spark-consumption-cli

---
name: spark-consumption-cli
description: >
license: MIT
---

> **Telemetry — MANDATORY.** Every `api.fabric.microsoft.com` call must carry
> `x-ms-fabric-skill: spark-consumption-cli` (`az rest`: `--headers "x-ms-fabric-skill=spark-consumption-cli"`),
> including every LRO poll, `fabric_lro` and retry. Snippets omit it — add it anyway.

> **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-updates` skill.
> - **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**
> 1. To find the workspace details (including its ID) from workspace name: list all workspaces and, then, use JMESPath filtering
> 2. 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

# Data Engineering Consumption — CLI Skill

## Table of Contents

| Task | Reference | Notes |
|---|---|---|
| Fabric Topology & Key Concepts | [COMMON-CORE.md § Fabric Topology & Key Concepts](../../common/COMMON-CORE.md#fabric-topology--key-concepts) ||
| Environment URLs | [COMMON-CORE.md § Environment URLs](../../common/COMMON-CORE.md#environment-urls) ||
| Authentication & Token Acquisition | [COMMON-CORE.md § Authentication & Token Acquisition](../../common/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](../../common/COMMON-CORE.md#core-control-plane-rest-apis) ||
| Pagination | [COMMON-CORE.md § Pagination](../../common/COMMON-CORE.md#pagination) ||
| Long-Running Operations (LRO) | [COMMON-CORE.md § Long-Running Operations (LRO)](../../common/COMMON-CORE.md#long-running-operations-lro) ||
| Rate Limiting & Throttling | [COMMON-CORE.md § Rate Limiting & Throttling](../../common/COMMON-CORE.md#rate-limiting--throttling) ||
| OneLake Data Access | [COMMON-CORE.md § OneLake Data Access](../../common/COMMON-CORE.md#onelake-data-access) | Requires `storage.azure.com` token, not Fabric token |
| Job Execution | [COMMON-CORE.md § Job Execution](../../common/COMMON-CORE.md#job-execution) ||
| Capacity Management | [COMMON-CORE.md § Capacity Management](../../common/COMMON-CORE.md#capacity-management) ||
| Gotchas & Troubleshooting | [COMMON-CORE.md § Gotchas & Troubleshooting](../../common/COMMON-CORE.md#gotchas--troubleshooting) ||
| Best Practices | [COMMON-CORE.md § Best Practices](../../common/COMMON-CORE.md#best-practices) ||
| Tool Selection Rationale | [COMMON-CLI.md § Tool Selection Rationale](../../common/COMMON-CLI.md#tool-selection-rationale) ||
| Finding Workspaces and Items in Fabric | [COMMON-CLI.md § Finding Workspaces and Items in Fabric](../../common/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](../../common/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](../../common/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](../../common/COMMON-CLI.md#pagination-pattern) ||
| Long-Running Operations (LRO) Pattern | [COMMON-CLI.md § Long-Running Operations (LRO) Pattern](../../common/COMMON-CLI.md#long-running-operations-lro-pattern) ||
| OneLake Data Access via `curl` | [COMMON-CLI.md § OneLake Data Access via curl](../../common/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](../../common/COMMON-CLI.md#sql--tds-data-plane-access) | `sqlcmd` (Go) connect, query, CSV export |
| Job Execution (CLI) | [COMMON-CLI.md § Job Execution](../../common/COMMON-CLI.md#job-execution) ||
| OneLake Shortcuts | [COMMON-CLI.md § OneLake Shortcuts](../../common/COMMON-CLI.md#onelake-shortcuts) ||
| Capacity Management (CLI) | [COMMON-CLI.md § Capacity Management](../../common/COMMON-CLI.md#capacity-management) ||
| Composite Recipes | [COMMON-CLI.md § Composite Recipes](../../common/COMMON-CLI.md#composite-recipes) ||
| Gotchas & Troubleshooting (CLI-Specific) | [COMMON-CLI.md § Gotchas & Troubleshooting (CLI-Specific)](../../common/COMMON-CLI.md#gotchas--troubleshooting-cli-specific) | `az rest` audience, shell escaping, token expiry |
| Quick Reference: `az rest` Template | [COMMON-CLI.md § Quick Reference: az rest Template](../../common/COMMON-CLI.md#quick-reference-az-rest-template) ||
| Quick Reference: Token Audience / CLI Tool Matrix | [COMMON-CLI.md § Quick Reference: Token Audience ↔ CLI Tool Matrix](../../common/COMMON-CLI.md#quick-reference-token-audience--cli-tool-matrix) | Which `--resource` + tool for each service |
| Relationship to SPARK-AUTHORING-CORE.md | [SPARK-CONSUMPTION-CORE.md § Relationship to SPARK-AUTHORING-CORE.md](../../common/SPARK-CONSUMPTION-CORE.md#relationship-to-spark-authoring-coremd) ||
| Data Engineering Consumption Capability Matrix | [SPARK-CONSUMPTION-CORE.md § Data Engineering Consumption Capability Matrix](../../common/SPARK-CONSUMPTION-CORE.md#data-engineering-consumption-capability-matrix) ||
| OneLake Table APIs (Schema-enabled Lakehouses) | [SPARK-CONSUMPTION-CORE.md § OneLake Table APIs (Schema-enabled Lakehouses)](../../common/SPARK-CONSUMPTION-CORE.md#onelake-table-apis-schema-enabled-lakehouses) | Unity Catalog-compatible metadata; requires `storage.azure.com` token |
| Lakehouse Livy Session Management | [SPARK-CONSUMPTION-CORE.md § Livy Session Management](../../common/SPARK-CONSUMPTION-CORE.md#livy-session-management) | Lakehouse Livy API: session creation, states, lifecycle, termination |
| Interactive Data Exploration | [SPARK-CONSUMPTION-CORE.md § Interactive Data Exploration](../../common/SPARK-CONSUMPTION-CORE.md#interactive-data-exploration) | Statement execution, output retrieval, data discovery |
| PySpark Analytics Patterns | [SPARK-CONSUMPTION-CORE.md § PySpark Analytics Patterns](../../common/SPARK-CONSUMPTION-CORE.md#pyspark-analytics-patterns) | Cross-lakehouse 3-part naming, performance optimization |
| Must/Prefer/Avoid | [SKILL.md § Must/Prefer/Avoid](#mustpreferavoid) | **MUST DO / AVOID / PREFER** checklists |
| Quick Start | [SKILL.md § Quick Start](#quick-start) | CLI-specific Lakehouse Livy session setup and data exploration |
| Key Fabric Patterns | [SKILL.md § Key Fabric Patterns](#key-fabric-patterns) | Spark pattern quick-reference table |
| Session Cleanup | [SKILL.md § Session Cleanup](#session-cleanup) | Clean up idle Lakehouse Livy sessions via CLI |

