Merge branch 'main' into 2563_no_list_columns

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: admiral
 Title: ADaM in R Asset Library
-Version: 1.1.1.9038
+Version: 1.1.1.9041
 Authors@R: c(
     person("Ben", "Straub", , "[email protected]", role = c("aut", "cre")),
     person("Stefan", "Bundfuss", role = "aut",

NAMESPACE

@@ -181,6 +181,7 @@ importFrom(dplyr,first)
 importFrom(dplyr,full_join)
 importFrom(dplyr,group_by)
 importFrom(dplyr,group_by_at)
+importFrom(dplyr,group_split)
 importFrom(dplyr,if_else)
 importFrom(dplyr,lag)
 importFrom(dplyr,mutate)
@@ -321,4 +322,5 @@ importFrom(tidyselect,matches)
 importFrom(tidyselect,vars_select)
 importFrom(utils,capture.output)
 importFrom(utils,file.edit)
+importFrom(utils,object.size)
 importFrom(utils,str)

NEWS.md

@@ -3,7 +3,7 @@
 ## New Features
 
 - New function `derive_vars_cat()` for deriving pairs of variables or more, e.g. 
-`AVALCATx` & `AVALCAxN`. (#2480)
+`AVALCATy` & `AVALCAyN`. (#2480)
 - New function `derive_vars_crit_flag()` for deriving criterion flag variables
 (`CRITy`, `CRITyFL`, `CRITyFLN`). (#2468)
 - New function `transform_range()`  to transform values from a source range to a
@@ -49,6 +49,10 @@ or that the queries dataset contains duplicates. (#2543)
 stops execution if the records in `dataset_merge` or `dataset_facm` respectively
 are not unique. (#2563)
 
+- The functions `derive_vars_joined()`, `derive_var_joined_exist_flag()`,
+`derive_extreme_event()`, and `filter_joined()` were updated to reduce their
+memory consumption. (#2590)
+
 ## Breaking Changes
 
 - The following function arguments are entering the next phase of the deprecation process: (#2487)

R/admiral-package.R

@@ -4,9 +4,9 @@
 #' @importFrom cli cli_abort ansi_collapse cli_div cli_inform cli_text cli_warn
 #' @importFrom dplyr across arrange between bind_cols bind_rows case_when
 #'   coalesce desc distinct ends_with everything filter first full_join group_by
-#'   group_by_at if_else mutate n n_distinct na_if pull rename rename_with
-#'   row_number select semi_join slice starts_with summarise summarise_all
-#'   tibble tribble ungroup union lag
+#'   group_by_at group_split if_else lag mutate n n_distinct na_if pull rename
+#'   rename_with row_number select semi_join slice starts_with summarise
+#'   summarise_all tibble tribble ungroup union
 #' @importFrom hms as_hms
 #' @importFrom lifecycle deprecate_warn deprecate_stop deprecated
 #' @importFrom lubridate %--% as_datetime ceiling_date date days duration
@@ -30,6 +30,6 @@
 #'             str_trim
 #' @importFrom tidyr crossing drop_na fill nest pivot_longer pivot_wider unnest
 #' @importFrom tidyselect all_of any_of contains matches vars_select
-#' @importFrom utils capture.output file.edit str
+#' @importFrom utils capture.output file.edit object.size str
 #'
 "_PACKAGE"

R/derive_basetype_records.R

@@ -39,7 +39,6 @@
 #' @examples
 #' library(tibble)
 #' library(dplyr, warn.conflicts = FALSE)
-#' library(rlang)
 #'
 #' bds <- tribble(
 #'   ~USUBJID, ~EPOCH,         ~PARAMCD,  ~ASEQ, ~AVAL,

