c# - 为什么在排序输入上插入到我的树中比随机输入更快？-6ren

c# - 为什么在排序输入上插入到我的树中比随机输入更快？

转载作者：IT王子更新时间：2023-10-29 04:38:20

现在我总是听说从随机选择的数据构建二叉搜索树比有序数据更快，这仅仅是因为有序数据需要显式重新平衡以保持树的高度最小。

最近我实现了一个不可变的 treap ，一种特殊的二叉搜索树，它使用随机化来保持自身相对平衡。与我的预期相反，我发现与无序数据相比，我可以始终如一地以快 2 倍的速度构建 treap，并且通常更好地平衡有序数据——我不知道为什么。

这是我的 treap 实现:

http://pastebin.com/VAfSJRwZ

这是一个测试程序:

using System;
using System.Collections.Generic;
using System.Linq;
using System.Diagnostics;

namespace ConsoleApplication1
{

    class Program
    {
        static Random rnd = new Random();
        const int ITERATION_COUNT = 20;

        static void Main(string[] args)
        {
            List<double> rndTimes = new List<double>();
            List<double> orderedTimes = new List<double>();

            rndTimes.Add(TimeIt(50, RandomInsert));
            rndTimes.Add(TimeIt(100, RandomInsert));
            rndTimes.Add(TimeIt(200, RandomInsert));
            rndTimes.Add(TimeIt(400, RandomInsert));
            rndTimes.Add(TimeIt(800, RandomInsert));
            rndTimes.Add(TimeIt(1000, RandomInsert));
            rndTimes.Add(TimeIt(2000, RandomInsert));
            rndTimes.Add(TimeIt(4000, RandomInsert));
            rndTimes.Add(TimeIt(8000, RandomInsert));
            rndTimes.Add(TimeIt(16000, RandomInsert));
            rndTimes.Add(TimeIt(32000, RandomInsert));
            rndTimes.Add(TimeIt(64000, RandomInsert));
            rndTimes.Add(TimeIt(128000, RandomInsert));
            string rndTimesAsString = string.Join("\n", rndTimes.Select(x => x.ToString()).ToArray());

            orderedTimes.Add(TimeIt(50, OrderedInsert));
            orderedTimes.Add(TimeIt(100, OrderedInsert));
            orderedTimes.Add(TimeIt(200, OrderedInsert));
            orderedTimes.Add(TimeIt(400, OrderedInsert));
            orderedTimes.Add(TimeIt(800, OrderedInsert));
            orderedTimes.Add(TimeIt(1000, OrderedInsert));
            orderedTimes.Add(TimeIt(2000, OrderedInsert));
            orderedTimes.Add(TimeIt(4000, OrderedInsert));
            orderedTimes.Add(TimeIt(8000, OrderedInsert));
            orderedTimes.Add(TimeIt(16000, OrderedInsert));
            orderedTimes.Add(TimeIt(32000, OrderedInsert));
            orderedTimes.Add(TimeIt(64000, OrderedInsert));
            orderedTimes.Add(TimeIt(128000, OrderedInsert));
            string orderedTimesAsString = string.Join("\n", orderedTimes.Select(x => x.ToString()).ToArray());

            Console.WriteLine("Done");
        }

        static double TimeIt(int insertCount, Action<int> f)
        {
            Console.WriteLine("TimeIt({0}, {1})", insertCount, f.Method.Name);

            List<double> times = new List<double>();
            for (int i = 0; i < ITERATION_COUNT; i++)
            {
                Stopwatch sw = Stopwatch.StartNew();
                f(insertCount);
                sw.Stop();
                times.Add(sw.Elapsed.TotalMilliseconds);
            }

            return times.Average();
        }

        static void RandomInsert(int insertCount)
        {
            Treap<double> tree = new Treap<double>((x, y) => x.CompareTo(y));
            for (int i = 0; i < insertCount; i++)
            {
                tree = tree.Insert(rnd.NextDouble());
            }
        }

        static void OrderedInsert(int insertCount)
        {
            Treap<double> tree = new Treap<double>((x, y) => x.CompareTo(y));
            for(int i = 0; i < insertCount; i++)
            {
                tree = tree.Insert(i + rnd.NextDouble());
            }
        }
    }
}

这是一张以毫秒为单位比较随机和有序插入时间的图表:

