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name: analyze-profile description: Analyze a StarRocks query profile JSON to discover available metrics, identify bottlenecks, and suggest which metrics would be valuable to display. allowed-tools: Read, Grep, Glob

Analyze StarRocks Query Profile

Analyze the query profile at $ARGUMENTS to discover metrics and identify performance characteristics.

Tasks

1. Load and Parse Profile

• Read the JSON file from the provided path (default to test_profiles/ directory if just a filename)
• Extract the Query.Execution structure
• Identify all Fragments, Pipelines, and Operators

2. Discover Available Metrics

For each operator type found (CONNECTOR_SCAN, HASH_JOIN_BUILD, HASH_JOIN_PROBE, AGGREGATE, EXCHANGE, etc.):

• List all CommonMetrics keys with example values
• List all UniqueMetrics keys with example values
• Note any __MAX_OF_* and __MIN_OF_* variants (useful for skew detection)

3. Identify Performance Characteristics

Analyze the profile for:

• Slowest operators: Which operators have highest OperatorTotalTime?
• Data volume: Which scans read the most BytesRead or RawRowsRead?
• Join efficiency: Check hashTableMemoryUsage, rowsSpilled
• Filter effectiveness: Compare RawRowsRead vs RowsRead for scans
• Skew indicators: Large gaps between __MAX_OF_* and __MIN_OF_* values

4. Output Report

Provide a structured report with:

1. Profile Summary: Query ID, duration, fragment count, operator count
2. Operator Inventory: Table of operator types and their counts
3. Metric Discovery: New/interesting metrics not currently displayed in the UI
4. Bottleneck Analysis: Top 3 performance concerns with specific values
5. Recommendations: Which metrics should be added to scan/join tables

Reference

• Use parseNumericValue() pattern for time strings like "1.592ms"
• Current scan metrics are defined in js/scanRender.js METRICS_CONFIG
• Current join metrics are defined in js/joinRender.js JOIN_METRICS_CONFIG