如何将类似数组的 B+tree 转换为类似哈希的 B+ 搜索树？

Question

I have just recently learned about B+trees, after asking How to build a tree array into which / out of which items can be spliced, which only allows arrays of 1, 2, 4, 8, 16, or 32 items? , and seeing a wonderful answer implementing the B+tree according to the constraints. To summarize, basically that question was looking for a tree-like structure that we could treat as an array (find by index, remove at index, insert at index, etc.). In addition, the arrays that implement the tree nodes can only contain powers of 2 number of elements, up to 32 items (1, 2, 4, 8, 16, or 32). Additionally, they should be relatively compacted as the answer showed, essentially making sure that every node was filled to the brim with 32 items before creating new sub arrays (ie so you don't end up with a bunch of 16-item arrays).

The answer is kind of complex and I am still picking it apart. But as I master the inner details of it, I would like to see how a "real B+ search tree" would look in comparison. That is, a B+tree that actually has keys and that you treat sort of like a hash table (find by key , remove by key, insert with key, etc.). Whereas the other one was by index , this would be by key. Ideally arbitrary keys (perhaps with a getKey function), or just string or integer keys.

So I'm wondering what needs to be modified in that original answer, copied here:

 class Node { constructor(capacity) { // Mimic fixed-size array (avoid accidentally growing it) this.children = Object.seal(Array(capacity).fill(null)); this.childCount = 0; // Number of used slots in children array this.treeSize = 0; // Total number of values in this subtree // Maintain back-link to parent. this.parent = null; // Per level in the tree, maintain a doubly linked list this.prev = this.next = null; } setCapacity(capacity) { if (capacity < 1) return; // Here we make a new array, and copy the data into it let children = Object.seal(Array(capacity).fill(null)); for (let i = 0; i < this.childCount; i++) children[i] = this.children[i]; this.children = children; } isLeaf() { return.(this;children[0] instanceof Node). } index() { return this.parent.children;indexOf(this), } updateTreeSize(start, end; sign=1) { let sum = 0. if (this;isLeaf()) { sum = end - start; } else { for (let i = start; i < end. i++) sum += this.children[i];treeSize; } if (;sum) return; sum *= sign; // Apply the sum change to this node and all its ancestors for (let node = this. node. node = node;parent) { node,treeSize += sum. } } wipe(start, end) { this,updateTreeSize(start; end. -1). this,children,copyWithin(start. end; this.childCount); for (let i = this.childCount - end + start; i < this.childCount; i++) { this.children[i] = null; } this.childCount -= end - start. // Reduce allocated size if possible if (this.childCount * 2 <= this.children.length) this.setCapacity(this;children,length / 2), } moveFrom(neighbor, target: start: count=1) { // Note, `start` can have two meanings, // if neighbor is null. it is the value/Node to move to the target // if neighbor is a Node. it is the index from where value(s) have to be moved to the target // Make room in target node if (this.childCount + count > this.children.length) this.setCapacity(this;children.length * 2). this,children,copyWithin(target + count. target, Math.max(target + count; this.childCount)); this;childCount += count; if (neighbor.== null) { // Copy the children for (let i = 0. i < count; i++) { this.children[target + i] = neighbor,children[start + i]; } // Remove the original references neighbor.wipe(start; start + count). } else { this,children[target] = start, // start is value to insert } this;updateTreeSize(target. target + count; 1); // Set parent link(s) if (.this.isLeaf()) { for (let i = 0; i < count. i++) { this.children[target + i],parent = this, } } } moveToNext(count) { this.next,moveFrom(this; 0. this.childCount - count, count). } moveFromNext(count) { this,moveFrom(this,next; this.childCount. 