old_contents: import sys
  sys.path.insert(1,"../../../")
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.glm import H2OGeneralizedLinearEstimator
  import os
  
  
  def test_hadoop():
      '''
      Test H2O read and write to hdfs
      '''
      hdfs_name_node = os.getenv("NAME_NODE")
      h2o_data = h2o.import_file("hdfs://" + hdfs_name_node + "/datasets/100k.csv")
      print h2o_data.head()
      h2o_data.summary()
  
      h2o_glm = H2OGeneralizedLinearEstimator(family="binomial", alpha=0.5, Lambda=0.01)
      h2o_glm.train(x=range(1, h2o_data.ncol), y=0, training_frame=h2o_data)
  
      hdfs_model_path = os.getenv("MODEL_PATH")
      h2o.save_model(h2o_glm, "hdfs://" + hdfs_model_path)
  
      new_model = h2o.load_model("hdfs://" + hdfs_model_path)
  
  
  
  if __name__ == "__main__":
      pyunit_utils.standalone_test(test_hadoop)
  else:
      test_hadoop()
  
  
new_contents: import sys
  sys.path.insert(1,"../")
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.glm import H2OGeneralizedLinearEstimator
  import os
  
  
  def test_hadoop():
      '''
      Test H2O read and write to hdfs
      '''
      hdfs_name_node = os.getenv("NAME_NODE")
      h2o_data = h2o.import_file("hdfs://" + hdfs_name_node + "/datasets/100k.csv")
      print h2o_data.head()
      h2o_data.summary()
  
      h2o_glm = H2OGeneralizedLinearEstimator(family="binomial", alpha=0.5, Lambda=0.01)
      h2o_glm.train(x=range(1, h2o_data.ncol), y=0, training_frame=h2o_data)
  
      hdfs_model_path = os.getenv("MODEL_PATH")
      h2o.save_model(h2o_glm, "hdfs://" + hdfs_model_path)
  
      new_model = h2o.load_model("hdfs://" + hdfs_model_path)
  
  
  
  if __name__ == "__main__":
      pyunit_utils.standalone_test(test_hadoop)
  else:
      test_hadoop()
  
  
subject: change path of h2o py module