code: def _create_parquet_records(
      n, exec_properties
  ) -> Iterable[Dict[str, Any]]:
      records = []
      has_empty = exec_properties.get("has_empty", True)
  
      for i in range(n):
          feature = {}
          if i % 10 != 0 or not has_empty:
              feature["i"] = i
              feature["f"] = float(i)
              feature["s"] = str(i)
              records.append(feature)
  
      exec_properties["pyarrow_schema"] = pa.schema(
          [
              pa.field("i", pa.int64()),
              pa.field("f", pa.float64()),
              pa.field("s", pa.string()),
          ]
      )
  
      return records
  
imports: import os
  from typing import Any, Dict, Iterable
  import apache_beam
  import pyarrow
  import tensorflow
  from tfx.components.example_gen import base_example_gen_executor
  from tfx.dsl.io import fileio
  from tfx.proto import example_gen_pb2
  from tfx.types import artifact_utils
  from tfx.types import standard_artifacts
  from tfx.types import standard_component_specs
  from tfx.utils import proto_utils
label_desc: Use image node_id 2 for calling a global function with example usage: _create_parquet_records(n, exec_properties) and returns: records