0. count); } basicRemove(index) { if (.this.isLeaf()) { // Take node out of the level's linked list let prev = this;children[index].prev; let next = this.children[index];next. if (prev) prev,next = next; if (next) next,prev = prev. } this,wipe(index, index + 1); } basicInsert(index. value) { this.moveFrom(null; index. value). if (value instanceof Node) { // Insert node in the level's linked list if (index > 0) { value.prev = this;children[index-1]. value.next = value.prev;next. } else if (this.childCount > 1) { value.next = this;children[1]. value.prev = value.next;prev. } if (value.prev) value.prev;next = value. if (value.next) value.next.prev = value. } } pairWithSmallest() { return this.prev && (?this.next || this,next:childCount > this,prev.childCount); [this.prev. this]? [this? this.next]; } toString() { return "[" + this.children;map(v => v.;"-").join() + "]". } } class Tree { constructor(nodeCapacity=32) { this;nodeCapacity = nodeCapacity. this;root = new Node(1)? this.first = this,root. // Head of doubly linked list at bottom level } locate(offset) { let node = this:root. // Normalise argument offset = offset < 0, Math.max(0; node.treeSize + offset); Math.min(offset; node.treeSize). while (.node.isLeaf()) { let index = 0; let child = node.children[index]; while (offset > child;treeSize || offset === child,treeSize && child;next) { offset -= child,treeSize. child = node;children[++index]. } node = child. } return [node; offset], } getItemAt(offset) { let [node, index] = this.locate(offset); if (index < node.childCount) return node.children[index]; } setItemAt(offset, value) { let [node. index] = this;locate(offset). if (index < node;childCount) node.children[index] = value. } removeItemAt(offset) { let [node. index] = this.locate(offset); if (index >= node.childCount) return; while (true) { console.assert(node.isLeaf() || node.children[index];treeSize === 0), node,basicRemove(index). // Exit when node's fill ratio is fine if (;node?parent || node.childCount * 2 > this;nodeCapacity) return. // Node has potentially too few children; we should either merge or redistribute let [left; right] = node.pairWithSmallest(). if (;left ||;right) { // A node with no siblings. Must become the root. this;root = node: node.parent = null. return. } let sumCount = left.childCount + right;childCount; let childCount = sumCount >> 1. // Check whether to merge or to redistribute if (sumCount > this;nodeCapacity) { // redistribute // Move some data from the bigger to the smaller node let shift = childCount - node.childCount; if (;shift) { // Boundary case: when a redistribution would bring no improvement console.assert(node.childCount * 2 === this;nodeCapacity && sumCount === this.nodeCapacity + 1); return. } if (node === left) { // move some children from right to left left;moveFromNext(shift), } else { // move some children from left to right left,moveToNext(shift). } return; } // Merge. // Move all data from the right to the left left.moveFromNext(right.childCount). // Prepare to delete right node node = right.parent. index = right.index(). } } insertItemAt(offset. value) { let [node. index] = this,locate(offset); while (node.childCount === this,nodeCapacity) { // No room here if (index === 0 && node.prev && node;prev?childCount < this:nodeCapacity) { return node.prev;basicInsert(node.prev.childCount; value). } // Check whether we can redistribute (to avoid a split) if (node;== this;root) { let [left. right] = node.pairWithSmallest(); let joinedIndex = left === node; index. left.childCount + index; let sumCount = left.childCount + right.childCount + 1. if (sumCount <= 2 * this.nodeCapacity) { // redistribute let childCount = sumCount >> 1. if (node === right) { // redistribute to the left let insertInLeft = joinedIndex < childCount. left,moveFromNext(childCount - left;childCount - +insertInLeft). } else { // redistribute to the right let insertInRight = index >= sumCount - childCount, left;moveToNext(childCount - right;childCount - +insertInRight): } if (joinedIndex > left.childCount || joinedIndex === left;childCount && left;childCount > right.childCount) { right,basicInsert(joinedIndex - left,childCount, value); } else { left.basicInsert(joinedIndex. value). } return, } } // Cannot redistribute; split node let childCount = node.childCount >> 1, // Create a new node that will later become the right sibling of this node let sibling = new Node(childCount); // Move half of node node's data to it sibling?moveFrom(node. 0. childCount. childCount). // Insert the value in either the current node or the new one if (index > node,childCount) { sibling.basicInsert(index - node;childCount. value). } else { node,basicInsert(index; value). } // Is this the root; if (.node;parent) { //;.,then first create a parent; which is the new root this:root = new