Use this mode if the time before the criteria is met is expected to be quite long. The poke interval should be more than one minute to prevent too much load on the scheduler.
exponential_backoffallow progressive longer waits between pokes by using exponential backoff algorithm
max_waitmaximum wait interval between pokes, can be timedelta or float seconds

Documentation

Contains general sensor behavior for SageMaker.

Subclasses should implement get_sagemaker_response() and state_from_response() methods. Subclasses should also implement NON_TERMINAL_STATES and FAILED_STATE methods.

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