cronitor pin to allow versions >= 5.0.1 to enable use of DayOfWeek as 7. Cronitor 4.0.0 is still disallowed. (Thanks, @joshuataylor!)checkDbReadyInitContainer to optionally disable db check initContainer.kind tags. (Thanks, @dragos-pop!)Re-executions.kind tag for display in the UI.DataprocResource now receives an optional parameter labels to be attached to Dataproc clusters. (Thanks, @thiagoazcampos!)checkDbReadyInitContainer flag to the Dagster Helm chart to allow disabling the default init container behavior. (Thanks, @easontm!)build_materialize_workbook_assets_definition which can be used to build assets that run materialize schedules for a Sigma workbook.SnowflakeResource and SnowflakeIOManager both accept additional_snowflake_connection_args config. This dictionary of arguments will be passed to the snowflake.connector.connect method. This config will be ignored if you are using the sqlalchemy connector.BackfillPolicy are now evaluated correctly during backfills. Self dependent assets no longer result in serial partition submissions or disregarded upstream dependencies.PipesCloudWatchMessageReader correctly identifies streams which are not ready yet and doesn't fail on ThrottlingException. (Thanks, @jenkoian!)FivetranWorkspace.sync_and_poll(...).fetch_column_metadata().dlt_assets API docs. (Thanks, @zilto!)dagster/run-id, dagster/code-location, dagster/user and Dagster Cloud environment variables) typically attached to external resources are now available under DagsterRun.dagster_execution_info.SensorReturnTypesUnion is now exported for typing the output of sensor functions.@fivetran_assets decorator.load_fivetran_asset_specs has been updated to accept an instance of DagsterFivetranTranslator or custom subclass.fivetran_assets decorator was added. It can be used with the FivetranWorkspace resource and DagsterFivetranTranslator translator to load Fivetran tables for a given connector as assets in Dagster. The build_fivetran_assets_definitions factory can be used to create assets for all the connectors in your Fivetran workspace.ECSPipesClient.run now waits up to 70 days for tasks completion (waiter parameters are configurable) (Thanks @jenkoian!)load_airbyte_cloud_asset_specs function has
been added. It can be used with the AirbyteCloudWorkspace resource and DagsterAirbyteTranslator translator to load your Airbyte Cloud connection streams as external assets in Dagster.icechunk kind.ConsolidatedSqliteEventLogStorage, which is mostly used for tests.1.6.0 may need to run dagster instance migrate to enable.map_asset_specs to enable modifying AssetSpecs and AssetsDefinitions in bulk.AssetSpec.replace_attributes and AssetSpec.merge_attributes to easily alter properties of an asset spec.PipesS3MessageReader now has a new parameter include_stdio_in_messages which enables log forwarding to Dagster via Pipes messages.log_external_stream has been added. It can be used to forward external logs to Dagster via Pipes messages.load_powerbi_asset_specs(..., use_workspace_scan=False).dagster-sigma snapshot command, allowing Sigma workspaces to be captured to a file for faster subsequent loading.DagsterExecutionStepNotFoundError errors when trying to execute an asset check step of a run launched by a backfill.owners added to AssetOuts when defining a @graph_multi_asset were not added to the underlying AssetsDefinition.& or | operators on AutomationConditions with labels would cause that label to be erased.SigmaFilter no longer fetch lineage information.DagsterPowerBITranslator.get_asset_key is deprecated in favor of DagsterPowerBITranslator.get_asset_spec().keyDagsterLookerApiTranslator.get_asset_key is deprecated in favor of DagsterLookerApiTranslator.get_asset_spec().keyDagsterSigmaTranslator.get_asset_key is deprecated in favor of DagsterSigmaTranslator.get_asset_spec().keyDagsterTableauTranslator.get_asset_key is deprecated in favor of DagsterTableauTranslator.get_asset_spec().keyAdded run_id to the run_tags index to improve database performance. Run dagster instance migrate to update the index. (Thanks, @HynekBlaha!)
