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Interactively analyze lakehouse data with PySpark, Livy sessions, and Spark SQL.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "spark-consumption-cli" skill from askskill: 1. Download https://raw.githubusercontent.com/microsoft/skills-for-fabric/main/skills/spark-consumption-cli/SKILL.md 2. Save it as ~/.claude/skills/spark-consumption-cli/SKILL.md 3. Reload skills and tell me it's ready
Use PySpark in a Livy session to read sales and customer tables from two lakehouses, perform a cross-lakehouse join, calculate the top 10 customers by sales in the last 90 days for each region, and provide the DataFrame code plus a results summary.
Executable PySpark DataFrame code, key calculation steps, and a region-based summary of results.
Use Spark SQL or PySpark to compare yesterday's version of this Delta table with the current version, identify inserted, deleted, and changed records, and explain how to read historical versions via time travel in Fabric Lakehouse.
A historical-version access method, comparison code, and a summary of inserted, deleted, and changed records.
In a Livy session, use PySpark to read raw JSON data in a lakehouse, check for missing fields, type mismatches, duplicate records, and quality issues after flattening nested fields, then generate remediation suggestions.
JSON parsing and cleansing code, a summary of data quality findings, and actionable remediation suggestions.
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 the workspace details (including its ID) from workspace name: list all workspaces and, then, use JMESPath filtering
- To find the item details (including its ID) from workspace ID, item type, and item name: list all items of that type in that workspace and, then, use JMESPath filtering
| Task | Reference | Notes |
|---|---|---|
| Fabric Topology & Key Concepts | COMMON-CORE.md § Fabric Topology & Key Concepts | |
| Environment URLs | COMMON-CORE.md § Environment URLs | |
| Authentication & Token Acquisition | COMMON-CORE.md § Authentication & Token Acquisition | Wrong audience = 401; read before any auth issue |
| Core Control-Plane REST APIs | COMMON-CORE.md § Core Control-Plane REST APIs | |
| Pagination | COMMON-CORE.md § Pagination | |
| Long-Running Operations (LRO) | COMMON-CORE.md § Long-Running Operations (LRO) | |
| Rate Limiting & Throttling | COMMON-CORE.md § Rate Limiting & Throttling | |
| OneLake Data Access | COMMON-CORE.md § OneLake Data Access | Requires storage.azure.com token, not Fabric token |
| Job Execution | COMMON-CORE.md § Job Execution | |
| Capacity Management | COMMON-CORE.md § Capacity Management | |
| Gotchas & Troubleshooting | COMMON-CORE.md § Gotchas & Troubleshooting | |
| Best Practices | COMMON-CORE.md § Best Practices | |
| Tool Selection Rationale | COMMON-CLI.md § Tool Selection Rationale | |
| Finding Workspaces and Items in Fabric | COMMON-CLI.md § Finding Workspaces and Items in Fabric | Mandatory — READ link first [needed for finding workspace id by its name or item id by its name, item type, and workspace id] |
| Authentication Recipes | COMMON-CLI.md § Authentication Recipes | az login flows and token acquisition |
Fabric Control-Plane API via az rest | COMMON-CLI.md § Fabric Control-Plane API via az rest | Always pass --resource https://api.fabric.microsoft.com or az rest fails |
| Pagination Pattern | COMMON-CLI.md § Pagination Pattern | |
| Long-Running Operations (LRO) Pattern | COMMON-CLI.md § Long-Running Operations (LRO) Pattern | |
OneLake Data Access via curl | COMMON-CLI.md § OneLake Data Access via curl | Use curl not az rest (different token audience) |
| SQL / TDS Data-Plane Access | COMMON-CLI.md § SQL / TDS Data-Plane Access | sqlcmd (Go) connect, query, CSV export |
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Query Spark History Server apps, jobs, stages, and metrics in natural language.