code: def betweenness_centrality_parallel(G, processes=None):
      """Parallel betweenness centrality  function"""
      p = Pool(processes=processes)
      node_divisor = len(p._pool) * 4
      node_chunks = list(chunks(G.nodes(), G.order() // node_divisor))
      num_chunks = len(node_chunks)
      bt_sc = p.starmap(
          nx.betweenness_centrality_subset,
          zip(
              [G] * num_chunks,
              node_chunks,
              [list(G)] * num_chunks,
              [True] * num_chunks,
              [None] * num_chunks,
          ),
      )
  
      # Reduce the partial solutions
      bt_c = bt_sc[0]
      for bt in bt_sc[1:]:
          for n in bt:
              bt_c[n] += bt[n]
      return bt_c
  
imports: from multiprocessing import Pool
  import time
  import itertools
  import matplotlib.pyplot
  import networkx
label_desc: Use image node_id 2 for calling a global function with example usage: betweenness_centrality_parallel(G, processes) and returns: bt_c