Have questions about how to use Dagster? Hit a bug? Have a feature request? The Dagster Labs team and the Dagster community make a best-effort attempt to respond on a few different platforms.
Where you go to get support can vary depending on what you want to accomplish. Refer to the following table for details about the resources available to you and when they should be used.
| I want to... | You should use... |
|---|---|
| Generally search for an answer on the internet | A search engine. Search engines like Google generally do a good job at surfacing relevant Dagster docs, Github Discussions, and Github Issues, so we recommend starting there. Unfortunately, ChatGPT is not currently a great resource for answering questions about Dagster because its training data doesn’t include Dagster’s latest APIs. |
| Use AI to self-serve | Dagster's trained Language Learning Model (LLM). Accessible in the Dagster Slack's #ask-ai channel or by clicking the Ask AI button on the docs site. |
| File a bug or feature request | GitHub Issues. We use GitHub Issues to track all community requests, whether they're created by Dagster team members or community members. If you find an issue that seems related to your situation but you're unsure, don't be shy! We can redirect it to a different issue if necessary. Check out the Tips section for tips on including code snippets and filing bugs. |
| Ask a question that may be helpful to others, or make a question visible to the Dagster team | GitHub Discussions. This is the main Q&A site for Dagster. We recommend posting most questions here as they'll show up in search engines and can then benefit others. Check out the Tips section for tips on including code snippets and how to ask questions that get answered. |
| Participate in real-time discussion with other Dagster users | Dagster community Slack. We strongly encourage you to join Dagster's Slack, as it's the main real-time gathering place for the community. Check out the Tips section for tips on including code snippets and how to ask questions that get answered. |
When posting in GitHub or Slack, including a code snippet can help others understand your question. Using Markdown to format the content as code improves readability. For example:
``` # backticks create a code block from dagster import ... ... ```
On GitHub - whether in issues or discussions - you can add syntax highlighting to code snippets to further improve readability. This is done by specifying the language at the top of the Markdown code block:
```python ## specifies language from dagster import ... ... ```
When filing a GitHub issue for a bug:
When posting questions in GitHub Discussions or Slack, we recommend:
Generally, the less time and effort it takes for someone to digest your question, the more likely it will get answered. Check out the following sections for examples of well-phrased questions and those that could use some improvement.
Question 1
Is it possible to set up Dagster to automatically update an entire downstream table every time that a specific partition of an upstream table is updated? We have a table that's partitioned by customer, and we have a specific analysis that we want to do on a specific customer.
✅ Good question!
This question is brief enough to be quickly digested, but specific enough to be complete.
Question 2
Is it possible to set up Dagster to automatically update an entire downstream table every time that a specific partition of an upstream table is updated? We have a table that's partitioned by customer, and we have a specific analysis that we want to do on a specific customer.
The background here is that that we've set up Fivetran to pulls in our per-customer Salesforce tables into one big Snowflake table. We have about 500 customers, and they get pulled in usually daily, but it depends on the customer. For about 20 of these customers, we have custom logic, implemented in SQL with dbt, that performs analyses that are specific to those customers. We want those analyses to run automatically when customer data is updated, so that our sales representatives can discover red flags when they check their Looker dashboards.
✅ Good question!
This version of the first question provides additional background information, but doesn't bury the core question. This can be helpful because it allows readers to more deeply understand the situation and provide broader suggestions.
Question 3
How do I use tables with specific upstream partitions?
❌ Needs improvement
This question needs more detail to allow the reader to provide appropriate suggestions.
Question 4
We've set up Fivetran to pulls in our per-customer Salesforce tables into one big Snowflake table. We have about 500 customers, and they get pulled in usually daily, but it depends on the customer. For about 20 of these customers, we have custom logic, implemented in SQL with dbt, that performs analyses that are specific to those customers. We want those analyses to run automatically when customer data is updated, so that our sales representatives can discover red flags when they check their Looker dashboards. How can I get this working with Dagster?
❌ Needs improvement
This question requires understanding an entire data pipeline to answer the core question.