---

## Must/Prefer/Avoid

### MUST DO

- Check for existing idle sessions before creating new ones
- Use dynamic workspace/lakehouse discovery
- Follow API patterns from [COMMON-CLI.md](../../common/COMMON-CLI.md)

### PREFER

- **sqldw-consumption-cli for simple lakehouse queries** — row counts, SELECT, schema exploration, filtering, and aggregation on lakehouse Delta tables should use the SQL Endpoint via `sqlcmd`, not Spark. Only use this skill when the user explicitly requests PySpark, DataFrames, or Spark-specific features.
- SQL Endpoint for Delta tables
- Livy for unstructured/JSON data or complex Python analytics
- Session reuse over creation

### AVOID

- Hardcoded workspace IDs
- Creating unnecessary sessions
- Large result sets without LIMIT
- **Confusing Lakehouse Livy sessions with Notebook Spark sessions** — This skill covers **Lakehouse Livy sessions** (the public Livy API at `/lakehouses/{lhId}/livyapi/.../sessions`). Notebook Spark sessions are created internally when running a notebook via the Jobs API (`RunNotebook`) and are NOT managed through the Livy API. To run a notebook as a job, see SPARK-AUTHORING-CORE.md § Notebook Execution & Job Management
- **Writing or generating notebook cells** — prompts that ask for `%%sql`, `%%configure`, PySpark notebook cell code, notebook deployment, or notebook execution belong to `spark-authoring-cli`, even when the cell queries data.

---

## Quick Start

### Environment Setup

Apply environment detection from COMMON-CORE.md Environment Detection Pattern to set:
- `$FABRIC_API_BASE` and `$FABRIC_RESOURCE_SCOPE`
- `$FABRIC_API_URL` and `$LIVY_API_PATH` for Livy operations

**Authentication**: Use token acquisition from [COMMON-CLI.md](../../common/COMMON-CLI.md) Environment Detection and API Configuration

### Workspace & Item Discovery

**Preferred**: Use [COMMON-CLI.md](../../common/COMMON-CLI.md) item discovery patterns (Finding things in Fabric) to find workspaces and items by name.

