Examples
This section contains examples of how to use Dagster. All examples can be found on Github.
| Name | Description | |
|---|---|---|
| Airflow Ingest | Create a pipeline from an Airflow DAG | Open |
| Airline Demo | A comprehensive demo to showcase Dagster and Dagit capabilities | Open |
| Asset Materialization | Record that a solid materialized an asset | Open |
| Conditional Execution | Conditionally execute part of a pipeline | Open |
| Config Mapping | Simplify solid config schemas with config mapping. | Open |
| dbt Integration | Use dagster-dbt to integrate dbt projects with Dagster | Open |
| Dependency DSL | Create a custom DSL for defining pipelines | Open |
| Docker Deployment | Example Docker Deployment | Open |
| EMR PySpark | Run a PySpark solids in EMR | Open |
| Execute Pipeline GraphQL | Trigger a Dagster pipeline externally by a GraphQL client | Open |
| Fan-In Dependency | Create a pipeline with a fan-in dependency | Open |
| Great Expectations integration | Use Great Expectations to check data quality | Open |
| Hooks | Create a pipeline with hooks | Open |
| Multi-Location Workspace | Setup a Dagster workspace with multiple locations | Open |
| No-Data Dependencies | Modeling dependencies without inputs and outputs | Open |
| Solid and Pipeline Tags | Create a pipeline with tags and a solid with tags | Open |
| Pipeline Unit Test | Unit-test a pipeline | Open |
| PySpark | Run PySpark code in solids | Open |
| User in the Loop | Set conditions for whether a pipeline should continue running | Open |
| Dynamic Graph (Experimental) | Determine graph structure at runtime | Open |
| Lakehouse (Experimental) | Define a computation graph in terms of the tables it produces | Open |
| Lakehouse w/ Two Types (Experimental) | Use the Lakehouse API with multiple compute types | Open |
| Memoization (Experimental) | Memoizing results from previous pipeline runs | Open |