⚡ Bolt: 고유 값 카운트 시 stats::na.omit 오버헤드 최적화 - #307
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R에서 `length(stats::na.omit(unique(x)))` 대신 `sum(!is.na(unique(x)))`를 사용하도록 수정하여, `stats::na.omit` 호출 시 발생하는 메서드 디스패치(method dispatch)와 속성 할당(attribute allocation) 오버헤드를 제거했습니다.
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| (sum(!is.na(unique(newFormModel@Data$data[, newFormItemName]))) == | ||
| sum(!is.na(unique(oldFormModel@Data$data[, oldFormItemName])))) |
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🔍 Regression guard misses new formula
The formula-integrity test still evaluates the previous expression. Add the optimized expression and edge cases so this calibration change has direct regression coverage.
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R에서 `length(stats::na.omit(unique(x)))` 및 `length(unique(stats::na.omit(x)))` 대신 `sum(!is.na(unique(x)))`를 사용하도록 수정하여, `stats::na.omit` 호출 시 발생하는 메서드 디스패치(method dispatch)와 속성 할당(attribute allocation) 오버헤드를 제거했습니다.
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💡 What:
R/aFIPC.R와R/surveyFA.R에서 사용되던length(stats::na.omit(unique(x)))또는length(unique(stats::na.omit(x)))구문을 모두sum(!is.na(unique(x)))로 교체했습니다.🎯 Why: R의
stats::na.omit함수는 S3 메서드 디스패치를 수행하고na.action속성을 할당하는 과정에서 불필요한 성능 오버헤드를 발생시킵니다. 내부적으로 C 레벨에서 처리되는 논리 연산자(!is.na)와 합계(sum)를 사용하면 이러한 오버헤드 없이 동일한 로직(NA가 아닌 고유 값의 개수 측정)을 훨씬 빠르게 수행할 수 있습니다.📊 Impact: 반복적으로 호출되는
surveyFA및 공통 문항 매칭 부분의 성능이 개선되었습니다. 동일한 결과를 반환하므로 하위 호환성 문제가 없습니다.🔬 Measurement:
testthat테스트 스위트가 기존과 동일하게 모든 테스트를 통과(PASS)하며, 속도 향상을 기대할 수 있습니다. 관련된 내용은.jules/bolt.md저널에 기록했습니다.PR created automatically by Jules for task 1824799397000706099 started by @seonghobae