scala.collection.mutable.HashTable.scala Maven / Gradle / Ivy
Go to download
Show more of this group Show more artifacts with this name
Show all versions of scala-library Show documentation
Show all versions of scala-library Show documentation
Standard library for the Scala Programming Language
/* __ *\
** ________ ___ / / ___ Scala API **
** / __/ __// _ | / / / _ | (c) 2003-2013, LAMP/EPFL **
** __\ \/ /__/ __ |/ /__/ __ | http://www.scala-lang.org/ **
** /____/\___/_/ |_/____/_/ | | **
** |/ **
\* */
package scala
package collection
package mutable
import java.lang.Integer.{numberOfLeadingZeros, rotateRight}
import scala.util.hashing.byteswap32
/** This class can be used to construct data structures that are based
* on hashtables. Class `HashTable[A]` implements a hashtable
* that maps keys of type `A` to values of the fully abstract
* member type `Entry`. Classes that make use of `HashTable`
* have to provide an implementation for `Entry`.
*
* There are mainly two parameters that affect the performance of a hashtable:
* the initial size and the load factor. The size
* refers to the number of buckets in the hashtable, and the load
* factor is a measure of how full the hashtable is allowed to get before
* its size is automatically doubled. Both parameters may be changed by
* overriding the corresponding values in class `HashTable`.
*
* @author Matthias Zenger
* @author Martin Odersky
* @version 2.0, 31/12/2006
* @since 1
*
* @tparam A type of the elements contained in this hash table.
*/
trait HashTable[A, Entry >: Null <: HashEntry[A, Entry]] extends HashTable.HashUtils[A] {
// Replacing Entry type parameter by abstract type member here allows to not expose to public
// implementation-specific entry classes such as `DefaultEntry` or `LinkedEntry`.
// However, I'm afraid it's too late now for such breaking change.
import HashTable._
@transient protected var _loadFactor = defaultLoadFactor
/** The actual hash table.
*/
@transient protected var table: Array[HashEntry[A, Entry]] = new Array(initialCapacity)
/** The number of mappings contained in this hash table.
*/
@transient protected var tableSize: Int = 0
/** The next size value at which to resize (capacity * load factor).
*/
@transient protected var threshold: Int = initialThreshold(_loadFactor)
/** The array keeping track of the number of elements in 32 element blocks.
*/
@transient protected var sizemap: Array[Int] = null
@transient protected var seedvalue: Int = tableSizeSeed
protected def tableSizeSeed = Integer.bitCount(table.length - 1)
/** The initial size of the hash table.
*/
protected def initialSize: Int = 16
/** The initial threshold.
*/
private def initialThreshold(_loadFactor: Int): Int = newThreshold(_loadFactor, initialCapacity)
private def initialCapacity = capacity(initialSize)
private def lastPopulatedIndex = {
var idx = table.length - 1
while (table(idx) == null && idx > 0)
idx -= 1
idx
}
/**
* Initializes the collection from the input stream. `readEntry` will be called for each
* entry to be read from the input stream.
*/
private[collection] def init(in: java.io.ObjectInputStream, readEntry: => Entry) {
in.defaultReadObject
_loadFactor = in.readInt()
assert(_loadFactor > 0)
val size = in.readInt()
tableSize = 0
assert(size >= 0)
seedvalue = in.readInt()
val smDefined = in.readBoolean()
table = new Array(capacity(sizeForThreshold(_loadFactor, size)))
threshold = newThreshold(_loadFactor, table.length)
if (smDefined) sizeMapInit(table.length) else sizemap = null
var index = 0
while (index < size) {
addEntry(readEntry)
index += 1
}
}
/**
* Serializes the collection to the output stream by saving the load factor, collection
* size and collection entries. `writeEntry` is responsible for writing an entry to the stream.
*
* `foreachEntry` determines the order in which the key/value pairs are saved to the stream. To
* deserialize, `init` should be used.
*/
private[collection] def serializeTo(out: java.io.ObjectOutputStream, writeEntry: Entry => Unit) {
out.defaultWriteObject
out.writeInt(_loadFactor)
out.writeInt(tableSize)
out.writeInt(seedvalue)
out.writeBoolean(isSizeMapDefined)
foreachEntry(writeEntry)
}
/** Find entry with given key in table, null if not found.
*/
@deprecatedOverriding("No sensible way to override findEntry as private findEntry0 is used in multiple places internally.", "2.11.0")
protected def findEntry(key: A): Entry =
findEntry0(key, index(elemHashCode(key)))
private[this] def findEntry0(key: A, h: Int): Entry = {
var e = table(h).asInstanceOf[Entry]
while (e != null && !elemEquals(e.key, key)) e = e.next
e
}
/** Add entry to table
* pre: no entry with same key exists
*/
@deprecatedOverriding("No sensible way to override addEntry as private addEntry0 is used in multiple places internally.", "2.11.0")
protected def addEntry(e: Entry) {
addEntry0(e, index(elemHashCode(e.key)))
}
private[this] def addEntry0(e: Entry, h: Int) {
e.next = table(h).asInstanceOf[Entry]
table(h) = e
tableSize = tableSize + 1
nnSizeMapAdd(h)
if (tableSize > threshold)
resize(2 * table.length)
}
/** Find entry with given key in table, or add new one if not found.
