def run(self, metadata):
'''
RETURN: {
'value': [(ID, NAME)], # ID = ['user', 3]
'query': {
'whereclause': [col.in_(*primary_keys)],
'column': [col],
'group_by': [col]
},
'axis_mapping': axis_map.column_mapping(result),
'delta':0
}
'''
if self.sublevels[0].name=='all':
return [{
'value': [([str(self.level)], str(self.level), False)],
'query': {
'column': [sqlalchemy.literal('all')],
},
'axis_mapping': axis_map.column_static(False),
'delta':0,
}]
# Make these 2 commands working in all cases:
# return self._run_transform(metadata)
# return self._run_star(metadata)
if self.object.table_id<>self.object.dimension_id.cube_id.table_id: # Add a condition on the object
result = self._run_transform(metadata)
else:
result = self._run_star(metadata)
return result
def _run_star(self, metadata):
"""
Compute axis values, and transform the main query in the same way
to add this branch of the star for this subset. The mappers
reassign to values.
"""
print '*** Start ***'
table, result,result_mapping, result_axis = self._compute_axis(metadata, True)
result_axis.setdefault('where_clause', [])
#
# The result to be applied to the main query object
#
result = {
'value': result,
'query': {
# 'whereclause': result_axis.get('where_clause',[]),
'column': result_axis.get('column', []),
'group_by': result_axis.get('column', [])
},
##
## How to use group of axis_mapping ?
##
'axis_mapping': axis_map.column_static(False),
'delta':0,
}
return [result]
def _run_transform(self, metadata):
"""
Compute axis values, and transform the main query according to axis
values for this subset. The main query slicer is transformed to a
single condition like: foreign_key in (...) and reapplied to axis
values.
"""
table, axis, mapping, result_axis = self._compute_axis(metadata, True)
table2 = common.table_get(metadata, self.object.dimension_id.cube_id.table_id)
sql_table = sqlalchemy.Table(self.object.table_id.column_link_id.table_id.table_db_name,metadata)
col = common.col_get(sql_table, self.object.table_id.column_link_id)
#
# The result to be applied to the main query object
#
result = []
for a in axis:
k = tuple(list(a)[0][1:])
mapping_axis = filter(lambda m: tuple(list(m)[:-1])==k, mapping)
primary_keys = map(lambda x:list(x)[-1], mapping_axis)
# To convert everything in to the string so that no conversion needed at later stage
# This is for the elements to be displayed in the rows and columns
for i in range(len(a[0])):
if a[0][i]:
if isinstance(a[0][i],int):
a[0][i] = str(a[0][i])
elif isinstance(a[0][i],float):
a[0][i] = str(int(a[0][i]))
else:
a[0][i] = '/'
a = list(a)
if isinstance(a[-1],int):
a[-1] = str(a[-1])
elif isinstance(a[-1],float):
a[-1] = str(int(a[-1]))
a = tuple(a)
primary_keys = map(lambda x: str(x),primary_keys)
result.append( {
'value': [a],
'query': {
'whereclause': [col.in_(primary_keys)],#.extend(result_axis['where_clause']),
'column': [sqlalchemy.literal('transform')],
},
'axis_mapping': axis_map.column_static(False),
'delta':0,
})
return result