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Changelog#

0.9.21#

Community Contributions

  • Fixed helm chart to only add flower to the K8s ingress when enabled (thanks @PenguinToast!)
  • Updated helm chart to use more lenient timeouts for liveness probes on user code deployments (thanks @PenguinToast!)

Bugfixes

  • [Helm/K8s] Due to Flower being incompatible with Celery 5.0, the Helm chart for Dagster now uses a specific image mher/flower:0.9.5 for the Flower pod.

0.9.20#

New

  • [Dagit] Show recent runs on individual schedule pages
  • [Dagit] It’s no longer required to run dagster schedule up or press the Reconcile button before turning on a new schedule for the first time
  • [Dagit] Various improvements to the asset view. Expanded the Last Materialization Event view. Expansions to the materializations over time view, allowing for both a list view and a graphical view of materialization data.

Community Contributions

  • Updated many dagster-aws tests to use mocked resources instead of depending on real cloud resources, making it possible to run these tests locally. (thanks @jmsanders!)

Bugfixes

  • fixed an issue with retries in step launchers
  • [Dagit] bugfixes and improvements
  • Fixed an issue where dagit sometimes left hanging processes behind after exiting

Experimental

  • [K8s] The dagster daemon is now optionally deployed by the helm chart. This enables run-level queuing with the QueuedRunCoordinator.

0.9.19#

New

  • Improved error handling when the intermediate storage stores and retrieves objects.
  • New URL scheme in Dagit, with repository details included on all paths for pipelines, solids, and schedules
  • Relaxed constraints for the AssetKey constructor, to enable arbitrary strings as part of the key path.
  • When executing a subset of a pipeline, configuration that does not apply to the current subset but would be valid in the original pipeline is now allowed and ignored.
  • GCSComputeLogManager was added, allowing for compute logs to be persisted to Google cloud storage
  • The step-partition matrix in Dagit now auto-reloads runs

Bugfixes

  • Dagit bugfixes and improvements
  • When specifying a namespace during helm install, the same namespace will now be used by the K8sScheduler or K8sRunLauncher, unless overridden.
  • @pipeline decorated functions with -> None typing no longer cause unexpected problems.
  • Fixed an issue where compute logs might not always be complete on Windows.

0.9.18#

Breaking Changes

  • CliApiRunLauncher and GrpcRunLauncher have been combined into DefaultRunLauncher. If you had one of these run launchers in your dagster.yaml, replace it with DefaultRunLauncher or remove the run_launcher: section entirely.

New

  • Added a type loader for typed dictionaries: can now load typed dictionaries from config.

Bugfixes

  • Dagit bugfixes and improvements
    • Added error handling for repository errors on startup and reload
    • Repaired timezone offsets
    • Fixed pipeline explorer state for empty pipelines
    • Fixed Scheduler table
  • User-defined k8s config in the pipeline run tags (with key dagster-k8s/config) will now be passed to the k8s jobs when using the dagster-k8s and dagster-celery-k8s run launchers. Previously, only user-defined k8s config in the pipeline definition’s tag was passed down.

Experimental

  • Run queuing: the new QueuedRunCoordinator enables limiting the number of concurrent runs. The DefaultRunCoordinator launches jobs directly from Dagit, preserving existing behavior.

0.9.17#

New

  • [dagster-dask] Allow connecting to an existing scheduler via its address
  • [dagster-aws] Importing dagster_aws.emr no longer transitively importing dagster_spark
  • [dagster-dbr] CLI solids now emit materializations

Community contributions

  • Docs fix (Thanks @kaplanbora!)

Bug fixes

  • PipelineDefinition 's that do not meet resource requirements for its types will now fail at definition time
  • Dagit bugfixes and improvements
  • Fixed an issue where a run could be left hanging if there was a failure during launch

Deprecated

  • We now warn if you return anything from a function decorated with @pipeline. This return value actually had no impact at all and was ignored, but we are making changes that will use that value in the future. By changing your code to not return anything now you will avoid any breaking changes with zero user-visible impact.