StarRocks Documentation Lookup

Look up information about $ARGUMENTS from StarRocks official documentation.

Primary Documentation Sources

1. Query Profile Operator Metrics (most relevant for metric definitions): https://docs.starrocks.io/docs/best_practices/query_tuning/query_profile_operator_metrics

2. Query Profile Tuning Recipes (bottleneck patterns and fixes): https://docs.starrocks.io/docs/best_practices/query_tuning/query_profile_tuning_recipes/

3. Query Planning (optimizer behavior, join strategies, distribution): https://docs.starrocks.io/docs/best_practices/query_tuning/query_planning/

Tasks

1. Search Documentation

• For metric definitions: fetch the Query Profile Operator Metrics page first
• For bottleneck patterns: fetch the Query Profile Tuning Recipes page
• For optimizer/planning questions: fetch the Query Planning page
• Use WebSearch for broader StarRocks documentation if needed

2. Explain the Metric/Concept

Provide:

• Definition: What the metric measures
• Units: Time (ns/us/ms/s), bytes, rows, count
• Location: CommonMetrics vs UniqueMetrics, which operator types have it
• Interpretation: What high/low values indicate

3. Performance Context

If relevant, explain:

• Bottleneck patterns: What issues this metric can reveal
• Related metrics: Other metrics to check alongside
• Optimization tips: How to improve if values are problematic

4. NorthStar Integration

Check if this metric is already displayed in NorthStar:

• Search js/scanRender.js for scan-related metrics
• Search js/joinRender.js for join-related metrics
• If not displayed, suggest whether it should be added

Common Metric Categories

Scan Operator Metrics

• Time: ScanTime, IOTaskExecTime, IOTaskWaitTime, SegmentInit, SegmentRead
• Rows: RawRowsRead, RowsRead, PullRowNum, filter metrics (ZoneMapIndexFilterRows, etc.)
• I/O: BytesRead, CompressedBytesRead, IOTime

Join Operator Metrics

• Build: BuildHashTableTime, HashTableMemoryUsage, RowsSpilled
• Probe: SearchHashTableTime, ProbeConjunctEvaluateTime

Common Bottleneck Patterns

• Cold storage: High IOTaskExecTime + BytesRead
• Thread starvation: High IOTaskWaitTime + low PeakIOTasks
• Data skew: Large gap between __MAX_OF_* and __MIN_OF_*
• Fragmentation: High RowsetsReadCount/SegmentsReadCount + long SegmentInit
• Missing filter pushdown: PushdownPredicates near 0, high PredFilterRows