code: def _call_plc_betweenness_centrality(
      mg_graph_x,
      sID: bytes,
      k: Union[int, cudf.Series],
      random_state: int,
      normalized: bool,
      endpoints: bool,
      do_expensive_check: bool,
      edge_bc: bool,
  ) -> cudf.DataFrame:
      if edge_bc:
          cp_arrays = pylibcugraph_edge_betweenness_centrality(
              resource_handle=ResourceHandle(
                  Comms.get_handle(sID).getHandle()
              ),
              graph=mg_graph_x,
              k=k,
              random_state=random_state,
              normalized=normalized,
              do_expensive_check=do_expensive_check,
          )
      else:
          cp_arrays = pylibcugraph_betweenness_centrality(
              resource_handle=ResourceHandle(
                  Comms.get_handle(sID).getHandle()
              ),
              graph=mg_graph_x,
              k=k,
              random_state=random_state,
              normalized=normalized,
              include_endpoints=endpoints,
              do_expensive_check=do_expensive_check,
          )
      return convert_to_cudf(cp_arrays, edge_bc)
  
file_path: cugraph/python/cugraph/cugraph/dask/centrality/betweenness_centrality.py
imports: from dask.distributed import wait, get_client
  from pylibcugraph import ResourceHandle, betweenness_centrality, edge_betweenness_centrality
  import cugraph.dask.comms.comms
  from cugraph.dask.common.input_utils import get_distributed_data
  import dask_cudf
  import cudf
  import cupy
  import warnings
  import dask
  from typing import Union
label_desc: Use image node_id 2 for calling a global function with example usage: _call_plc_betweenness_centrality(mg_graph_x, sID, k, random_state, normalized, endpoints, do_expensive_check, edge_bc) and returns: convert_to_cudf