帮助将 Databricks 笔记本、作业与数据路径系统迁移到 Microsoft Fabric。
复制安装指令,让 AI 自动完成配置 · 推荐新手
请帮我安装 askskill 上的 "databricks-migration" 技能: 1. 下载 https://raw.githubusercontent.com/microsoft/skills-for-fabric/main/skills/databricks-migration/SKILL.md 2. 保存为 ~/.claude/skills/databricks-migration/SKILL.md 3. 装好后重载技能,告诉我可以用了
请把下面 Databricks notebook 代码迁移到 Microsoft Fabric,重点将 dbutils.fs、dbutils.secrets、dbutils.notebook 和库安装方式替换为 Fabric 对应方案,并解释每处改动。
输出迁移后的 Fabric 代码,并附带逐项替换说明与注意事项。
我需要把 Databricks 中使用 Unity Catalog 三层命名空间和 DBFS 路径的脚本迁移到 Fabric。请将 catalog.schema.table 映射为 Lakehouse 可用结构,并把 DBFS 路径改写为 OneLake 路径或 Shortcut 方案。
给出表命名映射规则、路径改写结果,以及不兼容点处理建议。
请把这个 Databricks Job 和 Delta Live Tables 流水线迁移到 Microsoft Fabric,转换为 Spark Job Definition 或 Fabric 中可行的替代实现,并指出 MLflow、Photon、参数传递相关调整。
输出迁移后的作业设计方案、步骤映射表,以及功能差异说明。
Update Check — ONCE PER SESSION (mandatory) The first time this skill is used in a session, run the check-updates skill before proceeding.
- GitHub Copilot CLI / VS Code: invoke the
check-updatesskill.- Claude Code / Cowork / Cursor / Windsurf / Codex: compare local vs remote package.json version.
- Skip if the check was already performed earlier in this session.
CRITICAL NOTES
- To find workspace details (including its ID) from a workspace name: list all workspaces, then use JMESPath filtering
- To find item details (including its ID) from workspace ID, item type, and item name: list all items of that type in that workspace, then use JMESPath filtering
dbutils.widgetshas no direct equivalent in Fabric — use notebook parameters (cell tagparameters) ornotebookutils.runtime.contextfor context injectiondbutils.library(runtime library install) has no equivalent — use Fabric Environments for reproducible library management- Unity Catalog uses a 3-level namespace (
catalog.schema.table); Fabric Lakehouse uses 2-level (schema.tablewithin a named Lakehouse)
Read these companion documents before executing migration tasks:
az rest, az login, token acquisition, Fabric REST via CLIFor notebook and Lakehouse creation, see spark-authoring-cli. For Fabric Warehouse DDL/DML authoring, see sqldw-authoring-cli.
| Topic | Reference |
|---|---|
| Migration Workload Map | § Migration Workload Map |
Complete dbutils → notebookutils Mapping | dbutils-to-notebookutils.md |
| Unity Catalog → Fabric Lakehouse Schemas | catalog-migration.md |
| Before/After Code Patterns | code-patterns.md |
| Cluster Config → Fabric Spark Pools | § Cluster Config → Fabric Spark Pools |
| Databricks Jobs → Spark Job Definitions | § Databricks Jobs → Spark Job Definitions |
| Delta Sharing → OneLake Shortcuts | § Delta Sharing → OneLake Shortcuts |
| MLflow → Fabric ML Experiments | § MLflow → Fabric ML Experiments |
| Must / Prefer / Avoid | § Must / Prefer / Avoid |
| Authentication & Token Acquisition | COMMON-CORE.md § Authentication |
| Lakehouse Management | SPARK-AUTHORING-CORE.md § Lakehouse Management |
| Notebook Management | SPARK-AUTHORING-CORE.md § Notebook Management |
| Databricks Component | Fabric Target | Notes |
|---|---|---|
| All-purpose cluster (notebooks, REPL) | Fabric Notebook (Starter Pool or Custom Pool) | No persistent cluster — Fabric provisions compute on session start |
| Job cluster (automated jobs) | Spark Job Definition (SJD) | SJD maps one-to-one with Databricks Jobs on job clusters |
| Unity Catalog | Fabric Lakehouse (schema per namespace) | See catalog-migration.md |
| Databricks Repos (Git-backed notebooks) | Fabric Git Integration | Connect workspace to Azure DevOps or GitHub; notebooks are synced |
…
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