fastaggregation.go

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 {

				answer.highlowcontainer.appendContainer(s1, x1.highlowcontainer.getContainerAtIndex(pos1).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 {

				answer.highlowcontainer.appendContainer(s1, x1.highlowcontainer.getWritableContainerAtIndex(pos1).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())
				}
			}
		}
	}
}

// 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
}