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feat(eap-api): Use signs in count, average, and sum calculations #6613

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Dec 6, 2024
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feat(eap-api): Use signs in count, average, and sum calculations #6613

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28 changes: 19 additions & 9 deletions snuba/web/rpc/common/aggregation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -21,6 +21,7 @@
from snuba.web.rpc.common.exceptions import BadSnubaRPCRequestException

sampling_weight_column = column("sampling_weight")
sign_column = column("sign")

# Z value for 95% confidence interval is 1.96 which comes from the normal distribution z score.
z_value = 1.96
Expand Down Expand Up @@ -211,26 +212,27 @@ def get_extrapolated_function(
Function.ValueType, CurriedFunctionCall | FunctionCall
] = {
Function.FUNCTION_SUM: f.sum(
f.multiply(field, sampling_weight_column), **alias_dict
f.multiply(field, f.multiply(sign_column, sampling_weight_column)),
**alias_dict,
),
Function.FUNCTION_AVERAGE: f.divide(
f.sum(f.multiply(field, sampling_weight_column)),
f.sum(f.multiply(field, f.multiply(sign_column, sampling_weight_column))),
f.sumIf(
sampling_weight_column,
f.multiply(sign_column, sampling_weight_column),
get_field_existence_expression(aggregation),
),
**alias_dict,
),
Function.FUNCTION_AVG: f.divide(
f.sum(f.multiply(field, sampling_weight_column)),
f.sum(f.multiply(field, f.multiply(sign_column, sampling_weight_column))),
f.sumIf(
sampling_weight_column,
f.multiply(sign_column, sampling_weight_column),
get_field_existence_expression(aggregation),
),
**alias_dict,
),
Function.FUNCTION_COUNT: f.sumIf(
sampling_weight_column,
f.multiply(sign_column, sampling_weight_column),
get_field_existence_expression(aggregation),
**alias_dict,
),
Expand Down Expand Up @@ -407,9 +409,17 @@ def aggregation_to_expression(aggregation: AttributeAggregation) -> Expression:
alias = aggregation.label if aggregation.label else None
alias_dict = {"alias": alias} if alias else {}
function_map: dict[Function.ValueType, CurriedFunctionCall | FunctionCall] = {
Function.FUNCTION_SUM: f.sum(field, **alias_dict),
Function.FUNCTION_AVERAGE: f.avg(field, **alias_dict),
Function.FUNCTION_COUNT: f.count(field, **alias_dict),
Function.FUNCTION_SUM: f.sum(f.multiply(field, sign_column), **alias_dict),
Function.FUNCTION_AVERAGE: f.divide(
f.sum(f.multiply(field, sign_column)),
f.sumIf(sign_column, get_field_existence_expression(aggregation)),
**alias_dict,
),
Function.FUNCTION_COUNT: f.sumIf(
sign_column,
get_field_existence_expression(aggregation),
**alias_dict,
),
Function.FUNCTION_P50: cf.quantile(0.5)(field, **alias_dict),
Function.FUNCTION_P75: cf.quantile(0.75)(field, **alias_dict),
Function.FUNCTION_P90: cf.quantile(0.9)(field, **alias_dict),
Expand Down
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