This section explains how to accomplish common tasks in Dagster and showcases Dagster's experimental features.
|Versioning and Memoization||This guide describes how to use Dagster's versioning and memoization features. |
|Lakehouse||This guide describes how to use Dagster Lakehouse. |
|Lakehouse with Pandas and PySpark||This guide describes how to use Dagster Lakehouse with Pandas and PySpark. |
|Run Attribution||This guide describes how to perform Run Attribution by using a Custom Run Coordinator |
|Migrating to Graphs, Jobs, and Ops||This guide describes how to migrate the new Graph, Job, and Op APIs |
|Re-execution||This guide describes how to re-execute a pipeline within Dagit and using Dagster's APIs.|
|Fully-Featured Example Project||This guide describes the Hacker News example project, which takes advantage of many of Dagster's features|