循环遍历R中的数量级

data <- rnorm(1e8)  # 生成一个包含一亿个随机数的向量

sum_of_squares <- 0
for (i in seq_along(data)) {
  sum_of_squares <- sum_of_squares + data[i]^2
}
print(sum_of_squares)

library(parallel)
num_cores <- detectCores() - 1
cl <- makeCluster(num_cores)
sum_of_squares_parallel <- parSapply(cl, data, function(x) x^2)
stopCluster(cl)
print(sum(sum_of_squares_parallel))

library(data.table)
chunk_size <- 1e6
num_chunks <- ceiling(length(data) / chunk_size)

sum_of_squares_chunked <- 0
for (i in seq_len(num_chunks)) {
  start_idx <- (i - 1) * chunk_size + 1
  end_idx <- min(i * chunk_size, length(data))
  chunk <- data[start_idx:end_idx]
  sum_of_squares_chunked <- sum_of_squares_chunked + sum(chunk^2)
}
print(sum_of_squares_chunked)