def generate_optflow_fsl_token_when_two_vars(token, columns, result_value_name,
group_by, non_aggregation_index,
is_aggregation_part):
"""
Generate the token which is accepted by the OptFlow FSL expression
when the variable number is 2.
Args:
token (str): the string token.
columns (list[str]): the column names of the source table.
result_value_name (str): the result value name to be optimized.
group_by (str): the column name to be grouped.
non_aggregation_index (str): the index string inside the non
aggregation part of the result expression.
is_aggregation_part (bool): whether the token is inside the
aggregation part of the result expression.
Returns:
A token which OptFlow FSL expression accepts.
"""
if try_convert_to_aggregation_function(token):
return try_convert_to_aggregation_function(token)
if try_convert_comparision_token(token):
return try_convert_comparision_token(token)
if is_aggregation_part:
if token == result_value_name:
return '@X[i,j]'
if token in columns:
return '@input["%s"][i,j]' % token
return token
else:
if token == result_value_name:
raise ValueError("result value name %s should not appear "
"in non aggregation expression" % token)
if token in columns:
if not group_by:
raise ValueError(
"column %s should not appear in non aggregation expression"
% token)
return '@input["%s"][%s]' % (token, non_aggregation_index)
return token
def generate_optflow_fsl_expr_when_two_vars(columns,
tokens,
variables,
result_value_name,
group_by=None):
"""
Generate the OptFlow FSL expression when the variable number is 2.
Args:
columns (list[str]): the column names of the source table.
tokens (list[str]): the objective or constraint string token list.
variables (list[str]): the variable names to be optimized.
result_value_name (str): the result value name to be optimized.
group_by (str): the column name to be grouped.
Returns:
An OptFlow FSL expression.
"""
assert len(variables) == 2
has_aggregation_function = False
for token in tokens:
if try_convert_to_aggregation_function(token):
has_aggregation_function = True
break
assert has_aggregation_function, "OptFlow only supports the aggregation " \
"expression when there are 2 variables"
tokens, variables, result_value_name, group_by = update_by_column_names(
columns=columns,
tokens=tokens,
variables=variables,
result_value_name=result_value_name,
group_by=group_by)
assert_are_valid_tokens(columns=columns,
tokens=tokens,
result_value_name=result_value_name,
group_by=group_by)
if group_by and group_by not in variables:
raise ValueError("GROUP BY column %s should be inside variables" %
group_by)
if group_by == variables[0]:
outer_range = "for i in @I"
inner_range = "for j in @J"
non_aggregation_index = "i,@J[0]"
elif group_by == variables[1]:
outer_range = "for j in @J"
inner_range = "for i in @I"
non_aggregation_index = "@I[0],j"
else:
outer_range = None
inner_range = "for i in @I for j in @J"
non_aggregation_index = None
def generate_token(token, is_aggregation_part):
return generate_optflow_fsl_token_when_two_vars(
token=token,
columns=columns,
result_value_name=result_value_name,
group_by=group_by,
non_aggregation_index=non_aggregation_index,
is_aggregation_part=is_aggregation_part)
result_tokens = []
idx = 0
while idx < len(tokens):
left_indices, right_indices, next_idx = \
find_matched_aggregation_function_brackets(tokens, idx)
assert len(left_indices) <= 1, \
"OptFlow does not support nested aggregation calls"
left_idx = left_indices[0] if left_indices else next_idx
right_idx = right_indices[0] if right_indices else next_idx
while idx < left_idx:
result_tokens.append(generate_token(tokens[idx], False))
idx += 1
if left_idx == right_idx:
continue
while idx <= right_idx:
if idx == left_idx:
result_tokens.extend(['(', '['])
elif idx == right_idx:
result_tokens.extend([' ', inner_range, ']', ')'])
else:
result_tokens.append(generate_token(tokens[idx], True))
idx += 1
while idx < next_idx:
result_tokens.append(generate_token(tokens[idx], False))
idx += 1
expr = "".join(result_tokens)
if outer_range:
return "%s: %s" % (outer_range, expr)
else:
return expr