R/derive_joined.R

@@ -806,17 +806,92 @@ get_joined_data <- function(dataset,
 
   # join the input dataset with itself such that to each observation of the
   # input dataset all following observations are joined
+  data_add_to_join <- select(
+    data_add,
+    !!!by_vars,
+    !!!replace_values_by_names(extract_vars(order)),
+    !!!replace_values_by_names(join_vars),
+    !!tmp_obs_nr_var
+  )
+
+  # split input dataset into smaller pieces and process them separately
+  # This reduces the memory consumption.
+  if (is.null(by_vars_left)) {
+    # create batches of about 1MB input data
+    obs_per_batch <- floor(1000000 / as.numeric(object.size(data) / nrow(data)))
+    tmp_batch_nr <- get_new_tmp_var(data, prefix = "tmp_batch_nr")
+    data_list <- data %>%
+      mutate(!!tmp_batch_nr := ceiling(row_number() / obs_per_batch)) %>%
+      group_by(!!tmp_batch_nr) %>%
+      group_split(.keep = FALSE)
+    data_add_list <- list(data_add_to_join)
+  } else {
+    data_nest <- nest(data, data = everything(), .by = vars2chr(unname(by_vars_left)))
+    data_add_nest <- nest(data_add, data_add = everything(), .by = vars2chr(unname(by_vars_left)))
+    data_all_nest <- inner_join(data_nest, data_add_nest, by = vars2chr(by_vars_left))
+    data_list <- data_all_nest$data
+    data_add_list <- data_all_nest$data_add
+  }
+
+  joined_data <- map2(
+    data_list,
+    data_add_list,
+    function(x, y) {
+      get_joined_sub_data(
+        x,
+        y,
+        by_vars = by_vars_left,
+        tmp_obs_nr_var = tmp_obs_nr_var,
+        tmp_obs_nr_left = tmp_obs_nr_left,
+        join_type = join_type,
+        first_cond_upper = first_cond_upper,
+        first_cond_lower = first_cond_lower,
+        filter_join = filter_join
+      )
+    }
+  )
+
+  bind_rows(joined_data) %>%
+    remove_tmp_vars() %>%
+    select(-!!tmp_obs_nr_var_join)
+}
+
+#' Join Data for "joined" functions
+#'
+#' The helper function joins the data for the "joined" functions. All `.join`
+#' variables are included in the output dataset. It is called by
+#' `get_joined_data()` to process each by group separately. This reduces the
+#' memory consumption.
+#'
+#' @inheritParams get_joined_data
+#'
+#' @details
+#'
+#' 1. The input dataset (`dataset`) and the additional dataset (`dataset_add`)
+#' are left joined by the grouping variables (`by_vars`). If no grouping
+#' variables are specified, a full join is performed.
+#'
+#' 1. The joined dataset is restricted as specified by arguments `join_type`,
+#' `first_cond_upper`, and `first_cond_lower`. See argument descriptions for
+#' details.
+#'
+#' 1. The joined dataset is restricted by the `filter_join` condition.
+#'
+#' @keywords internal
+get_joined_sub_data <- function(dataset,
+                                dataset_add,
+                                by_vars,
+                                tmp_obs_nr_var,
+                                tmp_obs_nr_left,
+                                join_type,
+                                first_cond_upper,
+                                first_cond_lower,
+                                filter_join) {
   data_joined <-
     left_join(
-      data,
-      select(
-        data_add,
-        !!!by_vars,
-        !!!replace_values_by_names(extract_vars(order)),
-        !!!replace_values_by_names(join_vars),
-        !!tmp_obs_nr_var
-      ),
-      by = vars2chr(by_vars_left),
+      dataset,
+      dataset_add,
+      by = vars2chr(by_vars),
       suffix = c("", ".join")
     )
 
@@ -837,7 +912,7 @@ get_joined_data <- function(dataset,
     # select all observations up to the first confirmation observation
     data_joined <- filter_relative(
       data_joined,
-      by_vars = expr_c(by_vars_left, tmp_obs_nr_var),
+      by_vars = expr_c(by_vars, tmp_obs_nr_var),
       condition = !!first_cond_upper,
       order = exprs(!!parse_expr(paste0(as_name(tmp_obs_nr_var), ".join"))),
       mode = "first",
@@ -851,7 +926,7 @@ get_joined_data <- function(dataset,
     # select all observations up to the first confirmation observation
     data_joined <- filter_relative(
       data_joined,
-      by_vars = expr_c(by_vars_left, tmp_obs_nr_var),
+      by_vars = expr_c(by_vars, tmp_obs_nr_var),
       condition = !!first_cond_lower,
       order = exprs(!!parse_expr(paste0("desc(", as_name(tmp_obs_nr_var), ".join)"))),
       mode = "first",
@@ -862,9 +937,7 @@ get_joined_data <- function(dataset,
   }
   # apply confirmation condition, which may include summary functions
   data_joined %>%
-    group_by(!!!by_vars_left, !!tmp_obs_nr_left) %>%
+    group_by(!!!by_vars, !!tmp_obs_nr_left) %>%
     filter_if(filter_join) %>%
-    ungroup() %>%
-    remove_tmp_vars() %>%
-    select(-!!tmp_obs_nr_var_join)
+    ungroup()
 }