Kotlin:更新不可变列表元素

Question

Kotlin初学者在这里.如何获取列表而不进行变更,创建第二个(不可变)列表,在特定索引处包含一个更新元素？

我正在考虑两种方式,这两种方式似乎都可能导致性能下降,改变底层对象,或两者兼而有之.

data class Player(val name: String, val score: Int = 0)

val players: List<Player> = ...

// Do I do this?
val updatedPlayers1 = players.mapIndexed { i, player ->
    if (i == 2) player.copy(score = 100)
    else player
}

// Or this?
val updatedPlayer = players[2].copy(score = 100)
val mutable = players.toMutableList()
mutable.set(2, updatedPlayer)
val updatedPlayers2 = mutable.toList()

如果没有高效的方法,那么Kotlin stdlib或其他库中是否有更合适的数据结构？Kotlin似乎没有载体.

Answer 1

对我来说显然第二种方式应该更快,但多少？

所以我在这里写了一些基准

@State(Scope.Thread)
open class ModifyingImmutableList {

    @Param("10", "100", "10000", "1000000")
    var size: Int = 0

    lateinit var players: List<Player>

    @Setup
    fun setup() {
        players = generatePlayers(size)
    }

    @Benchmark fun iterative(): List<Player> {
        return players.mapIndexed { i, player ->
            if (i == 2) player.copy(score = 100)
            else player
        }
    }

    @Benchmark fun toMutable(): List<Player> {
        val updatedPlayer = players[2].copy(score = 100)
        val mutable = players.toMutableList()
        mutable.set(2, updatedPlayer)
        return mutable.toList()
    }

    @Benchmark fun toArrayList(): List<Player> {
        val updatedPlayer = players[2].copy(score = 100)
        return players.set(2, updatedPlayer)
    }
}

得到以下结果:

$ java -jar target/benchmarks.jar -f 5 -wi 5 ModifyingImmutableList
Benchmark                            (size)   Mode  Cnt         Score        Error  Units
ModifyingImmutableList.iterative         10  thrpt  100   6885018.769 ± 189148.764  ops/s
ModifyingImmutableList.iterative        100  thrpt  100    877403.066 ±  20792.117  ops/s
ModifyingImmutableList.iterative      10000  thrpt  100     10456.272 ±    382.177  ops/s
ModifyingImmutableList.iterative    1000000  thrpt  100       108.167 ±      3.506  ops/s
ModifyingImmutableList.toArrayList       10  thrpt  100  33278431.127 ± 560577.516  ops/s
ModifyingImmutableList.toArrayList      100  thrpt  100  11009646.095 ± 180549.177  ops/s
ModifyingImmutableList.toArrayList    10000  thrpt  100    129167.033 ±   2532.945  ops/s
ModifyingImmutableList.toArrayList  1000000  thrpt  100       528.502 ±     16.451  ops/s
ModifyingImmutableList.toMutable         10  thrpt  100  19679357.039 ± 338925.701  ops/s
ModifyingImmutableList.toMutable        100  thrpt  100   5504388.388 ± 102757.671  ops/s
ModifyingImmutableList.toMutable      10000  thrpt  100     62809.131 ±   1070.111  ops/s
ModifyingImmutableList.toMutable    1000000  thrpt  100       258.013 ±      8.076  ops/s

所以这个测试表明,迭代收集大约慢3~6倍,即复制.另外,我提供了我的实现:toArray,看起来更高效.

在10元素上,toArray方法具有33278431.127 ± 560577.516每秒吞吐量操作.它慢吗？或者它的速度非常快？我写了"基线"测试,它显示了复制Players和变异数组的成本.结果有趣:

@Benchmark fun baseline(): List<Player> {
    val updatedPlayer = players[2].copy(score = 100)
    mutable[2] = updatedPlayer;
    return mutable
}

哪里可变 - 只是MutableList,这是ArrayList.

$ java -jar target/benchmarks.jar -f 5 -wi 5 ModifyingImmutableList
Benchmark                            (size)   Mode  Cnt         Score         Error  Units
ModifyingImmutableList.baseline          10  thrpt  100  81026110.043 ± 1076989.958  ops/s
ModifyingImmutableList.baseline         100  thrpt  100  81299168.496 ±  910200.124  ops/s
ModifyingImmutableList.baseline       10000  thrpt  100  81854190.779 ± 1010264.620  ops/s
ModifyingImmutableList.baseline     1000000  thrpt  100  83906022.547 ±  615205.008  ops/s
ModifyingImmutableList.toArrayList       10  thrpt  100  33090236.757 ±  518459.863  ops/s
ModifyingImmutableList.toArrayList      100  thrpt  100  11074338.763 ±  138272.711  ops/s
ModifyingImmutableList.toArrayList    10000  thrpt  100    131486.634 ±    1188.045  ops/s
ModifyingImmutableList.toArrayList  1000000  thrpt  100       531.425 ±      18.513  ops/s

在10个元素上,我们有2x回归,而在100万个大约150000x!

所以看起来ArrayList不是不可变数据结构的最佳选择.但是还有很多其他系列,其中一个是pcollections.让我们看看他们在我们的场景中得到了什么:

@Benchmark fun pcollections(): List<Player> {
    val updatedPlayer = players[2].copy(score = 100)
    return pvector.with(2, updatedPlayer)
}

pvector在哪里pvector:PVector<Player> = TreePVector.from(players).