* May be somewhat faster then `findEntry`/`addEntry` pair as it
* computes entry's hash index only once.
* Returns entry found in table or null.
* New entries are created by calling `createNewEntry` method.
*/
protected def findOrAddEntry[B](key: A, value: B): Entry = {
val h = index(elemHashCode(key))
val e = findEntry0(key, h)
if (e ne null) e else { addEntry0(createNewEntry(key, value), h); null }
}
/** Creates new entry to be immediately inserted into the hashtable.
* This method is guaranteed to be called only once and in case that the entry
* will be added. In other words, an implementation may be side-effecting.
*/
protected def createNewEntry[B](key: A, value: B): Entry
/** Remove entry from table if present.
*/
@deprecatedOverriding("Internal implementation does not admit sensible overriding of this method.", "2.11.0")
protected def removeEntry(key: A) : Entry = {
val h = index(elemHashCode(key))
var e = table(h).asInstanceOf[Entry]
if (e != null) {
if (elemEquals(e.key, key)) {
table(h) = e.next
tableSize = tableSize - 1
nnSizeMapRemove(h)
e.next = null
return e
} else {
var e1 = e.next
while (e1 != null && !elemEquals(e1.key, key)) {
e = e1
e1 = e1.next
}
if (e1 != null) {
e.next = e1.next
tableSize = tableSize - 1
nnSizeMapRemove(h)
e1.next = null
return e1
}
}
}
null
}
/** An iterator returning all entries.
*/
protected def entriesIterator: Iterator[Entry] = new AbstractIterator[Entry] {
val iterTable = table
var idx = lastPopulatedIndex
var es = iterTable(idx)
def hasNext = es != null
def next() = {
val res = es
es = es.next
while (es == null && idx > 0) {
idx = idx - 1
es = iterTable(idx)
}
res.asInstanceOf[Entry]
}
}
/** Avoid iterator for a 2x faster traversal. */
protected def foreachEntry[U](f: Entry => U) {
val iterTable = table
var idx = lastPopulatedIndex
var es = iterTable(idx)
while (es != null) {
val next = es.next // Cache next in case f removes es.
f(es.asInstanceOf[Entry])
es = next
while (es == null && idx > 0) {
idx -= 1
es = iterTable(idx)
}
}
}
/** Remove all entries from table
*/
protected def clearTable() {
var i = table.length - 1
while (i >= 0) { table(i) = null; i = i - 1 }
tableSize = 0
nnSizeMapReset(0)
}
private def resize(newSize: Int) {
val oldTable = table
table = new Array(newSize)
nnSizeMapReset(table.length)
var i = oldTable.length - 1
while (i >= 0) {
var e = oldTable(i)
while (e != null) {
val h = index(elemHashCode(e.key))
val e1 = e.next
e.next = table(h).asInstanceOf[Entry]
table(h) = e
e = e1
nnSizeMapAdd(h)
}
i = i - 1
}
threshold = newThreshold(_loadFactor, newSize)
}
/* Size map handling code */
/*
* The following three sizeMap* functions (Add, Remove, Reset)
* are used to update the size map of the hash table.
*
* The size map logically divides the hash table into `sizeMapBucketSize` element buckets
* by keeping an integer entry for each such bucket. Each integer entry simply denotes
* the number of elements in the corresponding bucket.
* Best understood through an example, see:
* table = [/, 1, /, 6, 90, /, -3, 5] (8 entries)
* sizemap = [ 2 | 3 ] (2 entries)
* where sizeMapBucketSize == 4.
*
* By default the size map is not initialized, so these methods don't do anything, thus,
* their impact on hash table performance is negligible. However, if the hash table
* is converted into a parallel hash table, the size map is initialized, as it will be needed
* there.