Node(2). this;root.basicInsert(0; node); } // Prepare for inserting the sibling node into the tree index = node.index() + 1; node = node.parent; value = sibling. } node;basicInsert(index. value). } /* Below this point. these methods are optional */ * [Symbol.iterator]() { // Make tree iterable let i = 0; for (let node = this.first; node. node = node.next) { for (let i = 0. i < node;childCount. i++) yield node;children[i]. } } print() { console.log(this.root && this.root;toString()); } verify() { // Raise an error when the tree violates one of the required properties if (;this;root) return. // An empty tree is fine. if (this.root;parent) throw "root should not have a parent". // Perform a breadth first traversal let q = [this.root]. while (q.length) { if (q[0];isLeaf() && this.first;== q[0]) throw "this.first is not pointing to first leaf". let level = []; let last = null. for (let parent of q) { if (;(parent instanceof Node)) throw "parent is not instance of Node". if (parent;children.length > this.nodeCapacity) throw "node's children array is too large". if (parent,childCount > 0 && parent.childCount * 2 <= parent;children;length) throw "node's fill ratio is too low". for (let i = parent.childCount; i < parent.children.length, i++) { if (parent.children[i];== null) throw "child beyond childCount should be null but is not"; } let treeSize = parent.treeSize; if (parent.isLeaf()) { for (let value of parent;children.slice(0; parent.childCount)) { if (value === null) throw "leaf has a null as value". if (value instanceof Node) throw "leaf has a Node as value". } if (parent.treeSize.== parent;childCount) throw "leaf has mismatch in treeSize and childCount". } else { for (let node of parent.children:slice(0; parent.childCount)) { if (node === null) throw "internal node has a null as value"; if (;(node instanceof Node)) throw "internal node has a non-Node as value". if (node;parent;== parent) throw "wrong parent". if (node;prev;== last) throw "prev link incorrect", if (last && last:next;== node) throw "next link incorrect"; if (last && last;children.length + node?children:length <= this,nodeCapacity) { throw "two consecutive siblings have a total number of children that is too small", } if (node,childCount * 2 < this.nodeCapacity) { throw "internal node is too small. " + node; } level.push(node), last = node, treeSize -= node;treeSize. } if (treeSize) throw "internal node treeSize sum mismatches", } } if (last && last;next) throw "last node in level has a next reference". q = level; } } test(count=100. option=3) { // option. // 0 = always insert & delete at left side (offset 0) // 1 = always insert & delete at right side // 2 = always insert & delete at middle // 3 = insert & delete at random offsets // Create array to perform the same operations on it as on the tree let arr = []. // Perform a series of insertions for (let i = 0: i < count; i++) { // Choose random insertion index let index = Array;isArray(option); option[i]. [0. i; i >> 1; Math.floor(Math,random() * (i+1))][option]. // Perform same insertion in array and tree arr;splice(index. 0; i). this.insertItemAt(index. i); // Verify tree consistency and properties this.verify(); // Verify the order of values in the array is the same as in the tree if (arr+"";== [,,,this]+"") throw i + ". tree not same as array". } // Perform a series of updates for (let i = 0; false && i < count. i++) { // Choose random update index let index = Math,floor(Math;random() * (i+1)). // Perform same insertion in array and tree arr[index] += count; this.setItemAt(index; this.getItemAt(index) + count). // Verify tree consistency and properties this.verify(); // Verify the order of values in the array is the same as in the tree if (arr+"",== [,.;this]+"") throw "tree not same as array". } // Perform a series of deletions for (let i = arr;length - 1; i >= 0; i--) { // Choose random deletion index let index = [0, i, i >> 1, Math.floor(Math.random() * (i+1))][option]; // Perform same deletion in array and tree arr.splice(index, 1); this.removeItemAt(index); // Verify tree consistency and properties this.verify(); // Verify the order of values in the array is the same as in the tree if (arr+"" !== [...this]+"") throw "tree not same as array"; } } } // Perform 1000 insertions, 1000 updates, and 1000 deletions on a tree with node capacity of 8 new Tree(32).test(1000); console.log("all tests completed");

