com.facebook.presto.geospatial.rtree.Flatbush Maven / Gradle / Ivy
/*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package com.facebook.presto.geospatial.rtree;
import com.facebook.presto.common.array.DoubleBigArray;
import com.facebook.presto.geospatial.Rectangle;
import com.google.common.annotations.VisibleForTesting;
import it.unimi.dsi.fastutil.ints.IntArrayList;
import org.openjdk.jol.info.ClassLayout;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Comparator;
import java.util.List;
import java.util.function.Consumer;
import static com.google.common.base.Preconditions.checkArgument;
import static io.airlift.slice.SizeOf.sizeOf;
import static java.lang.Math.max;
import static java.lang.Math.min;
import static java.util.Objects.requireNonNull;
/**
* A fast, low memory footprint static RTree.
*
* Packed Hilbert RTrees -- aka Flatbushes -- create very few objects, instead
* storing the tree in a flat array. They support the standard RTree queries,
* but cannot be modified once built. It is quite possible to semi-efficiently
* remove objects.
*
* Consider an RTree with branching factor `b`. Each non-leaf node has two
* pieces of information:
* 1. The minimum bounding box of all descendants, and
* 2. Pointers to its children.
*
* The former is simply four doubles. The latter can be derived from the
* node's level and which sibling it is. This means we can actually flatten
* the tree into a single array of doubles, four per node. We can
* programmatically find the indices of a node's children (it will be faster if
* we pre-compute level offsets), and do envelope checks with just float
* operations. "padded" empty nodes will have NaN entries, which will naturally
* return false for all comparison operators, thus being automatically not
* selected.
*
* A critical choice in RTree implementation is how to group leaf nodes as
* children (and recursively, their parents). One method that is very efficient
* to construct and comparable to best lookup performance is sorting by an
* object's Hilbert curve index. Hilbert curves are naturally hierarchical, so
* successively grouping children and their parents will give a naturally nested
* structure. This means we only need to sort the items once.
*
* If sort time is a problem, we actually just need to "partition" into groups
* of `degree`, since the order of the children of a single parent doesn't
* matter. This could be done with quicksort, stopping once all items at index
* `n * degree` are correctly placed.
*
* Original implementation in JavaScript: https://github.com/mourner/flatbush
*/
public class Flatbush
{
// Number of coordinates to define an envelope
@VisibleForTesting
static final int ENVELOPE_SIZE = 4;
private static final int INSTANCE_SIZE = ClassLayout.parseClass(Flatbush.class).instanceSize();
private static final int DEFAULT_DEGREE = 16;
// Number of children per node
private final int degree;
// Offsets in tree for each level
private final int[] levelOffsets;
// Each node has four doubles: xMin, yMin, xMax, yMax
private final DoubleBigArray tree;
private final T[] items;
/**
* Build Flatbush RTree for `items`.
*
* @param items Items to index.
* @param degree Number of children for each intermediate node.
*/
public Flatbush(T[] items, int degree)
{
checkArgument(degree > 0, "degree must be positive");
this.degree = degree;
this.items = requireNonNull(items, "items is null");
this.levelOffsets = calculateLevelOffsets(items.length, degree);
this.tree = buildTree();
}
/**
* Build Flatbush RTree for `items` with default number of children per node.
*
* This will use the default degree.
*
* @param items Items to index.
*/
public Flatbush(T[] items)
{
this(items, DEFAULT_DEGREE);
}
/**
* Calculate the indices for each level.
*
* A given level contains a certain number of items. We give it a capacity
* equal to the next multiple of `degree`, so that each parent will have
* an equal number (`degree`) of children. This means the next level will
* have `capacity/degree` nodes, which yields a capacity equal to the next
* multiple, and so on, until the number of items is 1.
*
* Since we are storing each node as 4 doubles, we will actually multiply
* every index by 4.
*/
private static int[] calculateLevelOffsets(int numItems, int degree)
{
List offsets = new ArrayList<>();
// Leaf nodes start at 0, root is the last element.
offsets.add(0);
int level = 0;
while (numItems > 1) {
// The number of children will be the smallest multiple of degree >= numItems
int numChildren = (int) Math.ceil(1.0 * numItems / degree) * degree;
offsets.add(offsets.get(level) + ENVELOPE_SIZE * numChildren);
numItems = numChildren / degree;
level += 1;
}
return offsets.stream().mapToInt(Integer::intValue).toArray();
}
private DoubleBigArray buildTree()
{
// We initialize it to NaN, because all comparisons with NaN are false.
// Thus the normal intersection logic will not select uninitialized
// nodes.