Insertions         Random          Ordered         RandomTime / OrderedTime
50                 1.031665        0.261585        3.94
100                0.544345        1.377155        0.4
200                1.268320        0.734570        1.73
400                2.765555        1.639150        1.69
800                6.089700        3.558350        1.71
1000               7.855150        4.704190        1.67
2000               17.852000       12.554065       1.42
4000               40.157340       22.474445       1.79
8000               88.375430       48.364265       1.83
16000              197.524000      109.082200      1.81
32000              459.277050      238.154405      1.93
64000              1055.508875     512.020310      2.06
128000             2481.694230     1107.980425     2.24

我在代码中没有看到任何使有序输入比无序输入渐进更快的东西，所以我无法解释其中的差异。

为什么从有序输入构建 treap 比随机输入快得多？

最佳答案

我运行了你的代码，我认为它与旋转次数有关。在有序输入时，旋转次数是最优的，树永远不会旋转回来。

在随机输入过程中，树将不得不执行更多的旋转，因为它可能不得不来回旋转。

要真正找出答案，我必须为每次运行的左右旋转次数添加计数器。你可能可以自己做。

更新:

我在 rotateleft 和 rotateright 上设置了断点。在有序输入期间，从不使用 rotateright。随机输入的时候，两个都命中，我觉得用的比较频繁。

更新 2:

我向 50 项有序运行添加了一些输出(为清楚起见用整数代替)，以了解更多信息:

TimeIt(50, OrderedInsert)
LastValue = 0, Top.Value = 0, Right.Count = 0, Left.Count = 0
RotateLeft @value=0
LastValue = 1, Top.Value = 1, Right.Count = 0, Left.Count = 1
LastValue = 2, Top.Value = 1, Right.Count = 1, Left.Count = 1
LastValue = 3, Top.Value = 1, Right.Count = 2, Left.Count = 1
RotateLeft @value=3
RotateLeft @value=2
RotateLeft @value=1
LastValue = 4, Top.Value = 4, Right.Count = 0, Left.Count = 4
LastValue = 5, Top.Value = 4, Right.Count = 1, Left.Count = 4
LastValue = 6, Top.Value = 4, Right.Count = 2, Left.Count = 4
RotateLeft @value=6
LastValue = 7, Top.Value = 4, Right.Count = 3, Left.Count = 4
LastValue = 8, Top.Value = 4, Right.Count = 4, Left.Count = 4
RotateLeft @value=8
RotateLeft @value=7
LastValue = 9, Top.Value = 4, Right.Count = 5, Left.Count = 4
LastValue = 10, Top.Value = 4, Right.Count = 6, Left.Count = 4
RotateLeft @value=10
RotateLeft @value=9
RotateLeft @value=5
RotateLeft @value=4
LastValue = 11, Top.Value = 11, Right.Count = 0, Left.Count = 11
LastValue = 12, Top.Value = 11, Right.Count = 1, Left.Count = 11
RotateLeft @value=12
LastValue = 13, Top.Value = 11, Right.Count = 2, Left.Count = 11
RotateLeft @value=13
LastValue = 14, Top.Value = 11, Right.Count = 3, Left.Count = 11
LastValue = 15, Top.Value = 11, Right.Count = 4, Left.Count = 11
RotateLeft @value=15
RotateLeft @value=14
LastValue = 16, Top.Value = 11, Right.Count = 5, Left.Count = 11
LastValue = 17, Top.Value = 11, Right.Count = 6, Left.Count = 11
RotateLeft @value=17