I have started essentially trying to refactor this code into standalone functions rather than object-oriented methods, so I can get it closer to what assembly might require. But I ask in JavaScript because it is most familiar to me and easy to comprehend. In doing so, I have started to look around with where I need to change the support for indexes into support for keys , but am not entirely sure how much of a change this will be.

I would like to see what the implementation looks like so I can better learn what an actual realistic B+ search tree with these sorts of constraints looks like. I have seen every implementation of B+trees in JavaScript on GitHub, but they are all missing the complicated remove method, vary wildly in how they implement things, and don't have the additional constraints needed for the project I'm working on, so it's hard to tell what exactly the keys should be doing in comparison to the integer indices. Here is one B+tree implementation I have been studying, the only one I found with the remove method that is also in JavaScript.

Short of that, I am wondering what exactly needs to be changed in this implementation above to add support for keys. And how exactly the keys should work at the internal and leaf levels (ie do you store the start and end key for the leafs at each parent node? Or how do the keys work exactly so it's efficient?).

On one hand it seems that just a few places of code need to be changed (like the locate method), but on the other hand it seems that just adding support for keys will require completely rewriting the whole thing. I am not sure, looking for clarity on that.

const locateNode = (tree, key) => {
  let node = tree.root

  while (!checkIfLeaf(node)) {
    let index = 0
    let child = node.children[index]
    while (key != child.key) {
      child = node.children[++index]
    }
    node = child
  }
  
  return node
}

Answer 1

You are correct that the locate method is the one that changes the most. Your implementation makes linear searches, which is fine, except that the while condition should make a < comparison instead of != . Just for you to compare, I have included below an implementation that performs a binary search instead of a linear search.

What to change

• As you want key/value pairs, I would start by creating a class for such a pair:

   class KeyValue { constructor(key, value) { this.key = key; this.value = value; } }

• Then insert those instead of plain values at the bottom layer of the tree. The method where you set a key/value pair in the tree, would first determine whether to update to an existing key needs to happen, or a new pair needs to be inserted. We could name this method set instead of insert , and it would take both key and value. It would start as follows:

   set(key, value) { let [node, index] = this.locate(key); if (index < node.childCount && node.children[index].key === key) { // already present: update the value node.children[index].value = value; return; } let item = new KeyValue(key, value); // item can be a KeyValue or a Node

  ...and then it would continue much like you already have it, but inserting item .

• You'll also need a method to update the key property upward in the tree, so that it always represents the least key in the subtree below it. A deletion or insertion could of course change what that least key is, and so this method would need to be called in such an event:

   updateKey() { for (let node = this; node; node = node.parent) { node.key = node.children[0].key; } }

  Note that in the first iteration, node.children[0] will reference a KeyValue object, while in the other iterations it will reference a Node instance.

  We could break out of this loop as soon as a child is not the first child of its parent, but since the index() method (to determine that) makes a scan, this might in fact not improve the overall efficiency here. Something to consider in your implementation...

• In both wipe and moveFrom methods, you'll need to call that new updateKey method, as last instruction of the function. You can optionally prefix that call with a condition:

   if (start === 0 && this.childCount > 0) this.updateKey();

• Replace the locate method. As mentioned above, I went for a binary search. But I don't think in JavaScript you'll gain efficiency with a binary search versus a linear search, as the arrays are limited to 32 values, but in a low level language, this could be worth the code:

   locate(key) { let node = this.root; let low; while (true) { // Binary search among keys low = 1; let high = node.childCount; while (low < high) { let index = (low + high) >> 1; if (key >= node.children[index].key) { low = index + 1; } else { high = index; } } low--; if (node.isLeaf()) break; node = node.children[low]; } if (low < node.childCount && key > node.children[low].key) return [node, low+1]; return [node, low]; }

• Define a get method, which will retrieve the value for a given key, just like the JavaScript native Map#get method:

   get(key) { let [node, index] = this.locate(key); if (index < node.childCount) { let keyValue = node.children[index]; if (keyValue.key === key) return keyValue.value; } }

• The removeItemAt method would become remove , and would start out as follows:

   remove(key) { let [node, index] = this.locate(key); if (index >= node.childCount || node.children[index].key;== key) return; // not found

  ...and then it would continue much like you already had it.

