In the 2018 Advent of Code<\/a> challenged I solved all the puzzles in Groovy<\/a>. It is pretty obvious, that choosing good data structure is the most important to obtain performant solution. However, the way we iterate over those structures is also very significant, at least when using Groovy.<\/p>\n I want to measure how long it takes to sum some numbers. For testing performance of loops I prepared a small function that simply sums some numbers:<\/p>\n Pseudo code for summing functions is below:<\/p>\n Let’s implement the summing function in various ways.<\/p>\n First loop type is to use built-in (by Groovy) function Next, let’s write the same function using Now instead of using Measuring performance<\/h2>\n
void printAddingTime(String message, long to, Closure<Long> adder) {\r\n LocalTime start = LocalTime.now()\r\n long sum = adder(to)\r\n println(\"$message: $sum calculated in ${Duration.between(start, LocalTime.now()).toMillis()} ms\")\r\n}<\/pre>\nfor i = 1 to n\r\n for j = 1 to n\r\n sum += i * j\r\n end\r\nend<\/pre>\n
Loops types<\/code><\/h2>\ncollect<\/code> and sum<\/code><\/h3>\ncollect<\/code> and sum<\/code> on collections (Range<\/code> it this example):<\/p>\n(1..n).collect { long i ->\r\n (1..n).collect { long j ->\r\n i * j\r\n }.sum()\r\n}.sum()<\/pre>\neach<\/code><\/h3>\neach<\/code> built-in function on collections (Range<\/code> it this example) and then add results to accumulator variable:<\/p>\nlong sum = 0\r\n(1..n).each { long i ->\r\n (1..n).each { long j ->\r\n sum += i * j\r\n }\r\n}\r\nreturn sum<\/pre>\ntimes<\/code><\/h3>\neach<\/code> we could use the function times<\/code> built-in on Number<\/code> by Groovy:<\/p>\nlong sum = 0\r\nn.times { long i ->\r\n n.times { long j ->\r\n sum += (i + 1)*(j+1)\r\n }\r\n}\r\nreturn sum<\/pre>\n