高效的多维可变 Scala 数组

Efficient Multi dimenstion Mutable Scala Array

是否有内存高效的 Scala 多维数组,例如 Java?

我正在尝试解决 Hackerrank 内存限制严格的问题:256mb。我的解决方案在使用 (39384,39384) 元素创建二维数组时因内存不足错误而中断:

Array.ofDim[Long](39384,39384)

scala 控制台中也会发生同样的情况。

java.lang.OutOfMemoryError: Java heap space
        at scala.reflect.ManifestFactory$$anon.newArray(Manifest.scala:115)
        at scala.reflect.ManifestFactory$$anon.newArray(Manifest.scala:113)
        at scala.Array$.ofDim(Array.scala:222)
        at Solution$.solve(Solution.scala:4)
        at Solution$$anonfun$main.apply$mcVI$sp(Solution.scala:41)
        at scala.collection.immutable.Range.foreach$mVc$sp(Range.scala:160)
        at Solution$.main(Solution.scala:37)
        at Solution.main(Solution.scala)
        at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
        at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
        at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
        at java.lang.reflect.Method.invoke(Method.java:606)
        at scala.reflect.internal.util.ScalaClassLoader$$anonfun$run.apply(ScalaClassLoader.scala:68)
        at scala.reflect.internal.util.ScalaClassLoader$class.asContext(ScalaClassLoader.scala:31)
        at scala.reflect.internal.util.ScalaClassLoader$URLClassLoader.asContext(ScalaClassLoader.scala:99)
        at scala.reflect.internal.util.ScalaClassLoader$class.run(ScalaClassLoader.scala:68)
        at scala.reflect.internal.util.ScalaClassLoader$URLClassLoader.run(ScalaClassLoader.scala:99)
        at scala.tools.nsc.CommonRunner$class.run(ObjectRunner.scala:22)
        at scala.tools.nsc.ObjectRunner$.run(ObjectRunner.scala:39)
        at scala.tools.nsc.CommonRunner$class.runAndCatch(ObjectRunner.scala:29)
        at scala.tools.nsc.ObjectRunner$.runAndCatch(ObjectRunner.scala:39)
        at scala.tools.nsc.MainGenericRunner.runTarget(MainGenericRunner.scala:72)
        at scala.tools.nsc.MainGenericRunner.process(MainGenericRunner.scala:94)
        at scala.tools.nsc.MainGenericRunner$.main(MainGenericRunner.scala:103)
        at scala.tools.nsc.MainGenericRunner.main(MainGenericRunner.scala)

Array.ofDim[Long](39384,39384) 创建大小为 39384 * 39384 * Long = 1551099456 * 8 = 11 Gb 的数组,这显然大于 256 Mb。只需尝试更少的维度,看看它是如何工作的:

scala> Array.ofDim[Long](3,3)
res10: Array[Array[Long]] = Array(Array(0, 0, 0), Array(0, 0, 0), Array(0, 0, 0))

如果您需要对大型几何图形进行一些坐标处理 space - 您可以创建 Map[Point, Long] 个桥,例如 Map(Point(39382, 9000) -> 5L, Point(1,0) -> 9L)

如果您实际上只需要两个数组(每个数组大小为 39384)- 那么只需创建两个数组 Array.ofDim[Long](39384,2)

P.S。如果您的算法具有可扩展性,您还可以使用 Apache Spark 的多个节点进行计算。