--- /dev/null
+library(RPostgreSQL)
+library(data.table)
+
+nb_curves_per_request <- 5 # curves per (insert) request
+#tot_nb_curves <- 25e3 # total number of curves
+#dimension <- 17519 # number of sample points
+#nb_clust <- 15 # number of clusters
+temp_file <- "tmp_curves_batch" # (accessible) temporary file to store curves
+
+# Init connection with DB
+driver <- PostgreSQL(fetch.default.rec = nb_curves_per_request)
+con <- dbConnect(driver, user = "irsdi", password = "irsdi2017",
+ host = "localhost", port = "5432", dbname = "edf25m")
+
+setwd("~/tmp/")
+ref_centroids <- fread("2009_matrix-dt.csv")
+#ref_centroids <- sapply(1:nb_clust, function(k) cumsum(rnorm(dimension)))
+
+genRandCurves <- function(line, times) {
+ #ids <- as.integer(sprintf("%04i", seq_len(times) - 1)) * 1e6 + line[1]
+ ids <- as.integer(sprintf("%010i", (seq_len(times) - 1) * 1e6 + line[1]))
+ curve <- as.matrix(line[-1])
+ # simus <- lapply(1:times, function(i) line[-1] * runif(length(curve), .95, 1.05))
+ perturbances <- matrix(runif(length(curve) * times, .95, 1.05), nrow = times)
+ #curves_sim <- cbind(ids, t(apply(perturbances, 1, FUN = '*', curve)))
+ curves_sim <- data.frame(ids, t(apply(perturbances, 1, FUN = '*', curve)))
+ # series in columns, data as data.frame (as fwrite requests)
+ return(curves_sim)
+}
+
+# Loop: generate nb_curves_per_request curves, store them on a temp file,
+# and insert into DB using COPY command (should be faster than insert)
+system.time(
+ for (i in seq_len(nrow(ref_centroids))) {
+ curves <- genRandCurves(line = as.matrix(ref_centroids[i, ]), times = nb_curves_per_request)
+ fwrite(curves, temp_file, append = FALSE, sep = ",", col.names = FALSE)
+ # Required hack: add brackets (PostgreSQL syntax ...)
+ system(paste("sed -i 's/\\(.*\\)/{\\1}/g' ", temp_file, sep = ''))
+ query <- paste("COPY series (curve) FROM '", normalizePath(temp_file), "';", sep = '')
+ dbSendQuery(con, query)
+ }
+)
+
+dbDisconnect(con)
+unlink(temp_file)