Josh
02/26/2024, 10:33 AMScout
02/26/2024, 10:33 AMJosh
02/26/2024, 10:36 AMScout
02/26/2024, 10:36 AMcode_version
which can be used to version assets based on their computation logic. This feature allows you to skip redundant runs of computationally expensive assets by memoizing them based on whether the computation logic of an asset has changed. While this doesn't directly tell you which upstream dependency has changed, it does provide a mechanism to control materialization based on changes in the code. To implement a system that checks for updates in upstream dependencies within your code, you might consider the following approaches: 1. Asset Sensors: You could create sensors that monitor for changes in upstream assets. When an upstream asset is materialized, the sensor could trigger a downstream job or asset to be materialized. 2. Custom Logic: Implement custom logic within your assets that checks the materialization events of upstream assets. This could involve querying the Dagster instance for the materialization metadata of upstream assets and comparing timestamps or other relevant information to determine if an update has occurred. 3. Asset Dependencies: By defining explicit dependencies between assets, Dagster ensures that assets are materialized in the correct order. You could use the dependency graph to determine the order in which assets should be checked for updates. 4. Event Logs: You could also use Dagster's event log to track the materialization of assets. By querying the event log, you could potentially determine which upstream assets have been recently materialized. 5. Asset Materialization Hooks: Implement hooks that get called when an asset is materialized. These hooks could log or take action based on the materialization of upstream assets. Please note that these approaches are conceptual and would require custom implementation based on your specific use case and the capabilities of your Dagster deployment. For the most current and detailed guidance, you should refer to the latest Dagster documentation or seek assistance from the Dagster community.Josh
02/26/2024, 10:38 AMScout
02/26/2024, 10:38 AMpython from dagster import AssetKey, build_op_context def get_last_materialization_timestamp(context, asset_key): latest_materialization = context.instance.get_latest_materialization_events( asset_keys=[AssetKey(asset_key)] ) if latest_materialization and asset_key in latest_materialization: return latest_materialization[asset_key].timestamp else: return None # Example usage: with build_op_context() as context: timestamp = get_last_materialization_timestamp(context, "your_upstream_asset_key") print(f"The last materialization of the upstream asset occurred at: {timestamp}")
In this example, AssetKey("your_upstream_asset_key")
should be replaced with the actual key of your upstream asset. The get_latest_materialization_events
method returns a dictionary mapping AssetKey
to the latest materialization event for that asset. You can then access the timestamp
attribute of the event to get the time of the last materialization. Please ensure that you have the appropriate context and that your Dagster instance is properly configured to access the event logs. The exact implementation details may vary depending on the version of Dagster you are using and the setup of your environment. Always refer to the latest documentation for the most accurate and up-to-date information.