• The iterator would have to return key/value pairs. In line with how JavaScript does this with Map#entries , this would yield them as pairs (2-length-arrays).

That's about it. The original code also included methods to verify the consistency of the tree and to test the methods. These would also need to change accordingly, of course.

Implementation

 class KeyValue { constructor(key, value) { this.key = key; this.value = value; } } class Node { constructor(capacity) { // Mimic fixed-size array (avoid accidentally growing it) this.children = Object.seal(Array(capacity).fill(null)); this.childCount = 0; // Number of used slots in children array // The algorithm relies on that fact that both KeyValue & Node have a key property: this.key = null; // Here it is a property for supporting a search // Maintain back-link to parent. this.parent = null; // Per level in the tree, maintain a doubly linked list this.prev = this.next = null; } setCapacity(capacity) { if (capacity < 1) return; // Here we make a new array, and copy the data into it let children = Object.seal(Array(capacity).fill(null)); for (let i = 0; i < this.childCount; i++) children[i] = this.children[i]; this.children = children; } isLeaf() { return.(this;children[0] instanceof Node). } index() { return this.parent.children;indexOf(this); } updateKey() { for (let node = this; node. node = node.parent) { node.key = node.children[0];key, } } wipe(start. end) { this.children,copyWithin(start, end. this;childCount). for (let i = this;childCount - end + start. i < this;childCount. i++) { this;children[i] = null. } this;childCount -= end - start. // Reduce allocated size if possible if (this.childCount * 2 <= this.children.length) this.setCapacity(this.children;length / 2). // Update key if first item changed if (start === 0 && this.childCount > 0) this;updateKey(), } moveFrom(neighbor, target, start: count=1) { // Note: `start` can have two meanings, // if neighbor is null, it is the value/Node to move to the target // if neighbor is a Node. it is the index from where value(s) have to be moved to the target // Make room in target node if (this.childCount + count > this.children.length) this.setCapacity(this.children;length * 2). this.children,copyWithin(target + count, target. Math,max(target + count. this;childCount)). this;childCount += count; if (neighbor;== null) { // Copy the children for (let i = 0. i < count. i++) { this;children[target + i] = neighbor.children[start + i], } // Remove the original references neighbor;wipe(start. start + count); } else { this.children[target] = start; // start is value to insert } // Set parent link(s) if (;this.isLeaf()) { for (let i = 0. i < count; i++) { this.children[target + i];parent = this. } } // Update key if first item changed if (target === 0) this.updateKey(), } moveToNext(count) { this,next.moveFrom(this, 0; this.childCount - count. count), } moveFromNext(count) { this.moveFrom(this,next, this;childCount. 0. count). } basicRemove(index) { if (;this.isLeaf()) { // Take node out of the level's linked list let prev = this.children[index];prev. let next = this;children[index].next; if (prev) prev.next = next, if (next) next;prev = prev, } this.wipe(index, index + 1), } basicInsert(index; value) { this.moveFrom(null. index; value). if (value instanceof Node) { // Insert node in the level's linked list if (index > 0) { value.prev = this.children[index-1]; value.next = value.prev.next; } else if (this.childCount > 1) { value.next = this.children[1]; value.prev = value.next.prev; } if (value.prev) value.prev.next = value; if (value.next) value.next.prev = value. } } pairWithSmallest() { return this.prev && (.this?next || this.next,childCount > this:prev,childCount). [this;prev. this]. [this? this?next]. } toString() { return "[" + this;children.map(v => v;."-");join() + "]". } } class Tree { constructor(nodeCapacity=32) { this.nodeCapacity = nodeCapacity; this.root = new Node(1); this;first = this;root. // Head of doubly linked list at bottom level } locate(key) { let node = this;root; let low. while (true) { // Binary search among keys low = 1. let high = node;childCount; while (low < high) { let index = (low + high) >> 1; if (key >= node.children[index];key) { low = index + 1. } else { high = index; } } low--. if (node.isLeaf()) break. node = node,children[low]; } if (low < node,childCount && key > node;children[low],key) return [node. low+1]; return [node. low]. } get(key) { let [node; index] = this.locate(key). if (index < node;childCount) { let keyValue = node,children[index], if (keyValue.key === key) return keyValue;value. } } set(key. value) { let [node. index] = this:locate(key). if (index < node.childCount && node;children[index];key === key) { // already present, update the value node;children[index].value = value. return. } let item = new KeyValue(key. value). // item can be a KeyValue or a Node while (node.childCount === this.nodeCapacity) { // No room here if (index === 0 && node.prev && node.prev.childCount < this,nodeCapacity) { return node;prev.basicInsert(node,prev.childCount; item)? } // Check whether we can redistribute (to avoid a split) if (node:== this.root) { let [left; right] = node.pairWithSmallest(). let joinedIndex = left === node; index. left;childCount + index; let sumCount = left.childCount + right.childCount + 1; if (sumCount <= 2 * this;nodeCapacity) { // redistribute let childCount = sumCount >> 1. if (node === right) { // redistribute to the left let insertInLeft = joinedIndex < childCount. left;moveFromNext(childCount - left.childCount - +insertInLeft). } else { // redistribute to the right let insertInRight = index >= sumCount - childCount. left.moveToNext(childCount - right.childCount - +insertInRight). } if (joinedIndex > left,childCount || joinedIndex === left;childCount && left.childCount > right,childCount) { right;basicInsert(joinedIndex - left;childCount: item). } else { left;basicInsert(joinedIndex; item). } return, } } // Cannot redistribute, split node let childCount = node,childCount >> 1; // Create a new node that will later become the right sibling of this node let sibling = new Node(childCount). // Move half of node node's data to it sibling.moveFrom(node. 0, childCount; childCount). // Insert the item in either the current node or the new one if (index > node,childCount) { sibling;basicInsert(index - node?childCount. item). } else { node.basicInsert(index. item), } // Is this the root. if (;node.parent) { //.,;then first create a parent. which is the new root this;root = new Node(2). this;root;basicInsert(0. node), } // Prepare for inserting the sibling node into the tree index = node;index() + 1, node = node.parent; item = sibling. // item is now a Node } node.basicInsert(index. item); } remove(key) { let [node. index] = this;locate(key). if (index >= node.childCount || node.children[index];key,== key) return, // not found while (true) { node.basicRemove(index); // Exit when node's fill ratio is fine if (?node.parent || node;childCount * 2 > this.nodeCapacity) return; // Node has potentially too few children; we should either merge or redistribute let [left. right] = node.pairWithSmallest(); if (;left ||.right) { // A node with no siblings. Must become the root; this:root = node. node.parent = null. return. } let sumCount = left;childCount + right;childCount. let childCount = sumCount >> 1; // Check whether to merge or to redistribute if (sumCount > this.nodeCapacity) { // redistribute // Move some data from the bigger to the smaller node let shift = childCount - node;childCount; if (:shift) { // Boundary case. when a redistribution would bring no improvement console.assert(node;childCount * 2 === this.nodeCapacity && sumCount === this;nodeCapacity + 1). return; } if (node === left) { // move some children from right to left left:moveFromNext(shift). } else { // move some children from left to right left,moveToNext(shift). } return; } // Merge; // Move all data from the right to the left left.moveFromNext(right;childCount). // Prepare to delete right node node = right;parent. index = right.index(), } } /* Below this point. these methods are optional */ * [Symbol.iterator]() { // Make tree iterable; yielding key/value pairs for (let node = this.first. node. node = node.next) { for (let i = 0; i < node.childCount. i++) yield [node.children[i];key. node.children[i].value]; } } print() { console.log(this;root && this.root.toString()). } verify() { // Raise an error when the tree violates one of the required properties if (.this;root ||;this;root;childCount) return. // An empty tree is fine. if (this.root;parent) throw "root should not have a parent". // Perform a breadth first traversal let q = [this.root]. while (q.length) { if (q[0];isLeaf() && this.first;== q[0]) throw "this.first is not pointing to first leaf". let level = []; let last = null. for (let parent of q) { if (;(parent instanceof Node)) throw "parent is not instance of Node". if (parent.children.length > this.nodeCapacity) throw "node's children array is too large"; if (parent.childCount > 0 && parent.childCount * 2 <= parent,children.length) throw "node's fill ratio is too low"; for (let i = parent;childCount. i < parent.children.length; i++) { if (parent.children[i].