code: def compare(
      baseline_path: Path,
      comparison_path: Path,
      noise_threshold: float,
  ) -> None:
      baseline = BenchmarkRun.load_from_file(baseline_path)
      comparison = BenchmarkRun.load_from_file(comparison_path)
  
      console = Console()
  
      # use basename as the column names
      baseline_header = baseline_path.parent.stem
      comparison_header = comparison_path.parent.stem
  
      table = Table(show_header=True, header_style="bold magenta")
      table.add_column("Query", style="dim", width=12)
      table.add_column(baseline_header, justify="right", style="dim")
      table.add_column(comparison_header, justify="right", style="dim")
      table.add_column("Change", justify="right", style="dim")
  
      faster_count = 0
      slower_count = 0
      no_change_count = 0
      total_baseline_time = 0
      total_comparison_time = 0
  
      for baseline_result, comparison_result in zip(
          baseline.queries, comparison.queries
      ):
          assert baseline_result.query == comparison_result.query
  
          total_baseline_time += baseline_result.execution_time
          total_comparison_time += comparison_result.execution_time
  
          change = (
              comparison_result.execution_time
              / baseline_result.execution_time
          )
  
          if (
              (1.0 - noise_threshold)
              <= change
              <= (1.0 + noise_threshold)
          ):
              change_text = "no change"
              no_change_count += 1
          elif change < 1.0:
              change_text = f"+{(1 / change):.2f}x faster"
              faster_count += 1
          else:
              change_text = f"{change:.2f}x slower"
              slower_count += 1
  
          table.add_row(
              f"Q{baseline_result.query}",
              f"{baseline_result.execution_time:.2f}ms",
              f"{comparison_result.execution_time:.2f}ms",
              change_text,
          )
  
      console.print(table)
  
      # Calculate averages
      avg_baseline_time = total_baseline_time / len(baseline.queries)
      avg_comparison_time = total_comparison_time / len(
          comparison.queries
      )
  
      # Summary table
      summary_table = Table(
          show_header=True, header_style="bold magenta"
      )
      summary_table.add_column(
          "Benchmark Summary", justify="left", style="dim"
      )
      summary_table.add_column("", justify="right", style="dim")
  
      summary_table.add_row(
          f"Total Time ({baseline_header})",
          f"{total_baseline_time:.2f}ms",
      )
      summary_table.add_row(
          f"Total Time ({comparison_header})",
          f"{total_comparison_time:.2f}ms",
      )
      summary_table.add_row(
          f"Average Time ({baseline_header})",
          f"{avg_baseline_time:.2f}ms",
      )
      summary_table.add_row(
          f"Average Time ({comparison_header})",
          f"{avg_comparison_time:.2f}ms",
      )
      summary_table.add_row("Queries Faster", str(faster_count))
      summary_table.add_row("Queries Slower", str(slower_count))
      summary_table.add_row(
          "Queries with No Change", str(no_change_count)
      )
  
      console.print(summary_table)
  
file_path: arrow-datafusion/benchmarks/compare.py
imports: from __future__ import annotations
  import json
  from dataclasses import dataclass
  from typing import Dict, List, Any
  from pathlib import Path
  from argparse import ArgumentParser
label_desc: Use image node_id 1 for calling a global function with example usage: compare(baseline_path, comparison_path, noise_threshold) without return types