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fastaggregation.go
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/
fastaggregation.go
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package roaring
import (
"container/heap"
)
// Or function that requires repairAfterLazy
func lazyOR(x1, x2 *Bitmap) *Bitmap {
answer := NewBitmap()
pos1 := 0
pos2 := 0
length1 := x1.highlowcontainer.size()
length2 := x2.highlowcontainer.size()
main:
for (pos1 < length1) && (pos2 < length2) {
s1 := x1.highlowcontainer.getKeyAtIndex(pos1)
s2 := x2.highlowcontainer.getKeyAtIndex(pos2)
for {
if s1 < s2 {
answer.highlowcontainer.appendCopy(x1.highlowcontainer, pos1)
pos1++
if pos1 == length1 {
break main
}
s1 = x1.highlowcontainer.getKeyAtIndex(pos1)
} else if s1 > s2 {
answer.highlowcontainer.appendCopy(x2.highlowcontainer, pos2)
pos2++
if pos2 == length2 {
break main
}
s2 = x2.highlowcontainer.getKeyAtIndex(pos2)
} else {
c1 := x1.highlowcontainer.getContainerAtIndex(pos1)
switch t := c1.(type) {
case *arrayContainer:
c1 = t.toBitmapContainer()
case *runContainer16:
if !t.isFull() {
c1 = t.toBitmapContainer()
}
}
answer.highlowcontainer.appendContainer(s1, c1.lazyOR(x2.highlowcontainer.getContainerAtIndex(pos2)), false)
pos1++
pos2++
if (pos1 == length1) || (pos2 == length2) {
break main
}
s1 = x1.highlowcontainer.getKeyAtIndex(pos1)
s2 = x2.highlowcontainer.getKeyAtIndex(pos2)
}
}
}
if pos1 == length1 {
answer.highlowcontainer.appendCopyMany(x2.highlowcontainer, pos2, length2)
} else if pos2 == length2 {
answer.highlowcontainer.appendCopyMany(x1.highlowcontainer, pos1, length1)
}
return answer
}
// In-place Or function that requires repairAfterLazy
func (x1 *Bitmap) lazyOR(x2 *Bitmap) *Bitmap {
answer := NewBitmap() // TODO: we return a new bitmap... could be optimized
pos1 := 0
pos2 := 0
length1 := x1.highlowcontainer.size()
length2 := x2.highlowcontainer.size()
main:
for (pos1 < length1) && (pos2 < length2) {
s1 := x1.highlowcontainer.getKeyAtIndex(pos1)
s2 := x2.highlowcontainer.getKeyAtIndex(pos2)
for {
if s1 < s2 {
answer.highlowcontainer.appendWithoutCopy(x1.highlowcontainer, pos1)
pos1++
if pos1 == length1 {
break main
}
s1 = x1.highlowcontainer.getKeyAtIndex(pos1)
} else if s1 > s2 {
answer.highlowcontainer.appendCopy(x2.highlowcontainer, pos2)
pos2++
if pos2 == length2 {
break main
}
s2 = x2.highlowcontainer.getKeyAtIndex(pos2)
} else {
c1 := x1.highlowcontainer.getContainerAtIndex(pos1)
switch t := c1.(type) {
case *arrayContainer:
c1 = t.toBitmapContainer()
case *runContainer16:
if !t.isFull() {
c1 = t.toBitmapContainer()
}
case *bitmapContainer:
c1 = x1.highlowcontainer.getWritableContainerAtIndex(pos1)
}
answer.highlowcontainer.appendContainer(s1, c1.lazyIOR(x2.highlowcontainer.getContainerAtIndex(pos2)), false)
pos1++
pos2++
if (pos1 == length1) || (pos2 == length2) {
break main
}
s1 = x1.highlowcontainer.getKeyAtIndex(pos1)
s2 = x2.highlowcontainer.getKeyAtIndex(pos2)
}
}
}
if pos1 == length1 {
answer.highlowcontainer.appendCopyMany(x2.highlowcontainer, pos2, length2)
} else if pos2 == length2 {
answer.highlowcontainer.appendWithoutCopyMany(x1.highlowcontainer, pos1, length1)
}
return answer
}
// to be called after lazy aggregates
func (x1 *Bitmap) repairAfterLazy() {
for pos := 0; pos < x1.highlowcontainer.size(); pos++ {
c := x1.highlowcontainer.getContainerAtIndex(pos)
switch c.(type) {
case *bitmapContainer:
if c.(*bitmapContainer).cardinality == invalidCardinality {
c = x1.highlowcontainer.getWritableContainerAtIndex(pos)
c.(*bitmapContainer).computeCardinality()
if c.(*bitmapContainer).getCardinality() <= arrayDefaultMaxSize {
x1.highlowcontainer.setContainerAtIndex(pos, c.(*bitmapContainer).toArrayContainer())
} else if c.(*bitmapContainer).isFull() {
x1.highlowcontainer.setContainerAtIndex(pos, newRunContainer16Range(0, MaxUint16))
}
}
}
}
}
// FastAnd computes the intersection between many bitmaps quickly
// Compared to the And function, it can take many bitmaps as input, thus saving the trouble
// of manually calling "And" many times.
func FastAnd(bitmaps ...*Bitmap) *Bitmap {
if len(bitmaps) == 0 {
return NewBitmap()
} else if len(bitmaps) == 1 {
return bitmaps[0].Clone()
}
answer := And(bitmaps[0], bitmaps[1])
for _, bm := range bitmaps[2:] {
answer.And(bm)
}
return answer
}
// FastOr computes the union between many bitmaps quickly, as opposed to having to call Or repeatedly.
// It might also be faster than calling Or repeatedly.
func FastOr(bitmaps ...*Bitmap) *Bitmap {
if len(bitmaps) == 0 {
return NewBitmap()
} else if len(bitmaps) == 1 {
return bitmaps[0].Clone()
}
answer := lazyOR(bitmaps[0], bitmaps[1])
for _, bm := range bitmaps[2:] {
answer = answer.lazyOR(bm)
}
// here is where repairAfterLazy is called.
answer.repairAfterLazy()
return answer
}
// HeapOr computes the union between many bitmaps quickly using a heap.
// It might be faster than calling Or repeatedly.
func HeapOr(bitmaps ...*Bitmap) *Bitmap {
if len(bitmaps) == 0 {
return NewBitmap()
}
// TODO: for better speed, we could do the operation lazily, see Java implementation
pq := make(priorityQueue, len(bitmaps))
for i, bm := range bitmaps {
pq[i] = &item{bm, i}
}
heap.Init(&pq)
for pq.Len() > 1 {
x1 := heap.Pop(&pq).(*item)
x2 := heap.Pop(&pq).(*item)
heap.Push(&pq, &item{Or(x1.value, x2.value), 0})
}
return heap.Pop(&pq).(*item).value
}
// HeapXor computes the symmetric difference between many bitmaps quickly (as opposed to calling Xor repeated).
// Internally, this function uses a heap.
// It might be faster than calling Xor repeatedly.
func HeapXor(bitmaps ...*Bitmap) *Bitmap {
if len(bitmaps) == 0 {
return NewBitmap()
}
pq := make(priorityQueue, len(bitmaps))
for i, bm := range bitmaps {
pq[i] = &item{bm, i}
}
heap.Init(&pq)
for pq.Len() > 1 {
x1 := heap.Pop(&pq).(*item)
x2 := heap.Pop(&pq).(*item)
heap.Push(&pq, &item{Xor(x1.value, x2.value), 0})
}
return heap.Pop(&pq).(*item).value
}