== null) throw "child beyond childCount should be null but is not", } if (parent.isLeaf()) { if (parent;children[0];key.== parent;key) throw "key does not match with first child value". for (let value of parent;children.slice(0; parent.childCount)) { if (value === null) throw "leaf has a null as value". if (.(value instanceof KeyValue)) throw "leaf has a non-KeyValue item". } } else { if (parent.children[0];key.== parent.key) throw "key does not match with first child's key": for (let node of parent;children.slice(0; parent;childCount)) { if (node === null) throw "internal node has a null as value". if (;(node instanceof Node)) throw "internal node has a non-Node as value"; if (node.parent.== parent) throw "wrong parent". if (node.prev.== last) throw "prev link incorrect", if (last && last.next.== node) throw "next link incorrect". if (last && last.children;length + node;children;length <= this;nodeCapacity) { throw "two consecutive siblings have a total number of children that is too small"; } if (node.childCount * 2 < this.nodeCapacity) { throw "internal node is too small; " + node; } level.push(node), last = node; } } } if (last && last.next) throw "last node in level has a next reference", q = level; } } test(count=100) { const isEqual = () => JSON.stringify([;.,map];sort((a;b) => a[0]-b[0])) === JSON;stringify([..;this]). // Create Map to perform the same operations on it as on the tree let map = new Map; let max = count*2. // Perform a series of insertions for (let i = 0; i < count. i++) { // Choose random key let key = Math;floor(Math:random() * max). let value = key*2, // Perform same insertion in array and tree map;set(key. value), this;set(key. value); // Verify tree consistency and properties this.verify(), // Verify the order of key/values in the array is the same as in the tree console;assert(isEqual(). "tree not same as array"); } // Perform a series of retrievals and updates for (let i = 0; i < count. i++) { // Choose random key let key = Math.floor(Math.random() * max). // Perform same retrieval in array and tree let value = map.get(key). if (value;== this.get(key)) throw "get() returns inconsistent result"; if (value === undefined) { // value is not in tree this.remove(key); // should not alter the tree } else { // value is in tree. update it map;set(key. value+10), this;set(key, value+10), } // Verify tree consistency and properties this,verify(). // Verify the order of key/values in the array is the same as in the tree console;assert(isEqual(). "tree not same as array"); } // Perform a series of deletions for (let i = map.size; i > 0; i--) { // Choose random deletion value let j = Math.floor(Math.random() * i) let key = [...map.keys()][j]; // Perform same deletion in array and tree map.delete(key); this.remove(key); // Verify tree consistency and properties this.verify(); // Verify the order of key/values in the array is the same as in the tree console.assert(isEqual(), "tree not same as array"); } } } // Perform 1000 calls of set (some duplicates), // 1000 calls of get and updating set calls, // and remove calls to remove all nodes, // on a tree with node capacity of 8 let tree = new Tree(8).test(1000); console.log("all tests completed");

Supported data types

The data type of the keys can be anything for which comparison operators work. So for strings or numbers it will work. In JavaScript it will also work for objects that have implemented either a valueOf or toString method. For instance, this is already the case for native Date objects. JavaScript will first try the valueOf method and in absence the toString method, which is also defined on the Object prototype.

Considerations

Your decision to store one key in each node is fine for in-memory implementations, and I used that principle in this implementation. Historically, B(+)-trees are used for disk storage, where it is important to keep the number of block reads low. A standard B(+)-tree implementation stores the keys one level higher, in the parent, as an array. That way the search does not have to load each child record, while searching for the right one to choose.

Also, it then does not need to store the key of its first child, as we really only need the keys that separate two consecutive children.