**Fallback** (when workspace is already known):
```bash
# List workspaces
az rest --method get --resource "$FABRIC_RESOURCE_SCOPE" --url "$FABRIC_API_URL/workspaces" --query "value[].{name:displayName, id:id}" --output table
read -p "Workspace ID: " workspaceId

# List lakehouses in workspace
az rest --method get --resource "$FABRIC_RESOURCE_SCOPE" --url "$FABRIC_API_URL/workspaces/$workspaceId/items?type=Lakehouse" --query "value[].{name:displayName, id:id}" --output table  
read -p "Lakehouse ID: " lakehouseId
```

### Lakehouse Livy Session Management

> **Two types of Spark sessions in Fabric** — This skill manages **Lakehouse Livy sessions**, created via the public Livy API endpoint (`/lakehouses/{lhId}/livyapi/.../sessions`). These are ad-hoc interactive sessions for remote clients. **Notebook Spark sessions** are a separate mechanism — they are created internally when a Fabric Notebook is executed (via portal or Jobs API `RunNotebook`), and are managed through the notebook lifecycle, not the Livy API.

```bash
# Check for existing idle Lakehouse Livy session (avoid resource waste)
sessionId=$(az rest --method get --resource "$FABRIC_RESOURCE_SCOPE" --url "$FABRIC_API_URL/workspaces/$workspaceId/lakehouses/$lakehouseId/$LIVY_API_PATH/sessions" --query "sessions[?state=='idle'][0].id" --output tsv)

# Create if none available - FORCE STARTER POOL USAGE
if [[ -z "$sessionId" ]]; then
    cat > /tmp/body.json << 'EOF'
{
    "name":"analysis",
    "driverMemory":"56g",
    "driverCores":8,
    "executorMemory":"56g",
    "executorCores":8,
    "conf": {
        "spark.dynamicAllocation.enabled": "true",
        "spark.fabric.pool.name": "Starter Pool"
    }
}
EOF
    sessionId=$(az rest --method post --resource "$FABRIC_RESOURCE_SCOPE" --url "$FABRIC_API_URL/workspaces/$workspaceId/lakehouses/$lakehouseId/$LIVY_API_PATH/sessions" --body @/tmp/body.json --query "id" --output tsv)
    
    echo "⏳ Waiting for starter pool session to be ready..." 
    # With starter pools, this should be 3-5 seconds
    timeout=30  # Reduced from 90s since starter pools are fast
    while [ $timeout -gt 0 ]; do
        state=$(az rest --resource "$FABRIC_RESOURCE_SCOPE" --url "$FABRIC_API_URL/workspaces/$workspaceId/lakehouses/$lakehouseId/$LIVY_API_PATH/sessions/$sessionId" --query "state" --output tsv)
        if [[ "$state" == "idle" ]]; then
            echo "✅ Session ready in starter pool!"
            break
        fi
        echo "   Session state: $state (${timeout}s remaining)"
        sleep 3
        timeout=$((timeout - 3))
    done
fi
```

### Data Exploration (Fabric-Specific Patterns)
```bash
# Execute statement (LLM knows Python/Spark syntax)
cat > /tmp/body.json << 'EOF'
{
  "code": "spark.sql(\"SHOW TABLES\").show(); df = spark.table(\"your_table\"); df.describe().show()",
  "kind": "pyspark"
}
EOF
az rest --method post --resource "$FABRIC_RESOURCE_SCOPE" --url "$FABRIC_API_URL/workspaces/$workspaceId/lakehouses/$lakehouseId/$LIVY_API_PATH/sessions/$sessionId/statements" --body @/tmp/body.json
```

## Key Fabric Patterns

| Pattern | Code | Use Case |
|---|---|---|
| **Table Discovery** | `spark.sql("SHOW TABLES")` | List available tables |
| **Cross-Lakehouse** | `spark.sql("SELECT * FROM other_workspace.table")` | Query across workspaces |
| **Delta Features** | `df.history()`, `df.readVersion(1)` | Time travel, versioning |
| **Schema Evolution** | `df.printSchema()` | Understand structure |

## Lakehouse Livy Session Cleanup
```bash
# Clean up idle Lakehouse Livy sessions (optional)
az rest --method get --resource "$FABRIC_RESOURCE_SCOPE" --url "$FABRIC_API_URL/workspaces/$workspaceId/lakehouses/$lakehouseId/$LIVY_API_PATH/sessions" --query "sessions[?state=='idle'].id" --output tsv | xargs -I {} az rest --method delete --resource "$FABRIC_RESOURCE_SCOPE" --url "$FABRIC_API_URL/workspaces/$workspaceId/lakehouses/$lakehouseId/$LIVY_API_PATH/sessions/{}"
```

---

**Focus**: This skill provides Fabric-specific REST API patterns. LLM already knows Python/Spark syntax — we focus on Fabric integration, session management, and API endpoints.