github dagster-io/dagster 0.14.6

latest releases: 1.8.8, dagster-sigma/v0.0.10, dagster-sigma/v0.0.9...
2 years ago

New

  • Added IO manager for materializing assets to GCS. You can specify the GCS asset IO manager by using the following config for resource_defs in AssetGroup:
from dagster import AssetGroup, gcs_pickle_asset_io_manager, gcs_resource
asset_group = AssetGroup(
    [upstream_asset, downstream_asset],
    resource_defs={"io_manager": gcs_pickle_asset_io_manager, "gcs": gcs_resource}
)
  • Improved the performance of storage queries run by the sensor daemon to enforce the idempotency of run keys. This should reduce the database CPU when evaluating sensors with a large volume of run requests with run keys that repeat across evaluations.
  • [dagit] Added information on sensor ticks to show when a sensor has requested runs that did not result in the creation of a new run due to the enforcement of idempotency using run keys.
  • [k8s] Run and step workers are now labeled with the Dagster run id that they are currently handling.
  • If a step launched with a StepLauncher encounters an exception, that exception / stack trace will now appear in the event log.

Bugfixes

  • Fixed a race condition where canceled backfills would resume under certain conditions.
  • Fixed an issue where exceptions that were raised during sensor and schedule execution didn’t always show a stack trace in Dagit.
  • During execution, dependencies will now resolve correctly for certain dynamic graph structures that were previously resolving incorrectly.
  • When using the forkserver start_method on the multiprocess executor, preload_modules have been adjusted to prevent libraries that change namedtuple serialization from causing unexpected exceptions.
  • Fixed a naming collision between dagster decorators and submodules that sometimes interfered with static type checkers (e.g. pyright).
  • [dagit] postgres database connection management has improved when watching actively executing runs
  • [dagster-databricks] The databricks_pyspark_step_launcher now supports steps with RetryPolicies defined, as well as RetryRequested exceptions.

Community Contributions

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