script to parse results into R

process_metrics.R

@@ -0,0 +1,61 @@
+library(jsonlite)
+
+process_app_results <- function(dir) {
+  files <- list.files(dir, pattern="*.json")
+
+  results <- list()
+
+  for (f in files) {
+    fres <- list()
+    info = strsplit(f, "_")
+
+    fres[["dataset"]] <- info[[1]][1]
+    fres[["run"]] <- info[[1]][2]
+
+    metrics =  jsonlite::fromJSON(file.path(dir, f))
+    fres[["time"]] <- metrics[["CustomTotalAnalysisTime"]]
+    fres[["jsTotalHeapSize"]] <- metrics[["JSHeapTotalSize"]]
+    fres[["JSHeapUsedSize"]] <- metrics[["JSHeapUsedSize"]]
+
+    results[[f]] <- fres
+  }
+
+  as.data.frame(do.call(rbind, lapply(results, as.vector)))
+}
+
+
+process_cli_results <- function(dir) {
+  dirs <- dir(dir)
+
+  results <- list()
+
+  for (d in dirs) {
+    runs <- list.files(file.path(dir, d))
+
+    for (r in runs) {
+
+      fres <- list()
+
+      fres[["dataset"]] <- d
+      fres[["run"]] <- r
+
+      metrics <- readLines(file.path(dir, d, r))
+
+      usertime <- metrics[19]
+      memory <- metrics[27]
+
+      fres[["time"]] <- strsplit(usertime, ":")[[1]][2]
+
+      fres[["maxResidentSetSize"]] <- strsplit(memory, ":")[[1]][2]
+
+      results[[file.path(dir, d, r)]] <- fres
+
+    } 
+  }
+
+  as.data.frame(do.call(rbind, lapply(results, as.vector)))
+
+}
+
+df_app <- process_app_results("./app-results")
+df_cli <- process_cli_results("./cli-results")