Added icons for kind tags: Cassandra, ClickHouse, CockroachDB, Doris, Druid, Elasticsearch, Flink, Hadoop, Impala, Kafka, MariaDB, MinIO, Pinot, Presto, Pulsar, RabbitMQ, Redis, Redpanda, ScyllaDB, Starrocks, and Superset. (Thanks, @swrookie!)
Added a new icon for the Denodo kind tag. (Thanks, @tintamarre!)
Errors raised from defining more than one Definitions object at module scope now include the object names so that the source of the error is easier to determine.
[ui] Asset metadata entries like dagster/row_count now appear on the events page and are properly hidden on the overview page when they appear in the sidebar.
[dagster-aws] PipesGlueClient now attaches AWS Glue metadata to Dagster results produced during Pipes invocation.
[dagster-aws] PipesEMRServerlessClient now attaches AWS EMR Serverless metadata to Dagster results produced during Pipes invocation and adds Dagster tags to the job run.
[dagster-aws] PipesECSClient now attaches AWS ECS metadata to Dagster results produced during Pipes invocation and adds Dagster tags to the ECS task.
[dagster-aws] PipesEMRClient now attaches AWS EMR metadata to Dagster results produced during Pipes invocation.
[dagster-databricks] PipesDatabricksClient now attaches Databricks metadata to Dagster results produced during Pipes invocation and adds Dagster tags to the Databricks job.
[dagster-fivetran] Added load_fivetran_asset_specs function. It can be used with the FivetranWorkspace resource and DagsterFivetranTranslator translator to load your Fivetran connector tables as external assets in Dagster.
[dagster-looker] Errors are now handled more gracefully when parsing derived tables.
[dagster-sigma] Sigma assets now contain extra metadata and kind tags.
[dagster-sigma] Added support for direct workbook to warehouse table dependencies.
[dagster-sigma] Added include_unused_datasets field to SigmaFilter to disable pulling datasets that aren't used by a downstream workbook.
[dagster-sigma] Added skip_fetch_column_data option to skip loading Sigma column lineage. This can speed up loading large instances.
[dagster-sigma] Introduced an experimental dagster-sigma snapshot command, allowing Sigma workspaces to be captured to a file for faster subsequent loading.
dagster-airlift (experimental)#dagster-airlift is coming out of stealth. See the initial Airlift RFC here, and the following documentation to learn more:
More Airflow-related content is coming soon! We'd love for you to check it out, and post any comments / questions in the #airflow-migration channel in the Dagster slack.
monitor_all_code_locations and monitored_jobs did not raise the expected error. (Thanks, @apetryla!)AutomationCondition.any_deps_match() and AutomationCondition.all_deps_match() to render incorrectly when allow_selection or ignore_selection were set.CacheableAssetsDefinitions in code locations that contained AutomationConditionsToo many open files errors for jobs with many steps.dagster-dingtalk to the list of community supported libraries.dagster-wandb (Weights and Biases) documentation. (Thanks, @matt-weingarten!)dagster-sigma documentation.AssetOut.from_spec, that will construct an AssetOut from an AssetSpec.Column name section of the asset overview page.gcs (Google Cloud Storage) kind tag.report and semanticmodel kind tags.EcsRunLauncher. (Thanks, @zyd14!)DagsterDbtTranslator.get_code_version to customize the code version for your dbt assets. (Thanks, @Grzyblon!)PipesClientCompletedInvocation. This metadata will be attached to all materializations and asset checks stored during the pipes invocation.AutomationCondition.execution_in_progress which would cause it to evaluate to True for unpartitioned assets that were part of a run that was in progress, even if the asset itself had already been materialized.AutomationCondition.run_in_progress that would cause it to ignore queued runs.default_automation_condition_sensor to be constructed for user code servers running on dagster version < 1.9.0 even if the legacy auto_materialize: use_sensors configuration setting was set to False.0 in cases where all partitions were evaluated./ characters now work correctly with Dagster Pipes.dagster-airlift.types-sqlalchemy package is no longer included in the dagster[pyright] extra package.dagster project scaffold now has an option to create dagster