def prepare_data(self):
if not self.is_prepared:
self.histogram_list = Utils.get_distribution(self.value_list)
self.numeric_list = Utils.clean_examples_numeric(self.value_list)
if self.is_numeric():
self.sample_list = sc.parallelize(self.numeric_list).sample(False,
100.0 / len(self.numeric_list)).collect()
else:
self.value_text = sc.parallelize(self.value_list).map(lambda x: " %s " % x).reduce(lambda x, y: x + y)
self.is_prepared = True
def __init__(self, column, train_examples_map, sc):
self.train_examples_map = train_examples_map
self.test_examples = column.value_list
self.true_label = column.semantic_type
self.name = column.name
self.numeric_test_examples = Utils.clean_examples_numeric(self.test_examples)
self.is_numeric = column.is_numeric()
self.hist_examples = Utils.get_distribution(self.test_examples)
self.sc = sc