LastValue = 18, Top.Value = 11, Right.Count = 7, Left.Count = 11
LastValue = 19, Top.Value = 11, Right.Count = 8, Left.Count = 11
RotateLeft @value=19
LastValue = 20, Top.Value = 11, Right.Count = 9, Left.Count = 11
LastValue = 21, Top.Value = 11, Right.Count = 10, Left.Count = 11
RotateLeft @value=21
LastValue = 22, Top.Value = 11, Right.Count = 11, Left.Count = 11
RotateLeft @value=22
RotateLeft @value=20
RotateLeft @value=18
LastValue = 23, Top.Value = 11, Right.Count = 12, Left.Count = 11
LastValue = 24, Top.Value = 11, Right.Count = 13, Left.Count = 11
LastValue = 25, Top.Value = 11, Right.Count = 14, Left.Count = 11
RotateLeft @value=25
RotateLeft @value=24
LastValue = 26, Top.Value = 11, Right.Count = 15, Left.Count = 11
LastValue = 27, Top.Value = 11, Right.Count = 16, Left.Count = 11
RotateLeft @value=27
LastValue = 28, Top.Value = 11, Right.Count = 17, Left.Count = 11
RotateLeft @value=28
RotateLeft @value=26
RotateLeft @value=23
RotateLeft @value=16
RotateLeft @value=11
LastValue = 29, Top.Value = 29, Right.Count = 0, Left.Count = 29
LastValue = 30, Top.Value = 29, Right.Count = 1, Left.Count = 29
LastValue = 31, Top.Value = 29, Right.Count = 2, Left.Count = 29
LastValue = 32, Top.Value = 29, Right.Count = 3, Left.Count = 29
RotateLeft @value=32
RotateLeft @value=31
LastValue = 33, Top.Value = 29, Right.Count = 4, Left.Count = 29
RotateLeft @value=33
RotateLeft @value=30
LastValue = 34, Top.Value = 29, Right.Count = 5, Left.Count = 29
RotateLeft @value=34
LastValue = 35, Top.Value = 29, Right.Count = 6, Left.Count = 29
LastValue = 36, Top.Value = 29, Right.Count = 7, Left.Count = 29
LastValue = 37, Top.Value = 29, Right.Count = 8, Left.Count = 29
RotateLeft @value=37
LastValue = 38, Top.Value = 29, Right.Count = 9, Left.Count = 29
LastValue = 39, Top.Value = 29, Right.Count = 10, Left.Count = 29
RotateLeft @value=39
LastValue = 40, Top.Value = 29, Right.Count = 11, Left.Count = 29
RotateLeft @value=40
RotateLeft @value=38
RotateLeft @value=36
LastValue = 41, Top.Value = 29, Right.Count = 12, Left.Count = 29
LastValue = 42, Top.Value = 29, Right.Count = 13, Left.Count = 29
RotateLeft @value=42
LastValue = 43, Top.Value = 29, Right.Count = 14, Left.Count = 29
LastValue = 44, Top.Value = 29, Right.Count = 15, Left.Count = 29
RotateLeft @value=44
LastValue = 45, Top.Value = 29, Right.Count = 16, Left.Count = 29
LastValue = 46, Top.Value = 29, Right.Count = 17, Left.Count = 29
RotateLeft @value=46
RotateLeft @value=45
LastValue = 47, Top.Value = 29, Right.Count = 18, Left.Count = 29
LastValue = 48, Top.Value = 29, Right.Count = 19, Left.Count = 29
LastValue = 49, Top.Value = 29, Right.Count = 20, Left.Count = 29