projects from templates with excluded files/filepaths.parse_tableau_external_and_materializable_asset_specs is now available to parse a list of Tableau asset specs into a list of external asset specs and materializable asset specs.DagsterFivetranTranslator to customize assets loaded from Fivetran.dagster_snowflake.fetch_last_updated_timestamps now supports ignoring tables not found in Snowflake instead of raising an error.default_automation_condition_sensor to be constructed for user code servers running on dagster version < 1.9.0 even if the legacy auto_materialize: use_sensors configuration setting was set to False.dagster instance migrate on Dagster version 1.9.0 constructed a SQL query that exceeded the maximum allowed depth.ImportErrors are no longer raised when bigquery libraries are not installed [#25708]NoOpComputeLogManager. It did not make sense to default to the LocalComputeLogManager as pipeline runs are executed in ephemeral jobs, so logs could not be retrieved once these jobs were cleaned up. To have compute logs in a Kubernetes environment, users should configure a compute log manager that uses a cloud provider.dbt_pipeline to the hacker news example repo, which demonstrates how to run a dbt project within a Dagster pipeline.k8s_job_executor to match the configuration set in the K8sRunLauncher.DAGSTER_GRPC_MAX_RX_BYTES environment variable.dagster instance migrate when the asset catalog contains wiped assets.--models, --select, or --exclude flags while configuring the dbt_cli_resource, it will no longer attempt to supply these flags to commands that don’t accept them.yield_result wrote output value to the same file path if output names are the same for different solids.ops can now be used as a config entry in place of solids.EcsRunLauncher more resilient to ECS’ eventual consistency model.[@run_status_sensor](https://docs.dagster.io/_apidocs/schedules-sensors#dagster.run_status_sensor) which defines sensors that react to given PipelineRunStatus.solid on build_hook_context. This allows you to access the hook_context.solid parameter.dagster’s dependency on docstring-parser has been loosened.@pipeline now pulls its description from the doc string on the decorated function if it is provided.dagster new-project now no longer targets a non-existent mode.@repository functions.GraphDefinition.to_job now supports the description argument.AmazonECS_FullAccess policy. Now, the attached roles has been more narrowly scoped to only allow the daemon and dagit tasks to interact with the ECS actions required by the EcsRunLauncher.Error: Got unexpected extra arguments. Now, it ignores the entrypoint and launches succeed.dagster instance migrate.ScheduleDefinition constructor to instantiate a schedule definition, if a schedule name is not provided, the name of the schedule will now default to the pipeline name, plus “_schedule”, instead of raising an error.description and solid_retry_policy were getting dropped when using a solid_hook decorator on a pipeline definition (#4355).@pipeline_failure_sensor that prevented them from working.With the new first-class Pipeline Failure sensors, you can now write sensors to perform arbitrary actions when pipelines in your repo fail using @pipeline_failure_sensor. Out-of-the-box sensors are provided to send emails using make_email_on_pipeline_failure_sensor and slack messages using make_slack_on_pipeline_failure_sensor.
See the Pipeline Failure Sensor docs to learn more.
New first-class Asset sensors help you define sensors that launch pipeline runs or notify appropriate stakeholders when specific asset keys are materialized. This pattern also enables Dagster to infer cross-pipeline dependency links. Check out the docs here!
Solid-level retries: A new retry_policy argument to the @solid decorator allows you to easily and flexibly control how specific solids in your pipelines will be retried if they fail by setting a RetryPolicy.
Writing tests in Dagster is now even easier, using the new suite of direct invocation apis. Solids, resources, hooks, loggers, sensors, and schedules can all be invoked directly to test their behavior. For example, if you have some solid my_solid that you'd like to test on an input, you can now write assert my_solid(1, "foo") == "bar" (rather than explicitly calling execute_solid()).
