perfetto-sql

To analyze Android trace performance, you translate natural language analysis goals into validated Perfetto SQL queries. This process uses schema-aware generation against standard library tables to investigate slices, threads, and CPU metrics.

You can use natural language to find expensive slices in an Android startup trace by converting your analysis request into validated Perfetto SQL. This automatically applies schema-aware query patterns to identify costly rendering slices.

Perfetto trace analysis relies on standard library tables containing slices, threads, and CPU metrics. Query generation uses schema guidance to identify the correct modules and columns for validating complex system performance investigations.

Perfetto trace_processor supports idempotent SQL patterns for system performance investigations. Validated execution against local trace files ensures queries are syntactically correct and reliably analyze thread activity and memory-related events.

Perfetto SQL queries often fail due to schema mismatches and common query mistakes when analyzing complex Android traces. Schema-aware query generation avoids these errors by validating syntax against standard library references before execution.

The best way to validate Perfetto SQL is by generating syntactically valid queries using standard library references. This ensures schema-aware query generation and idempotent SQL patterns before validated execution against local trace files.