自然地，有序的项目总是被添加到树的右侧。当右侧大于左侧时，就会发生 rotateleft。向右旋转永远不会发生。每次树翻倍时，都会大致选择一个新的顶部节点。优先级值的随机性使它有点抖动，因此在这次运行中它变为 0、1、4、11、29。

随机运行揭示了一些有趣的东西:

TimeIt(50, RandomInsert)
LastValue = 0,748661640914465, Top.Value = 0,748661640914465, Right.Count = 0, Left.Count = 0
LastValue = 0,669427539533669, Top.Value = 0,748661640914465, Right.Count = 0, Left.Count = 1
RotateRight @value=0,669427539533669
LastValue = 0,318363281115127, Top.Value = 0,748661640914465, Right.Count = 0, Left.Count = 2
RotateRight @value=0,669427539533669
LastValue = 0,33133987678743, Top.Value = 0,748661640914465, Right.Count = 0, Left.Count = 3
RotateLeft @value=0,748661640914465
LastValue = 0,955126694382693, Top.Value = 0,955126694382693, Right.Count = 0, Left.Count = 4
RotateRight @value=0,669427539533669
RotateLeft @value=0,33133987678743
RotateLeft @value=0,318363281115127
RotateRight @value=0,748661640914465
RotateRight @value=0,955126694382693
LastValue = 0,641024029180884, Top.Value = 0,641024029180884, Right.Count = 3, Left.Count = 2
LastValue = 0,20709771951991, Top.Value = 0,641024029180884, Right.Count = 3, Left.Count = 3
LastValue = 0,830862050331599, Top.Value = 0,641024029180884, Right.Count = 4, Left.Count = 3
RotateRight @value=0,20709771951991
RotateRight @value=0,318363281115127
LastValue = 0,203250563798123, Top.Value = 0,641024029180884, Right.Count = 4, Left.Count = 4
RotateLeft @value=0,669427539533669
RotateRight @value=0,748661640914465
RotateRight @value=0,955126694382693
LastValue = 0,701743399585478, Top.Value = 0,641024029180884, Right.Count = 5, Left.Count = 4
RotateLeft @value=0,669427539533669
RotateRight @value=0,701743399585478
RotateLeft @value=0,641024029180884
LastValue = 0,675667521858433, Top.Value = 0,675667521858433, Right.Count = 4, Left.Count = 6
RotateLeft @value=0,33133987678743
RotateLeft @value=0,318363281115127
RotateLeft @value=0,203250563798123
LastValue = 0,531275219531392, Top.Value = 0,675667521858433, Right.Count = 4, Left.Count = 7
RotateRight @value=0,748661640914465
RotateRight @value=0,955126694382693
RotateLeft @value=0,701743399585478
LastValue = 0,704049674190604, Top.Value = 0,675667521858433, Right.Count = 5, Left.Count = 7
RotateRight @value=0,203250563798123
RotateRight @value=0,531275219531392
RotateRight @value=0,641024029180884
RotateRight @value=0,675667521858433
LastValue = 0,161392807104342, Top.Value = 0,161392807104342, Right.Count = 13, Left.Count = 0
RotateRight @value=0,203250563798123
RotateRight @value=0,531275219531392
RotateRight @value=0,641024029180884
RotateRight @value=0,675667521858433
RotateLeft @value=0,161392807104342
LastValue = 0,167598206162266, Top.Value = 0,167598206162266, Right.Count = 13, Left.Count = 1
LastValue = 0,154996359793002, Top.Value = 0,167598206162266, Right.Count = 13, Left.Count = 2
RotateLeft @value=0,33133987678743
LastValue = 0,431767346538495, Top.Value = 0,167598206162266, Right.Count = 14, Left.Count = 2
RotateRight @value=0,203250563798123
RotateRight @value=0,531275219531392
RotateRight @value=0,641024029180884
RotateRight @value=0,675667521858433
RotateLeft @value=0,167598206162266
LastValue = 0,173774613614089, Top.Value = 0,173774613614089, Right.Count = 14, Left.Count = 3
RotateRight @value=0,830862050331599
LastValue = 0,76559642412029, Top.Value = 0,173774613614089, Right.Count = 15, Left.Count = 3
RotateRight @value=0,76559642412029
RotateLeft @value=0,748661640914465
RotateRight @value=0,955126694382693
RotateLeft @value=0,704049674190604
RotateLeft @value=0,675667521858433
LastValue = 0,75742144871383, Top.Value = 0,173774613614089, Right.Count = 16, Left.Count = 3
LastValue = 0,346844367844446, Top.Value = 0,173774613614089, Right.Count = 17, Left.Count = 3
RotateRight @value=0,830862050331599
LastValue = 0,787565814232251, Top.Value = 0,173774613614089, Right.Count = 18, Left.Count = 3
LastValue = 0,734950566540915, Top.Value = 0,173774613614089, Right.Count = 19, Left.Count = 3
RotateLeft @value=0,20709771951991
RotateRight @value=0,318363281115127
RotateLeft @value=0,203250563798123
RotateRight @value=0,531275219531392
RotateRight @value=0,641024029180884