$ java -jar target/benchmarks.jar -f 5 -wi 5 ModifyingImmutableList
Benchmark                             (size)   Mode  Cnt         Score         Error  Units
ModifyingImmutableList.baseline           10  thrpt  100  79462416.691 ± 1391446.159  ops/s
ModifyingImmutableList.baseline          100  thrpt  100  79991447.499 ± 1328008.619  ops/s
ModifyingImmutableList.baseline        10000  thrpt  100  80017095.482 ± 1385143.058  ops/s
ModifyingImmutableList.baseline      1000000  thrpt  100  81358696.411 ± 1308714.098  ops/s
ModifyingImmutableList.pcollections       10  thrpt  100  15665979.142 ±  371910.991  ops/s
ModifyingImmutableList.pcollections      100  thrpt  100   9419433.113 ±  161562.675  ops/s
ModifyingImmutableList.pcollections    10000  thrpt  100   4747628.815 ±   81192.752  ops/s
ModifyingImmutableList.pcollections  1000000  thrpt  100   3011819.457 ±   45548.403  ops/s

好结果!在100万个案例中,我们的执行速度只有27倍,这非常酷,但在小型集合pcollections上ArrayList实现速度稍微慢一点.

更新:正如@mfulton26所述,在toMutable基准测试中toList是不必要的,所以我删除它并重新运行测试.此外,我TreePVector从现有阵列添加基准的创建成本:

$ java -jar target/benchmarks.jar  ModifyingImmutableList
Benchmark                                 (size)   Mode  Cnt         Score         Error  Units
ModifyingImmutableList.baseline               10  thrpt  200  77639718.988 ± 1384171.128  ops/s
ModifyingImmutableList.baseline              100  thrpt  200  75978576.147 ± 1528533.332  ops/s
ModifyingImmutableList.baseline            10000  thrpt  200  79041238.378 ± 1137107.301  ops/s
ModifyingImmutableList.baseline          1000000  thrpt  200  84739641.265 ±  557334.317  ops/s

ModifyingImmutableList.iterative              10  thrpt  200   7389762.016 ±   72981.918  ops/s
ModifyingImmutableList.iterative             100  thrpt  200    956362.269 ±   11642.808  ops/s
ModifyingImmutableList.iterative           10000  thrpt  200     10953.451 ±     121.175  ops/s
ModifyingImmutableList.iterative         1000000  thrpt  200       115.379 ±       1.301  ops/s

ModifyingImmutableList.pcollections           10  thrpt  200  15984856.119 ±  162075.427  ops/s
ModifyingImmutableList.pcollections          100  thrpt  200   9322011.769 ±  176301.745  ops/s
ModifyingImmutableList.pcollections        10000  thrpt  200   4854742.140 ±   69066.751  ops/s
ModifyingImmutableList.pcollections      1000000  thrpt  200   3064251.812 ±   35972.244  ops/s

ModifyingImmutableList.pcollectionsFrom       10  thrpt  200   1585762.689 ±   20972.881  ops/s
ModifyingImmutableList.pcollectionsFrom      100  thrpt  200     67107.504 ±     808.308  ops/s
ModifyingImmutableList.pcollectionsFrom    10000  thrpt  200       268.268 ±       2.901  ops/s
ModifyingImmutableList.pcollectionsFrom  1000000  thrpt  200         1.406 ±       0.015  ops/s

ModifyingImmutableList.toArrayList            10  thrpt  200  34567833.775 ±  423910.463  ops/s
ModifyingImmutableList.toArrayList           100  thrpt  200  11395084.257 ±   76689.517  ops/s
ModifyingImmutableList.toArrayList         10000  thrpt  200    134299.055 ±     602.848  ops/s
ModifyingImmutableList.toArrayList       1000000  thrpt  200       549.064 ±      15.317  ops/s

ModifyingImmutableList.toMutable              10  thrpt  200  32441627.735 ±  391890.514  ops/s
ModifyingImmutableList.toMutable             100  thrpt  200  11505955.564 ±   71394.457  ops/s
ModifyingImmutableList.toMutable           10000  thrpt  200    134819.741 ±     526.830  ops/s
ModifyingImmutableList.toMutable         1000000  thrpt  200       561.031 ±       8.117  ops/s

Answer 2

Kotlin的List接口用于对列表进行"只读访问",这些列表不一定是不可变列表.不可通过接口强制执行不变性.在某些情况下,Kotlin的stdlib 当前的toList调用实现,toMutableList并将其结果作为"只读访问"返回List.

如果你有一个List玩家,并希望有效地让另一个List玩家获得更新的元素,那么一个简单的解决方案是将列表复制到a MutableList,更新所需的元素,然后只使用Kotlin的"读取"存储对结果列表的引用.只访问" List界面:

val updatedPlayers: List<Player> = players.toMutableList().apply {
    this[2] = updatedPlayer
}

如果这是您打算经常做的事情,您可以考虑创建一个扩展函数来封装实现细节:

inline fun <T> List<T>.copy(mutatorBlock: MutableList<T>.() -> Unit): List<T> {
    return toMutableList().apply(mutatorBlock)
}

然后,您可以更流畅地复制具有更新的列表(类似于数据类复制),而无需显式指定结果类型:

val updatedPlayers = players.copy { this[2] = updatedPlayer }