[Experimental] A new set of experimental core APIs. Among many benefits, these changes unify concepts such as Presets and Partition sets, make it easier to reuse common resources within an environment, make it possible to construct test-specific resources outside of your pipeline definition, and more. These changes are significant and impactful, so we encourage you to try them out and let us know how they feel! You can learn more about the specifics here
[Experimental] There’s a new reference deployment for running Dagster on AWS ECS and a new EcsRunLauncher that launches each pipeline run in its own ECS Task.
[Experimental] There’s a new k8s_job_executor (https://docs.dagster.io/_apidocs/libraries/dagster-k8s#dagster_k8s.k8s_job_executor)which executes each solid of your pipeline in a separate Kubernetes job. This addition means that you can now choose at runtime (https://docs.dagster.io/deployment/guides/kubernetes/deploying-with-helm#executor) between single pod and multi-pod isolation for solids in your run. Previously this was only configurable for the entire deployment- you could either use the K8sRunLauncher with the default executors (in process and multiprocess) for low isolation, or you could use the CeleryK8sRunLauncher with the celery_k8s_job_executor for pod-level isolation. Now, your instance can be configured with the K8sRunLauncher and you can choose between the default executors or the k8s_job_executor.
Using the @schedule, @resource, or @sensor decorator no longer requires a context parameter. If you are not using the context parameter in these, you can now do this:
@schedule(cron_schedule="\* \* \* \* \*", pipeline_name="my_pipeline") def my_schedule(): return {} @resource def my_resource(): return "foo" @sensor(pipeline_name="my_pipeline") def my_sensor(): return RunRequest(run_config={})
Dynamic mapping and collect features are no longer marked “experimental”. DynamicOutputDefinition and DynamicOutput can now be imported directly from dagster.
Added repository_name property on SensorEvaluationContext, which is name of the repository that the sensor belongs to.
get_mapping_key is now available on SolidExecutionContext , allowing for discerning which downstream branch of a DynamicOutput you are in.
When viewing a run in Dagit, you can now download its debug file directly from the run view. This can be loaded into dagit-debug.
[dagster-dbt] A new dbt_cli_resource simplifies the process of working with dbt projects in your pipelines, and allows for a wide range of potential uses. Check out the integration guide for examples!
k8s_job_executor that caused solid tag user defined Kubernetes config to not be applied to the Kubernetes jobs.The deprecated SystemCronScheduler and K8sScheduler schedulers have been removed. All schedules are now executed using the dagster-daemon proess. See the deployment docs for more information about how to use the dagster-daemon process to run your schedules.
If you have written a custom run launcher, the arguments to the launch_run function have changed in order to enable faster run launches. launch_run now takes in a LaunchRunContext object. Additionally, run launchers should now obtain the PipelinePythonOrigin to pass as an argument to dagster api execute_run. See the implementation of DockerRunLauncher for an example of the new way to write run launchers.
[helm] .Values.dagsterDaemon.queuedRunCoordinator has had its schema altered. It is now referenced at .Values.dagsterDaemon.runCoordinator.
Previously, if you set up your run coordinator configuration in the following manner:
dagsterDaemon: queuedRunCoordinator: enabled: true module: dagster.core.run_coordinator class: QueuedRunCoordinator config: max_concurrent_runs: 25 tag_concurrency_limits: [] dequeue_interval_seconds: 30
It is now configured like:
dagsterDaemon: runCoordinator: enabled: true type: QueuedRunCoordinator config: queuedRunCoordinator: maxConcurrentRuns: 25 tagConcurrencyLimits: [] dequeueIntervalSeconds: 30
The method events_for_asset_key on DagsterInstance has been deprecated and will now issue a warning. This method was previously used in our asset sensor example code. This can be replaced by calls using the new DagsterInstance API get_event_records. The example code in our sensor documentation has been updated to use our new APIs as well.