RotateRight @value=0,675667521858433
RotateRight @value=0,75742144871383
RotateLeft @value=0,173774613614089
LastValue = 0,236504829598826, Top.Value = 0,236504829598826, Right.Count = 17, Left.Count = 6
RotateLeft @value=0,830862050331599
RotateLeft @value=0,787565814232251
RotateLeft @value=0,76559642412029
RotateRight @value=0,955126694382693
LastValue = 0,895606500048007, Top.Value = 0,236504829598826, Right.Count = 18, Left.Count = 6
LastValue = 0,599106418713511, Top.Value = 0,236504829598826, Right.Count = 19, Left.Count = 6
LastValue = 0,8182332901369, Top.Value = 0,236504829598826, Right.Count = 20, Left.Count = 6
RotateRight @value=0,734950566540915
LastValue = 0,704216948572647, Top.Value = 0,236504829598826, Right.Count = 21, Left.Count = 6
RotateLeft @value=0,346844367844446
RotateLeft @value=0,33133987678743
RotateRight @value=0,431767346538495
RotateLeft @value=0,318363281115127
RotateRight @value=0,531275219531392
RotateRight @value=0,641024029180884
RotateRight @value=0,675667521858433
RotateRight @value=0,75742144871383
LastValue = 0,379157059536854, Top.Value = 0,236504829598826, Right.Count = 22, Left.Count = 6
RotateLeft @value=0,431767346538495
LastValue = 0,46832062046431, Top.Value = 0,236504829598826, Right.Count = 23, Left.Count = 6
RotateRight @value=0,154996359793002
LastValue = 0,0999000217299443, Top.Value = 0,236504829598826, Right.Count = 23, Left.Count = 7
RotateLeft @value=0,20709771951991
LastValue = 0,229543754006524, Top.Value = 0,236504829598826, Right.Count = 23, Left.Count = 8
RotateRight @value=0,8182332901369
LastValue = 0,80358425984326, Top.Value = 0,236504829598826, Right.Count = 24, Left.Count = 8
RotateRight @value=0,318363281115127
LastValue = 0,259324726769386, Top.Value = 0,236504829598826, Right.Count = 25, Left.Count = 8
RotateRight @value=0,318363281115127
LastValue = 0,307835293145774, Top.Value = 0,236504829598826, Right.Count = 26, Left.Count = 8
RotateLeft @value=0,431767346538495
LastValue = 0,453910283024381, Top.Value = 0,236504829598826, Right.Count = 27, Left.Count = 8
RotateLeft @value=0,830862050331599
LastValue = 0,868997387527021, Top.Value = 0,236504829598826, Right.Count = 28, Left.Count = 8
RotateLeft @value=0,20709771951991
RotateRight @value=0,229543754006524
RotateLeft @value=0,203250563798123
LastValue = 0,218358597354199, Top.Value = 0,236504829598826, Right.Count = 28, Left.Count = 9
RotateRight @value=0,0999000217299443
RotateRight @value=0,161392807104342
LastValue = 0,0642934488431986, Top.Value = 0,236504829598826, Right.Count = 28, Left.Count = 10
RotateRight @value=0,154996359793002
RotateLeft @value=0,0999000217299443
LastValue = 0,148295871982489, Top.Value = 0,236504829598826, Right.Count = 28, Left.Count = 11
LastValue = 0,217621828065078, Top.Value = 0,236504829598826, Right.Count = 28, Left.Count = 12
RotateRight @value=0,599106418713511
LastValue = 0,553135806020878, Top.Value = 0,236504829598826, Right.Count = 29, Left.Count = 12
LastValue = 0,982277666210326, Top.Value = 0,236504829598826, Right.Count = 30, Left.Count = 12
RotateRight @value=0,8182332901369
LastValue = 0,803671114520948, Top.Value = 0,236504829598826, Right.Count = 31, Left.Count = 12
RotateRight @value=0,203250563798123
RotateRight @value=0,218358597354199
LastValue = 0,19310415405459, Top.Value = 0,236504829598826, Right.Count = 31, Left.Count = 13
LastValue = 0,0133136604043253, Top.Value = 0,236504829598826, Right.Count = 31, Left.Count = 14
RotateLeft @value=0,46832062046431
RotateRight @value=0,531275219531392
RotateRight @value=0,641024029180884
RotateRight @value=0,675667521858433
RotateRight @value=0,75742144871383
LastValue = 0,483394719419719, Top.Value = 0,236504829598826, Right.Count = 32, Left.Count = 14
RotateLeft @value=0,431767346538495
RotateRight @value=0,453910283024381
LastValue = 0,453370328738061, Top.Value = 0,236504829598826, Right.Count = 33, Left.Count = 14
LastValue = 0,762330518459124, Top.Value = 0,236504829598826, Right.Count = 34, Left.Count = 14
LastValue = 0,699010426969738, Top.Value = 0,236504829598826, Right.Count = 35, Left.Count = 14

