AltimateAI / AltimateAI/altimate-code
Add Databricks API support for notebooks, jobs, and clusters
- 主要語言
- TypeScript
- 星號
- 811
- 分支
- 134
- 平均合併
- 3 天 2 小時
- 30 天內合併 PR
- 50
描述
No Databricks APIs are currently available for managing notebooks, jobs, or clusters. Specifically requested capabilities:
- Create/manage Databricks Notebooks (Workspace REST API)
- Create/manage Databricks Jobs/Workflows (Jobs API) for scheduling and orchestration
- Create/manage Delta Live Tables (DLT) pipelines
- Manage clusters/compute (Cluster API)
Currently, altimate-code can only interact with Databricks via SQL warehouse connections (sql_execute, schema_inspect, dbt models, cost/finops analysis, lineage). There's no way to programmatically create or manage notebooks, jobs, or clusters directly — users must generate the content as text and manually apply it via the Databricks UI or CLI. Native API integration for these would let altimate-code build and orchestrate full Databricks pipelines, not just SQL-layer transformations.
---
### Metadata
| Field | Value |
|-------|-------|
| CLI Version | 0.9.7 |
| Platform | darwin |
| Architecture | arm64 |
| OS Release | 25.5.0 |
| Category | feature |
貢獻指南
研究方向
Start by surveying the existing sql_execute, schema_inspect, dbt models, cost/finops, and lineage integrations to find the CLI's current Databricks connection points. Define the API entry points and tests for notebooks, jobs, DLT pipelines, and clusters; done means these resources can be managed programmatically rather than only generated for manual UI or CLI application.
由索引模型根據 Issue 內容生成。
評估
- 技術堆疊
- typescript
- 領域
- backend-api-design, cli, data-engineering
- Issue 類型
- 功能
- 難度
- 5/5
- 預估耗時
- 一週以上
- 活躍度
- 活躍
- 描述清晰度
- 需要釐清
- 新手友好度
- 30/100