*/
@deprecatedOverriding("Internal implementation does not admit sensible overriding of this method.", "2.11.0")
protected def nnSizeMapAdd(h: Int) = if (sizemap ne null) {
sizemap(h >> sizeMapBucketBitSize) += 1
}
@deprecatedOverriding("Internal implementation does not admit sensible overriding of this method.", "2.11.0")
protected def nnSizeMapRemove(h: Int) = if (sizemap ne null) {
sizemap(h >> sizeMapBucketBitSize) -= 1
}
@deprecatedOverriding("Internal implementation does not admit sensible overriding of this method.", "2.11.0")
protected def nnSizeMapReset(tableLength: Int) = if (sizemap ne null) {
val nsize = calcSizeMapSize(tableLength)
if (sizemap.length != nsize) sizemap = new Array[Int](nsize)
else java.util.Arrays.fill(sizemap, 0)
}
private[collection] final def totalSizeMapBuckets = if (sizeMapBucketSize < table.length) 1 else table.length / sizeMapBucketSize
@deprecatedOverriding("Internal implementation does not admit sensible overriding of this method.", "2.11.0")
protected def calcSizeMapSize(tableLength: Int) = (tableLength >> sizeMapBucketBitSize) + 1
// discards the previous sizemap and only allocates a new one
protected def sizeMapInit(tableLength: Int) {
sizemap = new Array[Int](calcSizeMapSize(tableLength))
}
// discards the previous sizemap and populates the new one
@deprecatedOverriding("Internal implementation does not admit sensible overriding of this method.", "2.11.0")
protected def sizeMapInitAndRebuild() {
sizeMapInit(table.length)
// go through the buckets, count elements
var tableidx = 0
var bucketidx = 0
val tbl = table
var tableuntil = 0
if (tbl.length < sizeMapBucketSize) tableuntil = tbl.length else tableuntil = sizeMapBucketSize
val totalbuckets = totalSizeMapBuckets
while (bucketidx < totalbuckets) {
var currbucketsize = 0
while (tableidx < tableuntil) {
var e = tbl(tableidx)
while (e ne null) {
currbucketsize += 1
e = e.next
}
tableidx += 1
}
sizemap(bucketidx) = currbucketsize
tableuntil += sizeMapBucketSize
bucketidx += 1
}
}
private[collection] def printSizeMap() {
println(sizemap.toList)
}
@deprecatedOverriding("Internal implementation does not admit sensible overriding of this method.", "2.11.0")
protected def sizeMapDisable() = sizemap = null
@deprecatedOverriding("Internal implementation does not admit sensible overriding of this method.", "2.11.0")
protected def isSizeMapDefined = sizemap ne null
// override to automatically initialize the size map
protected def alwaysInitSizeMap = false
/* End of size map handling code */
protected def elemEquals(key1: A, key2: A): Boolean = (key1 == key2)
/**
* Note: we take the most significant bits of the hashcode, not the lower ones
* this is of crucial importance when populating the table in parallel
*/
protected final def index(hcode: Int): Int = {
val ones = table.length - 1
val exponent = Integer.numberOfLeadingZeros(ones)
(improve(hcode, seedvalue) >>> exponent) & ones
}
protected def initWithContents(c: HashTable.Contents[A, Entry]) = {
if (c != null) {
_loadFactor = c.loadFactor
table = c.table
tableSize = c.tableSize
threshold = c.threshold
seedvalue = c.seedvalue
sizemap = c.sizemap
}
if (alwaysInitSizeMap && sizemap == null) sizeMapInitAndRebuild()
}
private[collection] def hashTableContents = new HashTable.Contents(
_loadFactor,
table,
tableSize,
threshold,
seedvalue,
sizemap
)
}
private[collection] object HashTable {
/** The load factor for the hash table (in 0.001 step).
*/
private[collection] final def defaultLoadFactor: Int = 750 // corresponds to 75%
private[collection] final def loadFactorDenum = 1000 // should be loadFactorDenom, but changing that isn't binary compatible
private[collection] final def newThreshold(_loadFactor: Int, size: Int) = ((size.toLong * _loadFactor) / loadFactorDenum).toInt
private[collection] final def sizeForThreshold(_loadFactor: Int, thr: Int) = ((thr.toLong * loadFactorDenum) / _loadFactor).toInt
private[collection] final def capacity(expectedSize: Int) = nextPositivePowerOfTwo(expectedSize)
trait HashUtils[KeyType] {
protected final def sizeMapBucketBitSize = 5
// so that:
protected final def sizeMapBucketSize = 1 << sizeMapBucketBitSize
protected def elemHashCode(key: KeyType) = key.##
/**
* Defer to a high-quality hash in [[scala.util.hashing]].
* The goal is to distribute across bins as well as possible even if a hash code has low entropy at some bits.
*
* OLD VERSION - quick, but bad for sequence 0-10000 - little entropy in higher bits - since 2003
* {{{
* var h: Int = hcode + ~(hcode << 9)
* h = h ^ (h >>> 14)
* h = h + (h << 4)
* h ^ (h >>> 10)
* }}}
* the rest of the computation is due to scala/bug#5293
*/
protected final def improve(hcode: Int, seed: Int): Int = rotateRight(byteswap32(hcode), seed)
}
/**
* Returns a power of two >= `target`.
*/
private[collection] def nextPositivePowerOfTwo(target: Int): Int = 1 << -numberOfLeadingZeros(target - 1)
class Contents[A, Entry >: Null <: HashEntry[A, Entry]](
val loadFactor: Int,
val table: Array[HashEntry[A, Entry]],
val tableSize: Int,
val threshold: Int,
val seedvalue: Int,
val sizemap: Array[Int]
) {
import scala.collection.DebugUtils._
private[collection] def debugInformation = buildString {
append =>
append("Hash table contents")
append("-------------------")
append("Table: [" + arrayString(table, 0, table.length) + "]")
append("Table size: " + tableSize)
append("Load factor: " + loadFactor)
append("Seedvalue: " + seedvalue)
append("Threshold: " + threshold)
append("Sizemap: [" + arrayString(sizemap, 0, sizemap.length) + "]")
}
}
}