code: def _read_results(src_dir):
      results = collections.defaultdict(
          lambda: collections.defaultdict(list)
      )
      path = pathlib.Path(os.path.join(src_dir, "target", "criterion"))
      for path in list(path.glob("**/new/raw.csv")):
          with open(path) as csv_file:
              reader = csv.DictReader(csv_file)
              for row in reader:
                  suite, name = _parse_benchmark_group(row)
                  results[suite][name].append(_result_in_seconds(row))
      return results
  
file_path: arrow-datafusion/conbench/_criterion.py
imports: import collections
  import csv
  import os
  import pathlib
  import subprocess
  import conbench.runner
  from conbench.machine_info import github_info
label_desc: Use image node_id 3 for calling a global function with example usage: _read_results(src_dir) and returns: results