AssetKeys to solid outputs through either the OutputDefinition or IOManager, which allows Dagster to automatically generate asset lineage information for assets referenced in this way. Direct parents of an asset will appear in the Dagit Asset Catalog. See the asset docs to learn more.DynamicOutput and map from the last release, this release includes the ability to collect over dynamically mapped outputs. You can see an example here.partition_days_offset argument to the @daily_schedule decorator that allows you to customize which partition is used for each execution of your schedule. The default value of this parameter is 1, which means that a schedule that runs on day N will fill in the partition for day N-1. To create a schedule that uses the partition for the current day, set this parameter to 0, or increase it to make the schedule use an earlier day’s partition. Similar arguments have also been added for the other partitioned schedule decorators (@monthly_schedule, @weekly_schedule, and @hourly_schedule).ardescription parameter that takes in a human-readable string description and displays it on the corresponding landing page in Dagit.AssetMaterialization now accepts a tags argument. Tags can be used to filter assets in Dagit.QueuedRunCoordinator daemon is now more resilient to errors while dequeuing runs. Previously runs which could not launch would block the queue. They will now be marked as failed and removed from the queue.dagster-daemon process uses fewer resources and spins up fewer subprocesses to load pipeline information. Previously, the scheduler, sensor, and run queue daemon each spun up their own process for this–now they share a single process.dagster-daemon process now runs each of its daemons in its own thread. This allows the scheduler, sensor loop, and daemon for launching queued runs to run in parallel, without slowing each other down.workspace.yaml file to load your pipelines, you can now specify an environment variable for the server’s hostname and port.dagster run delete CLI command to delete a run and its associated event log entries.fs_io_manager now defaults the base directory to base_dir via the Dagster instance’s local_artifact_storage configuration. Previously, it defaulted to the directory where the pipeline was executed.handle_output, load_input, or a type check function, the log output now includes context about which input or output the error occurred during.BoolSource config type (similar to the StringSource type). The config value for this type can be a boolean literal or a pointer to an environment variable that is set to a boolean value.DagsterNoStepsToExecuteException.OutputContext passed to the has_output method of MemoizableIOManager now includes a working log.workspace.yaml file without restarting Dagit. To reload your workspace, navigate to the Status page and press the “Reload all” button in the Workspace section.step and type filtering now offers fuzzy search, all log event types are now searchable, and visual bugs within the input have been repaired. Additionally, the default setting for “Hide non-matches” has been flipped to true.grpc_server repository location, Dagit will automatically detect changes and prompt you to reload when the remote server updates.dagster asset wipe.snowflake_resource can now be configured to use the SQLAlchemy connector (thanks @basilvetas!)seed and docs generate are now available as solids in the library dagster-dbt. (thanks @dehume-drizly!)dagster-spark config schemas now support loading values for all fields via environment variables.gcs_pickle_io_manager now also retries on 403 Forbidden errors, which previously would only retry on 429 TooManyRequests.K8sRunLauncher and CeleryK8sRunLauncher no longer reload the pipeline being executed just before launching it. The previous behavior ensured that the latest version of the pipeline was always being used, but was inconsistent with other run launchers. Instead, to ensure that you’re running the latest version of your pipeline, you can refresh your repository in Dagit by pressing the button next to the repository name.userDeployments.deployments in the Helm chart, replicaCount now defaults to 1 if not specified.dagster/dagster-k8s and dagster/dagster-celery-k8s can be used for all processes which don't require user code (Dagit, Daemon, and Celery workers when using the CeleryK8sExecutor). user-code-example can be used for a sample user repository. The prior images (k8s-dagit, k8s-celery-worker, k8s-example) are deprecated.dagster-k8s, dagster-celery-k8s, user-code-example, and k8s-dagit-example images to a public ECR registry in addition to DockerHub. If you are encountering rate limits when attempting to pull images from DockerHub, you should now be able to pull these images from public.ecr.aws/dagster..Values.dagsterHome is now a global variable, available at .Values.global.dagsterHome..Values.global.postgresqlSecretName has been introduced, for subcharts to access the Dagster Helm chart’s generated Postgres secret properly..Values.userDeployments has been renamed .Values.dagster-user-deployments to reference the subchart’s values. When using Dagster User Deployments, enabling .Values.dagster-user-deployments.enabled will create a workspace.yaml for Dagit to locate gRPC servers with user code. To create the actual gRPC servers, .Values.dagster-user-deployments.enableSubchart should be enabled. To manage the gRPC servers in a separate Helm release, .Values.dagster-user-deployments.enableSubchart should be disabled, and the subchart should be deployed in its own helm release.Schedules now run in UTC (instead of the system timezone) if no timezone has been set on the schedule. If you’re using a deprecated scheduler like SystemCronScheduler or K8sScheduler, we recommend that you switch to the native Dagster scheduler. The deprecated schedulers will be removed in the next Dagster release.
