code: def test_parquet_read_basic(ray_start_regular_shared, fs, data_path):
      df1 = pd.DataFrame({"one": [1, 2, 3], "two": ["a", "b", "c"]})
      table = pa.Table.from_pandas(df1)
      setup_data_path = _unwrap_protocol(data_path)
      path1 = os.path.join(setup_data_path, "test1.parquet")
      pq.write_table(table, path1, filesystem=fs)
      df2 = pd.DataFrame({"one": [4, 5, 6], "two": ["e", "f", "g"]})
      table = pa.Table.from_pandas(df2)
      path2 = os.path.join(setup_data_path, "test2.parquet")
      pq.write_table(table, path2, filesystem=fs)
  
      ds = ray.data.read_parquet(data_path, filesystem=fs)
  
      # Test metadata-only parquet ops.
      check_num_computed(ds, 0, 0)
      assert ds.count() == 6
      assert ds.size_bytes() > 0
      # Schema information is available from Parquet metadata, so
      # we do not need to compute the first block.
      assert ds.schema() is not None
      check_num_computed(ds, 0, 0)
      input_files = ds.input_files()
      assert len(input_files) == 2, input_files
      assert "test1.parquet" in str(input_files)
      assert "test2.parquet" in str(input_files)
      assert (
          str(ds) == "Dataset(num_blocks=2, num_rows=6, "
          "schema={one: int64, two: string})"
      ), ds
      assert (
          repr(ds) == "Dataset(num_blocks=2, num_rows=6, "
          "schema={one: int64, two: string})"
      ), ds
      check_num_computed(ds, 0, 0)
  
      # Forces a data read.
      values = [[s["one"], s["two"]] for s in ds.take_all()]
      check_num_computed(ds, 2, 0)
      assert sorted(values) == [
          [1, "a"],
          [2, "b"],
          [3, "c"],
          [4, "e"],
          [5, "f"],
          [6, "g"],
      ]
  
      # Test column selection.
      ds = ray.data.read_parquet(
          data_path, columns=["one"], filesystem=fs
      )
      values = [s["one"] for s in ds.take()]
      assert sorted(values) == [1, 2, 3, 4, 5, 6]
      assert ds.schema().names == ["one"]
  
imports: import os
  import shutil
  from typing import Any
  import numpy
  import pandas
  import pyarrow
  import pyarrow.parquet
  import pytest
  from pytest_lazyfixture import lazy_fixture
  import ray
  from ray.data.block import BlockAccessor
  from ray.data.context import DataContext
  from ray.data.datasource import DefaultFileMetadataProvider, DefaultParquetMetadataProvider
  from ray.data.datasource.parquet_base_datasource import ParquetBaseDatasource
  from ray.data.datasource.parquet_datasource import NUM_CPUS_FOR_META_FETCH_TASK, PARALLELIZE_META_FETCH_THRESHOLD, RETRY_EXCEPTIONS_FOR_META_FETCH_TASK, ParquetDatasource, _deserialize_fragments_with_retry, _SerializedFragment
  from ray.data.datasource.path_util import _unwrap_protocol
  from ray.data.tests.conftest import *
  from ray.data.tests.mock_http_server import *
  from ray.tests.conftest import *
label_desc: Use image node_id 4 for calling a global function with example usage: test_parquet_read_basic(ray_start_regular_shared, fs, data_path) without return types