AssetSelection.dagster-snowflake now requires snowflake-connector-python>=3.4.0@sling_assets accepts an optional name parameter for the underlying opdagster-openai library is now available.DagsterDbtTranslatorSettings called enable_duplicate_source_asset_keys that allows users to set duplicate asset keys for their dbt sources. Thanks @hello-world-bfree!ConfigurableResource.SlingConnectionResource where a blank keyword argument would be emitted as an environment variabledbt source freshness would cause an error.DbtArtifacts has been added for managing the behavior of rebuilding the manifest during development but expecting a pre-built one in production.send sample alert button now exists on both the alert policies page and in the alert policies editor to make it easier to debug and configure alerts without having to wait for an event to kick them off.SlingConnectionResource that raised an error when connecting to a database.graph_multi_assets with check_specs now support subsetting.run_retries.retry_on_op_or_asset_failures setting that can be set to false to make run retries only occur when there is an unexpected failure that crashes the run, allowing run-level retries to co-exist more naturally with op or asset retries. See the docs for more information.dagster dev now sets the environment variable DAGSTER_IS_DEV_CLI allowing subprocesses to know that they were launched in a development context.@multi_observable_source_asset decorator enables defining a set of assets that can be observed together with the same function.@sling_assets and Resource SlingConnectionResource have been added for the [dagster-embedded-elt.sling](http://dagster-embedded-elt.sling) package. Deprecated build_sling_asset, SlingSourceConnection and SlingTargetConnection.QueuedRunCoordinator.dagster-polars has been added as an integration. Thanks @danielgafni!@dbt_assets now supports loading projects with semantic models.@dbt_assets now supports loading projects with model versions.get_asset_key_for_model now supports retrieving asset keys for seeds and snapshots. Thanks @aksestok!@asset decorator causing a false positive in Pyright strict mode. Thanks @tylershunt!security_context field on the k8s_job_executor didn't correctly set the security context on the launched step pods. Thanks @krgn!ObserveResults with no data_version.FreshnessPolicys on observable source assets. These assets will be considered “Overdue” when the latest value for the “dagster/data_time” metadata value is older than what’s allowed by the freshness policy.DbtCliResource now include metadata from the dbt adapter response. This includes fields like rows_affected, query_id from the Snowflake adapter, or bytes_processed from the BigQuery adapter.k8s_job_executor.context.log.exception in a sensor or schedule did not properly capture exception information.@observable_source_asset-decorated functions can now return an ObserveResult. This allows including metadata on the observation, in addition to a data version. This is currently only supported for non-partitioned assets.AutoMaterializeRule.skip_on_not_all_parents_updated_since_cron class allows you to construct AutoMaterializePolicys which wait for all parents to be updated after the latest tick of a given cron schedule.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
Community Contributions
/License for packages that claim distribution under Apache-2.0 (thanks @bollwyvl!)New
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.configured api on solids now enforces name argument as positional. The name argument remains a keyword argument on executors. name argument has been removed from resources, and loggers to reflect that they are anonymous. Previously, you would receive an error message if the name argument was provided to configured on resources or loggers.minimum_interval_seconds field, the overall sensor daemon interval can now be configured in the dagster.yaml instance settings with:sensor_settings: interval_seconds: 30 # (default)
This changes the interval at which the daemon checks for sensors which haven't run within their minimum_interval_seconds.
TypeCheckdagster-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. The dagster-daemon process will shut down if any of the daemon threads crash or hang, so that the execution environment knows that it needs to be restarted.dagster new-repo is a new CLI command that generates a Dagster repository with skeleton code in your filesystem. This CLI command is experimental and it may generate different files in future versions, even between dot releases. As of 0.10.5, dagster new-repo does not support Windows. See here for official API docs.grpc_server repository location, Dagit will automatically detect changes and prompt you to reload when the remote server updates.Integrations
Bugfixes
Bugfixes