apache/airflow

Improve Databricks operators with query tags

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#66,839 创建于 2026年5月13日

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 (5 评论) (0 反应) (0 负责人)Python (44,809 star) (16,781 fork)batch import
good first issuekind:featureprovider:databricks

描述

Description

Databricks supports query tags which allows us to track where the source of a query is on Databricks UI. Reference: https://docs.databricks.com/aws/en/sql/user/queries/query-tags

Currently when a query is sent to Databricks, on Databricks UI, the only info we can see is the query is from Airflow, but there is no other metadata like airflow dag id, task id, run id and etc.

Use case/motivation

With query tags instrumented, it will be easy for organizations to track and do Databricks cost contribution across different Airflow DAGs.

Related issues

No response

Are you willing to submit a PR?

  • Yes I am willing to submit a PR!

Code of Conduct

贡献者指南

技术栈
python
领域
backenddata
议题类型
feature
难度面向新贡献者的预计实现难度，1 表示很小改动，5 表示专家级工作。
3
预计时间有经验贡献者完成调查、实现、测试并准备 pull request 的粗略时间范围。
1-2 days
活动状态议题当前的可参与程度：新鲜、活跃、陈旧、阻塞或等待维护者输入。
active
清晰度议题是否清楚说明期望改动、验收标准和下一步。
clear
前置要求
Basic understanding of Apache Airflow operatorsFamiliarity with Databricks SQLPython programming
新手友好度1-100 的估计分数，表示该议题对首次贡献者的友好程度。
50
研究方向
Examine the existing Databricks operators in the Airflow providers package (e.g., airflow/providers/databricks/operators/). Understand the query tag documentation from Databricks to see how tags are passed. Consider adding a parameter to the operators for query tags and ensure they are attached to each query execution. Check for any existing PRs or discussions on the issue for implementation details.