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Optimize tidyCovariates() for new Andromeda when data are large (Issue308) #309

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Merged
anthonysena merged 2 commits into from
Jun 16, 2025
Merged

Optimize tidyCovariates() for new Andromeda when data are large (Issue308) #309

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d514584
Merge pull request #305 from OHDSI/develop
ginberg May 9, 2025
fc817de
Optimizing tidyCovariates for large data. Dixes #308
Jun 13, 2025
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17 changes: 12 additions & 5 deletions R/Normalization.R
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Original file line number Diff line number Diff line change
Expand Up @@ -179,20 +179,27 @@ tidyCovariateData <- function(covariateData,
deleteCovariateIds <- c(deleteCovariateIds, toDelete$covariateId)
ParallelLogger::logInfo("Removing ", nrow(toDelete), " infrequent covariates")
}
if (length(deleteCovariateIds) > 0) {
newCovariates <- newCovariates %>%
filter(!.data$covariateId %in% deleteCovariateIds)
}

# When performing both filtering by covariate IDs and normalization, it is *much* faster
# to apply the filtering to the maxValuePerCovariateId table, and let the inner join
# apply the filtering to the covariate table (instead of filtering the covariate table
# directly).
if (normalize) {
ParallelLogger::logInfo("Normalizing covariates")
if (length(deleteCovariateIds) > 0) {
covariateData$maxValuePerCovariateId <- covariateData$maxValuePerCovariateId %>%
filter(!.data$covariateId %in% deleteCovariateIds)
}
newCovariates <- newCovariates %>%
inner_join(covariateData$maxValuePerCovariateId, by = "covariateId") %>%
mutate(covariateValue = .data$covariateValue / .data$maxValue) %>%
select(-.data$maxValue)
metaData$normFactors <- covariateData$maxValuePerCovariateId %>%
collect()
}
} else if (length(deleteCovariateIds) > 0) {
newCovariates <- newCovariates %>%
filter(!.data$covariateId %in% deleteCovariateIds)
}
newCovariateData$covariates <- newCovariates
if (!is.null(covariateData$timeRef)) {
newCovariateData$timeRef <- covariateData$timeRef
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