code: def get_feature_cols():
      return ["user", "item"] + sparse_features + dense_features
  
file_path: BigDL/python/orca/tutorial/NCF/process_xshards.py
imports: import os
  import numpy
  import pandas
  import scipy.sparse
  from sklearn.model_selection import train_test_split
  from bigdl.orca.data.pandas import read_csv
  from bigdl.orca.data.transformer import StringIndexer, MinMaxScaler
label_desc: Use image node_id 4 for calling a global function with example usage: get_feature_cols() and returns: unknown