def max(self, src_col_name, new_col_name='max'):
"""
:param src_col_name: the column to find the max of its values
:param new_col_name: the new column name of the max
:return: if src_col_name is not None and is a groupby column, return a dataset with a new column name. else
return an integer
"""
if self.cached:
ds = self._cache_dataset()
return ds.max(src_col_name, new_col_name)
param = None
if src_col_name not in self.columns:
raise Exception("Aggregation column {} doesn't exist in this dataset".format(src_col_name))
agg_col = src_col_name
if agg_col not in self.grouping_cols and agg_col in self.parent_dataset.columns:
agg_node = GroupedAggregationOperator(self.name, agg_col, AggregationFunction.MAX, new_col_name, param)
self.query_queue.append_node(agg_node)
self.add_column(new_col_name)
self.agg_columns.append(new_col_name)
#elif agg_col in self.agg_columns:
# # TODO: Generate a subquery when running an aggregation over aggregated column after groupby
# pass
else:
# TODO: Don't allow any more operations on the dataset
agg_node = AggregationOperator(self.name, agg_col, AggregationFunction.MAX, new_col_name, param)
self.query_queue.append_node(agg_node)
self.add_column(new_col_name)
self.agg_columns.append(new_col_name)
return self
def sum(self, src_col_name, new_col_name='sum'):
"""
:param src_col_name: the column to find the sum of its values
:param new_col_name: the new column name of the sum
:return: if src_col_name is not None and is a groupby column, return a dataset with a new column name. else
return an integer
"""
if self.cached:
ds = self._cache_dataset()
return ds.sum(src_col_name, new_col_name)
param = None
if src_col_name not in self.columns:
raise Exception("Aggregation column {} doesn't exist in this dataset".format(src_col_name))
agg_col = src_col_name
if agg_col not in self.grouping_cols and agg_col in self.parent_dataset.columns:
agg_node = GroupedAggregationOperator(self.name, agg_col, AggregationFunction.SUM, new_col_name, param)
self.query_queue.append_node(agg_node)
self.add_column(new_col_name)
self.agg_columns.append(new_col_name)
else:
agg_node = AggregationOperator(self.name, agg_col, AggregationFunction.SUM, new_col_name, param)
self.query_queue.append_node(agg_node)
self.columns = [src_col_name, new_col_name]
self.agg_columns.append(new_col_name)
return self
def count(self, src_col_name=None, new_col_name='count', unique=False):
"""
:param src_col_name: the column to count its values
:param new_col_name: the new column name of the count
:param unique: if True retun the number of unique values else return the size of the result set
:return: if src_col_name is not None and is a groupby column, return a dataset with a new column name. else
return an integer
"""
if self.cached:
ds = self._cache_dataset()
return ds.count(src_col_name, new_col_name, unique)
if unique:
param = "DISTINCT"
else:
param = None
if src_col_name is not None:
if src_col_name not in self.columns and src_col_name not in self.parent_dataset.columns:
raise Exception("Aggregation column {} doesn't exist in this dataset".format(src_col_name))
agg_col = src_col_name
if agg_col not in self.grouping_cols and agg_col in self.parent_dataset.columns:
agg_node = GroupedAggregationOperator(self.name, agg_col, AggregationFunction.COUNT, new_col_name, param)
self.query_queue.append_node(agg_node)
self.add_column(new_col_name)
self.agg_columns.append(new_col_name)
else:
# TODO: Don't allow any more operations on the dataset
agg_node = AggregationOperator(self.name, agg_col, AggregationFunction.COUNT, new_col_name, param)
self.query_queue.append_node(agg_node)
self.add_column(new_col_name)
self.agg_columns.append(new_col_name)
else:
# TODO: Don't allow any more operations on the dataser
agg_node = IntegerCountOperator(self.name, new_col_name, param)
self.query_queue.append_node(agg_node)
self.add_column(new_col_name)
self.agg_columns.append(new_col_name)
return self