{"id":18000,"date":"2022-10-28T13:49:11","date_gmt":"2022-10-28T08:19:11","guid":{"rendered":"https:\/\/jassweb.com\/solved\/solved-create-hashset-with-a-large-number-of-elements-1m\/"},"modified":"2022-10-28T13:49:11","modified_gmt":"2022-10-28T08:19:11","slug":"solved-create-hashset-with-a-large-number-of-elements-1m","status":"publish","type":"post","link":"https:\/\/jassweb.com\/solved\/solved-create-hashset-with-a-large-number-of-elements-1m\/","title":{"rendered":"[Solved] Create Hashset with a large number of elements (1M)"},"content":{"rendered":"

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\n<\/p>\n

\n
\n
<\/div>\n
\n
\n

To build on @Enigmativity’s answer, here’s a proper benchmark using BenchmarkDotNet:<\/p>\n

public class Benchmark\n{\n    private const int N = 1000000;\n\n    [Benchmark]\n    public HashSet<int> EnumerableRange() => new HashSet<int>(Enumerable.Range(1, N + 1));\n\n    [Benchmark]\n    public HashSet<int> NoPreallocation()\n    {\n        var result = new HashSet<int>();\n        for (int n = 1; n < N + 1; n++)\n        {\n            result.Add(n);\n        }\n        return result;\n    }\n\n    [Benchmark]\n    public HashSet<int> Preallocation()\n    {\n        var result = new HashSet<int>(N);\n        for (int n = 1; n < N + 1; n++)\n        {\n            result.Add(n);\n        }\n        return result;\n    }\n}\n\npublic class Program\n{\n    public static void Main(string[] args)\n    {\n        BenchmarkRunner.Run(typeof(Program).Assembly);\n    }\n}\n<\/code><\/pre>\n
With the results:<\/p>\n
\n\n\n\n\n\n\n\n
Method<\/th>\nMean<\/th>\nError<\/th>\nStdDev<\/th>\n<\/tr>\n<\/thead>\n
EnumerableRange<\/td>\n29.17 ms<\/td>\n0.743 ms<\/td>\n2.179 ms<\/td>\n<\/tr>\n
NoPreallocation<\/td>\n23.96 ms<\/td>\n0.471 ms<\/td>\n0.775 ms<\/td>\n<\/tr>\n
Preallocation<\/td>\n11.68 ms<\/td>\n0.233 ms<\/td>\n0.665 ms<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n
As we can see, using linq is a bit slower than not using linq (as expected), and pre-allocating saves a significant amount of time.<\/p>\n<\/p><\/div>\n
<\/div>\n<\/div>\n
            1<\/span> <\/p><\/div>\n<\/div>\n
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solved Create Hashset with a large number of elements (1M) <\/p>\n","protected":false},"excerpt":{"rendered":"
[ad_1] To build on @Enigmativity’s answer, here’s a proper benchmark using BenchmarkDotNet: public class Benchmark { private const int N = 1000000; [Benchmark] public HashSet<int> EnumerableRange() => new HashSet<int>(Enumerable.Range(1, N + 1)); [Benchmark] public HashSet<int> NoPreallocation() { var result = new HashSet<int>(); for (int n = 1; n < N + 1; n++) { result.Add(n); … Read more<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[320],"tags":[352,324,325],"class_list":["post-18000","post","type-post","status-publish","format-standard","hentry","category-solved","tag-net","tag-c","tag-performance"],"yoast_head":"\n[Solved] Create Hashset with a large number of elements (1M) - JassWeb<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/jassweb.com\/solved\/solved-create-hashset-with-a-large-number-of-elements-1m\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"[Solved] Create Hashset with a large number of elements (1M) - JassWeb\" \/>\n<meta property=\"og:description\" content=\"[ad_1] To build on @Enigmativity’s answer, here’s a proper benchmark using BenchmarkDotNet: public class Benchmark { private const int N = 1000000; [Benchmark] public HashSet<int> EnumerableRange() => new HashSet<int>(Enumerable.Range(1, N + 1)); [Benchmark] public HashSet<int> NoPreallocation() { var result = new HashSet<int>(); for (int n = 1; n < N + 1; n++) { result.Add(n); ... 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