DoubleBigArray tree = new DoubleBigArray(Double.NaN);
tree.ensureCapacity(levelOffsets[levelOffsets.length - 1] + ENVELOPE_SIZE);
if (items.length > degree) {
sortByHilbertIndex(items);
}
int writeOffset = 0;
for (T item : items) {
tree.set(writeOffset++, item.getExtent().getXMin());
tree.set(writeOffset++, item.getExtent().getYMin());
tree.set(writeOffset++, item.getExtent().getXMax());
tree.set(writeOffset++, item.getExtent().getYMax());
}
int numChildren = items.length;
for (int level = 0; level < levelOffsets.length - 1; level++) {
int readOffset = levelOffsets[level];
writeOffset = levelOffsets[level + 1];
int numParents = 0;
double xMin = Double.POSITIVE_INFINITY;
double yMin = Double.POSITIVE_INFINITY;
double xMax = Double.NEGATIVE_INFINITY;
double yMax = Double.NEGATIVE_INFINITY;
int child = 0;
for (; child < numChildren; child++) {
xMin = min(xMin, tree.get(readOffset++));
yMin = min(yMin, tree.get(readOffset++));
xMax = max(xMax, tree.get(readOffset++));
yMax = max(yMax, tree.get(readOffset++));
if ((child + 1) % degree == 0) {
numParents++;
tree.set(writeOffset++, xMin);
tree.set(writeOffset++, yMin);
tree.set(writeOffset++, xMax);
tree.set(writeOffset++, yMax);
xMin = Double.POSITIVE_INFINITY;
yMin = Double.POSITIVE_INFINITY;
xMax = Double.NEGATIVE_INFINITY;
yMax = Double.NEGATIVE_INFINITY;
}
}
if (child % degree != 0) {
numParents++;
tree.set(writeOffset++, xMin);
tree.set(writeOffset++, yMin);
tree.set(writeOffset++, xMax);
tree.set(writeOffset++, yMax);
}
numChildren = numParents;
}
return tree;
}
/**
* Find intersection candidates for `query` rectangle.
*
* This will feed to `consumer` each object in the rtree whose bounding
* rectangle intersects the query rectangle. The actual intersection
* check will need to be performed by the caller.
*
* @param query Rectangle for which to search for intersection.
* @param consumer Function to call for each intersection candidate.
*/
public void findIntersections(Rectangle query, Consumer consumer)
{
IntArrayList todoNodes = new IntArrayList(levelOffsets.length * degree);
IntArrayList todoLevels = new IntArrayList(levelOffsets.length * degree);
int rootLevel = levelOffsets.length - 1;
int rootIndex = levelOffsets[rootLevel];
if (doesIntersect(query, rootIndex)) {
todoNodes.push(rootIndex);
todoLevels.push(rootLevel);
}
while (!todoNodes.isEmpty()) {
int nodeIndex = todoNodes.popInt();
int level = todoLevels.popInt();
if (level == 0) {
// This is a leaf node
consumer.accept(items[nodeIndex / ENVELOPE_SIZE]);
}
else {
int childrenOffset = getChildrenOffset(nodeIndex, level);
for (int i = 0; i < degree; i++) {
int childIndex = childrenOffset + ENVELOPE_SIZE * i;
if (doesIntersect(query, childIndex)) {
todoNodes.push(childIndex);
todoLevels.push(level - 1);
}
}
}
}
}
private boolean doesIntersect(Rectangle query, int nodeIndex)
{
return query.getXMax() >= tree.get(nodeIndex) // xMin
&& query.getYMax() >= tree.get(nodeIndex + 1) // yMin
&& query.getXMin() <= tree.get(nodeIndex + 2) // xMax
&& query.getYMin() <= tree.get(nodeIndex + 3); // yMax
}
/**
* Get the offset of the first child for the node.
*
* @param nodeIndex Index in tree of first entry for node
* @param level Level of node
*/
@VisibleForTesting
int getChildrenOffset(int nodeIndex, int level)
{
int indexInLevel = nodeIndex - levelOffsets[level];
return levelOffsets[level - 1] + degree * indexInLevel;
}
@VisibleForTesting
int getHeight()
{
return levelOffsets.length;
}
/*
* Sorts items in-place by the Hilbert index of the envelope center.
*/
private void sortByHilbertIndex(T[] items)
{
if (items == null || items.length < 2) {
return;
}
Rectangle totalExtent = items[0].getExtent();
for (int i = 1; i < items.length; i++) {
totalExtent = totalExtent.merge(items[i].getExtent());
}
HilbertIndex hilbert = new HilbertIndex(totalExtent);
Arrays.parallelSort(items, Comparator.comparing(item ->
hilbert.indexOf(
(item.getExtent().getXMin() + item.getExtent().getXMax()) / 2,
(item.getExtent().getYMin() + item.getExtent().getYMax()) / 2)));
}
public boolean isEmpty()
{
return items.length == 0;
}
public long getEstimatedSizeInBytes()
{
long result = INSTANCE_SIZE + sizeOf(levelOffsets) + tree.sizeOf();
for (T item : items) {
result += item.getEstimatedSizeInBytes();
}
return result;
}
}