轮换的发生并不是因为树不平衡，而是因为随机选择的优先级。例如，我们在第 13 次插入时进行了 4 次旋转。我们有一棵树在 5/7 处平衡(很好)，但达到 13/0!随机优先级的使用似乎值得进一步研究。无论如何，很明显随机插入比有序插入导致更多的旋转。

关于c# - 为什么在排序输入上插入到我的树中比随机输入更快？，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/2437733/

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我有两张 table 。想象第一个是一个目录，包含很多文件(第二个表)。第二个表(文件)包含修改日期。现在，我想选择所有目录并按修改日期 ASC 对它们进行排序(因此，最新的修改最上面)。我不想显
mysql - 首先按(条件)排序，然后按(条件)排序
我想先根据用户的状态然后根据用户名来排序我的 sql 请求。该状态由 user_type 列设置: 1=活跃，2=不活跃，3=创始人。我会使用此请求来执行此操作，但它不起作用，因为我想在“活跃”成员
c++ - sort a, b, c是否等同于sort c；排序 b;排序？
在 C++ 中，我必须实现一个“类似 Excel/Access”(引用)的查询生成器，以允许对数据集进行自定义排序。如果您在 Excel 中使用查询构建器或 SQL 中的“ORDER BY a, b,
MongoDB 按字段 A 排序，如果字段 B != null 否则按字段 C 排序
我面临这样的挑战: 检索按字段 A 排序的文档如果字段 B 存在/不为空 . 否则按字段排序 C. 在 SQL 世界中，我会做两个查询并创建一个 UNION SELECT，但我不知道如何从 Mon
dart - 在 Dart 中，如何仅使用级联或链式调用来干净地映射/排序/折叠/排序/扩展？
我想对源列表执行以下操作: map 列表排序折叠排序展开列表其中一些方法(例如map和toList)是可链接的，因为它们返回非空对象。但是，sort 方法返回 void，因为它对 List
linux - 有人可以解释重新格式化 awk () | 输出的最佳方法吗？排序 | uniq-c |排序-rg？
我制作了一个用于分析 Windows 日志消息编号的脚本。 uniq -c 数字的输出很难预测，因为根据数字的大小会有不同的空白。此时，我手动删除了空白。这是对消息进行排序和计数的命令: cat n
python - 在 Python 字典中按值(降序)排序，然后按键(升序)排序
我有以下词典: mydict1 = {1: 11, 2: 4, 5: 1, 6: 1} mydict2 = {1: 1, 5: 1} 对于它们中的每一个，我想首先按值(降序)排序，然后按键(升序)排序
delphi - 如何使用多个比较器在 TObjectList<> 中进行类似于 Excel 的按 A 排序，然后按 B 排序
我刚刚开始使用泛型，目前在对多个字段进行排序时遇到问题。案例: 我有一个 PeopleList 作为 TObjectList我希望能够通过一次选择一个排序字段，但尽可能保留以前的排序来制作类似 Ex
sql - 如果 Column1 不为空，则按 Column1 排序，否则按 Column2 排序
有没有办法在 sql 中组合 ORDER BY 和 IS NULL 以便我可以在列不为空时按列排序，但如果它为null，按另一列排序？最佳答案类似于: ORDER BY CASE WHEN
mysql - 排序 mysql 结果。按 col1 排序，按 col2 分组
我有一个包含 2 列“id”和“name”的表。 id 是常规的自动增量索引，name 只是 varchar。 id name 1 john 2 mary 3 pop 4 mary 5 j
node.js - API 分页、过滤、排序 VS CLIENT 分页、过滤、排序
场景网站页面有一个带有分页、过滤、排序功能的表格 View 。表中的数据是从REST API服务器获取的，数据包含数百万条记录。数据库 REST API 服务器 Web 服务器浏览器问
objective-c - 获取 NSDictionary 键的 NSArray，按 Value 排序，然后按 Key 排序
假设我有一本字典，其中的键(单词)和值(分数)如下: GOD 8 DONG 16 DOG 8 XI 21 我想创建一个字典键(单词)的 NSArray，首先按分数排序，然后按字
mysql - sphinx 搜索查询前 20 个按标题 WEIGHT 排序，后 20 个按标题 ASC 排序，无重复输出
如何在 sphinx 上通过 sql 命令选择前 20 行按标题 WEIGHT 排序，接下来 20 行按标题 ASC 排序(总共 40 个结果)，但不要给出重复的标题输出。我尝试了这个 sql 命令
SQLite - 排序
我有一个奇怪的问题，当从 SQLite 数据库中选择信息并根据日期排序时，返回的结果无效。我的SQL语句是这样的: Select pk from usersDates order by dateti

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c# - 为什么在排序输入上插入到我的树中比随机输入更快？