Names provided to alias on solids now enforce the same naming rules as solids. You may have to update provided names to meet these requirements.
The retries method on Executor should now return a RetryMode instead of a Retries. This will only affect custom Executor classes.
Submitting partition backfills in Dagit now requires dagster-daemon to be running. The instance setting in dagster.yaml to optionally enable daemon-based backfills has been removed, because all backfills are now daemon-based backfills.
# removed, no longer a valid setting in dagster.yaml backfill: daemon_enabled: true
The corresponding value flag dagsterDaemon.backfill.enabled has also been removed from the Dagster helm chart.
dagster.yaml has been removed. The sensor daemon now runs in a continuous loop so this customization is no longer useful.# removed, no longer a valid setting in dagster.yaml sensor_settings: interval_seconds: 10
instance argument to RunLauncher.launch_run has been removed. If you have written a custom RunLauncher, you’ll need to update the signature of that method. You can still access the DagsterInstance on the RunLauncher via the _instance parameter.has_config_entry, has_configurable_inputs, and has_configurable_outputs properties of solid and composite_solid have been removed.name argument to PipelineDefinition has been removed, and the argument is now required.execute_run_with_structured_logs and execute_step_with_structured_logs internal CLI entry points have been removed. Use execute_run or execute_step instead.python_environment key has been removed from workspace.yaml. Instead, to specify that a repository location should use a custom python environment, set the executable_path key within a python_file, python_module, or python_package key. See the docs for more information on configuring your workspace.yaml file.read or to keys accordingly.Bugfixes
Community Contributions
seed and docs generate are now available as solids in the
library dagster-dbt. (thanks @dehume-drizly!)New
Dagit now has a global search feature in the left navigation, allowing you to jump quickly to pipelines, schedules, and sensors across your workspace. You can trigger search by clicking the search input or with the / keyboard shortcut.
Timestamps in Dagit have been updated to be more consistent throughout the app, and are now localized based on your browser’s settings.
Adding SQLPollingEventWatcher for alternatives to filesystem or DB-specific listen/notify
functionality
We have added the BoolSource config type (similar to the StringSource type). The config value for
this type can be a boolean literal or a pointer to an environment variable that is set to a boolean
value.
The QueuedRunCoordinator daemon is now more resilient to errors while dequeuing runs. Previously
runs which could not launch would block the queue. They will now be marked as failed and removed
from the queue.
When deploying your own gRPC server for your pipelines, you can now specify that connecting to that
server should use a secure SSL connection. For example, the following workspace.yaml file specifies
that a secure connection should be used:
load_from: - grpc_server: host: localhost port: 4266 location_name: "my_grpc_server" ssl: true
The dagster-daemon process uses fewer resources and spins up fewer subprocesses to load pipeline
information. Previously, the scheduler, sensor, and run queue daemon each spun up their own process
for this–now they share a single process.
