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DSA in JavaScript
Advanced Data Structures

Segment Tree

Data Structure · Stretch

Level: StretchPrefix Sum

Step through it: Prefix Sum pattern

numbers

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Question: what is 1 + 4 + 2? Adding three numbers is easy. But if someone asks 1,000 range questions, you re-add the same numbers again and again.

In computer science, a segment tree also known as a statistic tree is a tree data structure used for storing information about intervals, or segments. It allows querying which of the stored segments contain a given point. It is, in principle, a static structure; that is, it's a structure that cannot be modified once it's built. A similar data structure is the interval tree.

A segment tree is a binary tree. The root of the tree represents the whole array. The two children of the root represent the first and second halves of the array. Similarly, the children of each node corresponds to the two halves of the array corresponding to the node.

We build the tree bottom up, with the value of each node being the "minimum" (or any other function) of its children's values. This will take O(n log n) time. The number of operations done is the height of the tree, which is O(log n). To do range queries, each node splits the query into two parts, one sub-query for each child. If a query contains the whole subarray of a node, we can use the precomputed value at the node. Using this optimisation, we can prove that only O(log n) minimum operations are done.

Application

A segment tree is a data structure designed to perform certain array operations efficiently - especially those involving range queries.

Applications of the segment tree are in the areas of computational geometry, and geographic information systems.

Current implementation of Segment Tree implies that you may pass any binary (with two input params) function to it and thus you're able to do range query for variety of functions. In tests you may find examples of doing min, max and sum range queries on SegmentTree.

Code

SegmentTree.js
import isPowerOfTwo from '../../../algorithms/math/is-power-of-two/isPowerOfTwo';

export default class SegmentTree {
  /**
   * @param {number[]} inputArray
   * @param {function} operation - binary function (i.e. sum, min)
   * @param {number} operationFallback - operation fallback value (i.e. 0 for sum, Infinity for min)
   */
  constructor(inputArray, operation, operationFallback) {
    this.inputArray = inputArray;
    this.operation = operation;
    this.operationFallback = operationFallback;

    // Init array representation of segment tree.
    this.segmentTree = this.initSegmentTree(this.inputArray);

    this.buildSegmentTree();
  }

  /**
   * @param {number[]} inputArray
   * @return {number[]}
   */
  initSegmentTree(inputArray) {
    let segmentTreeArrayLength;
    const inputArrayLength = inputArray.length;

    if (isPowerOfTwo(inputArrayLength)) {
      // If original array length is a power of two.
      segmentTreeArrayLength = (2 * inputArrayLength) - 1;
    } else {
      // If original array length is not a power of two then we need to find
      // next number that is a power of two and use it to calculate
      // tree array size. This is happens because we need to fill empty children
      // in perfect binary tree with nulls.And those nulls need extra space.
      const currentPower = Math.floor(Math.log2(inputArrayLength));
      const nextPower = currentPower + 1;
      const nextPowerOfTwoNumber = 2 ** nextPower;
      segmentTreeArrayLength = (2 * nextPowerOfTwoNumber) - 1;
    }

    return new Array(segmentTreeArrayLength).fill(null);
  }

  /**
   * Build segment tree.
   */
  buildSegmentTree() {
    const leftIndex = 0;
    const rightIndex = this.inputArray.length - 1;
    const position = 0;
    this.buildTreeRecursively(leftIndex, rightIndex, position);
  }

  /**
   * Build segment tree recursively.
   *
   * @param {number} leftInputIndex
   * @param {number} rightInputIndex
   * @param {number} position
   */
  buildTreeRecursively(leftInputIndex, rightInputIndex, position) {
    // If low input index and high input index are equal that would mean
    // the we have finished splitting and we are already came to the leaf
    // of the segment tree. We need to copy this leaf value from input
    // array to segment tree.
    if (leftInputIndex === rightInputIndex) {
      this.segmentTree[position] = this.inputArray[leftInputIndex];
      return;
    }

    // Split input array on two halves and process them recursively.
    const middleIndex = Math.floor((leftInputIndex + rightInputIndex) / 2);
    // Process left half of the input array.
    this.buildTreeRecursively(leftInputIndex, middleIndex, this.getLeftChildIndex(position));
    // Process right half of the input array.
    this.buildTreeRecursively(middleIndex + 1, rightInputIndex, this.getRightChildIndex(position));

    // Once every tree leaf is not empty we're able to build tree bottom up using
    // provided operation function.
    this.segmentTree[position] = this.operation(
      this.segmentTree[this.getLeftChildIndex(position)],
      this.segmentTree[this.getRightChildIndex(position)],
    );
  }

  /**
   * Do range query on segment tree in context of this.operation function.
   *
   * @param {number} queryLeftIndex
   * @param {number} queryRightIndex
   * @return {number}
   */
  rangeQuery(queryLeftIndex, queryRightIndex) {
    const leftIndex = 0;
    const rightIndex = this.inputArray.length - 1;
    const position = 0;

    return this.rangeQueryRecursive(
      queryLeftIndex,
      queryRightIndex,
      leftIndex,
      rightIndex,
      position,
    );
  }

  /**
   * Do range query on segment tree recursively in context of this.operation function.
   *
   * @param {number} queryLeftIndex - left index of the query
   * @param {number} queryRightIndex - right index of the query
   * @param {number} leftIndex - left index of input array segment
   * @param {number} rightIndex - right index of input array segment
   * @param {number} position - root position in binary tree
   * @return {number}
   */
  rangeQueryRecursive(queryLeftIndex, queryRightIndex, leftIndex, rightIndex, position) {
    if (queryLeftIndex <= leftIndex && queryRightIndex >= rightIndex) {
      // Total overlap.
      return this.segmentTree[position];
    }

    if (queryLeftIndex > rightIndex || queryRightIndex < leftIndex) {
      // No overlap.
      return this.operationFallback;
    }

    // Partial overlap.
    const middleIndex = Math.floor((leftIndex + rightIndex) / 2);

    const leftOperationResult = this.rangeQueryRecursive(
      queryLeftIndex,
      queryRightIndex,
      leftIndex,
      middleIndex,
      this.getLeftChildIndex(position),
    );

    const rightOperationResult = this.rangeQueryRecursive(
      queryLeftIndex,
      queryRightIndex,
      middleIndex + 1,
      rightIndex,
      this.getRightChildIndex(position),
    );

    return this.operation(leftOperationResult, rightOperationResult);
  }

  /**
   * Left child index.
   * @param {number} parentIndex
   * @return {number}
   */
  getLeftChildIndex(parentIndex) {
    return (2 * parentIndex) + 1;
  }

  /**
   * Right child index.
   * @param {number} parentIndex
   * @return {number}
   */
  getRightChildIndex(parentIndex) {
    return (2 * parentIndex) + 2;
  }
}

References

Practice

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