Integrations
dagster-k8s, dagster-celery-k8s, user-code-example, and
k8s-dagit-example images to a public ECR registry in addition to DockerHub. If you are
encountering rate limits when attempting to pull images from DockerHub, you should now be able to
pull these images from public.ecr.aws/dagster.dagster-spark config schemas now support loading values for all fields via
environment variables.Bugfixes
redis.internal
is set to True in helm chart.dagster-daemon process sometimes left dangling subprocesses running
during sensor execution, causing excess resource usage.tag method on solid invocations (as opposed to solid
definitions) are now correctly propagated during execution. They were previously being ignored.Experimental
MySQL (via dagster-mysql) is now supported as a backend for event log, run, & schedule storages. Add the following to your dagster.yaml to use MySQL for storage:
run_storage: module: dagster_mysql.run_storage class: MySQLRunStorage config: mysql_db: username: { username } password: { password } hostname: { hostname } db_name: { database } port: { port } event_log_storage: module: dagster_mysql.event_log class: MySQLEventLogStorage config: mysql_db: username: { username } password: { password } hostname: { hostname } db_name: { db_name } port: { port } schedule_storage: module: dagster_mysql.schedule_storage class: MySQLScheduleStorage config: mysql_db: username: { username } password: { password } hostname: { hostname } db_name: { db_name } port: { port }
New
dagster instance migrate to upgrade.step and type filtering now offer fuzzy search, all log event types are now searchable, and visual bugs within the input have been repaired. Additionally, the default setting for “Hide non-matches” has been flipped to true.dagster-daemon process now runs faster when running multiple schedulers or sensors from the same repository.fs_io_manager now defaults the base directory to base_dir via the Dagster instance’s local_artifact_storage configuration. Previously, it defaults to the directory where the pipeline is executed.versioned_filesystem_io_manager and custom_path_fs_io_manager now require base_dir as part of the resource configs. Previously, the base_dir defaulted to the directory where the pipeline was executed.dagster instance migrate and configuring your instance with the following settings in dagster.yaml:There is a corresponding flag in the Dagster helm chart to enable this instance configuration. See the Helm chart’s values.yaml file for more information.
description parameter that takes in a human-readable string description and displays it on the corresponding landing page in Dagit.Integrations
gcs_pickle_io_manager now also retries on 403 Forbidden errors, which previously would only retry on 429 TooManyRequests.Bug Fixes
Tuple with nested inner types in solid definitions no longer causes GraphQL errorsdagster new-repo should now properly generate subdirectories and files, without needing to install dagster from source (e.g. with pip install --editable).Dependencies
pendulum datetime/timezone library.Documentation
New
dagster run delete CLI command to delete a run and its associated event log entries.partition_days_offset argument to the @daily_schedule decorator that allows you to customize which partition is used for each execution of your schedule. The default value of this parameter is 1, which means that a schedule that runs on day N will fill in the partition for day N-1. To create a schedule that uses the partition for the current day, set this parameter to 0, or increase it to make the schedule use an earlier day’s partition. Similar arguments have also been added for the other partitioned schedule decorators (@monthly_schedule, @weekly_schedule, and @hourly_schedule).dagster new-repo command now includes a workspace.yaml file for your new repository.workspace.yaml file to load your pipelines, you can now specify an environment variable for the server’s hostname and port. For example, this is now a valid workspace:load_from: - grpc_server: host: env: FOO_HOST port: env: FOO_PORT
Integrations
K8sRunLauncher and CeleryK8sRunLauncher no longer reload the pipeline being executed just before launching it. The previous behavior ensured that the latest version of the pipeline was always being used, but was inconsistent with other run launchers. Instead, to ensure that you’re running the latest version of your pipeline, you can refresh your repository in Dagit by pressing the button next to the repository name.Bug Fixes
--path-prefix option. This has been fixed.ModeDefinition that contains a single executor, that executor is now selected by default.reconstructable on pipelines with that were also decorated with hooks no longer raises an error.dagster-daemon liveness-check command previously returned false when daemons surfaced non-fatal errors to be displayed in Dagit, leading to crash loops in Kubernetes. The command has been fixed to return false only when the daemon has stopped running.OutputDefinitions with io_manager_keys, or InputDefinitions with root_manager_keys, but any of the modes provided for the pipeline definition do not include a resource definition for the required key, Dagster now raises an error immediately instead of when the pipeline is executed.dagster-dbt has been updated to handle the new run_results.json schema for dbt 0.19.0.Dependencies
Documentation