这是上面的一个修改版本，适用于多个根项，我使用guid为我的id和parentid，所以在创建它们的UI中，我硬编码根项为0000000-00000-00000-TREE-ROOT-ITEM

var树= unflatten(记录，" tree - root - item ");

function unflatten(records, rootCategoryId, parent, tree){
    if(!_.isArray(tree)){
        tree = [];
        _.each(records, function(rec){
            if(rec.parentId.indexOf(rootCategoryId)>=0){        // change this line to compare a root id
            //if(rec.parentId == 0 || rec.parentId == null){    // example for 0 or null
                var tmp = angular.copy(rec);
                tmp.children = _.filter(records, function(r){
                    return r.parentId == tmp.id;
                });
                tree.push(tmp);
                //console.log(tree);
                _.each(tmp.children, function(child){
                    return unflatten(records, rootCategoryId, child, tree);
                });
            }
        });
    }
    else{
        if(parent){
            parent.children = _.filter(records, function(r){
                return r.parentId == parent.id;
            });
            _.each(parent.children, function(child){
                return unflatten(records, rootCategoryId, child, tree);
            });
        }
    }
    return tree;
}

你可以使用npm包数组到树https://github.com/alferov/array-to-tree。 它将普通的节点数组(带有指向父节点的指针)转换为嵌套的数据结构。

解决了从数据库数据集检索到嵌套数据结构(即导航树)的转换问题。

用法:

var arrayToTree = require('array-to-tree');

var dataOne = [
  {
    id: 1,
    name: 'Portfolio',
    parent_id: undefined
  },
  {
    id: 2,
    name: 'Web Development',
    parent_id: 1
  },
  {
    id: 3,
    name: 'Recent Works',
    parent_id: 2
  },
  {
    id: 4,
    name: 'About Me',
    parent_id: undefined
  }
];

arrayToTree(dataOne);

/*
 * Output:
 *
 * Portfolio
 *   Web Development
 *     Recent Works
 * About Me
 */

你可以使用这个来自Github或NPM的“treeify”包。

安装:

$ NPM install——save-dev treeify-js

下面是我根据上面的答案创建的一个简单的帮助函数，为通天塔环境量身定制:

import { isEmpty } from 'lodash'

export default function unflattenEntities(entities, parent = {id: null}, tree = []) {

  let children = entities.filter( entity => entity.parent_id == parent.id)

  if (!isEmpty( children )) {
    if ( parent.id == null ) {
      tree = children
    } else {
      parent['children'] = children
    }
    children.map( child => unflattenEntities( entities, child ) )
  }

  return tree

}

这是一个旧线程，但我认为更新永远不会伤害，与ES6你可以做到:

const data = [{ id: 1, parent_id: 0 }, { id: 2, parent_id: 1 }, { id: 3, parent_id: 1 }, { id: 4, parent_id: 2 }, { id: 5, parent_id: 4 }, { id: 8, parent_id: 7 }, { id: 9, parent_id: 8 }, { id: 10, parent_id: 9 }]; const arrayToTree = (items=[], id = null, link = 'parent_id') => items.filter(item => id==null ? !items.some(ele=>ele.id===item[link]) : item[link] === id ).map(item => ({ ...item, children: arrayToTree(items, item.id) })) const temp1=arrayToTree(data) console.log(temp1) const treeToArray = (items=[], key = 'children') => items.reduce((acc, curr) => [...acc, ...treeToArray(curr[key])].map(({ [`${key}`]: child, ...ele }) => ele), items); const temp2=treeToArray(temp1) console.log(temp2)

希望它能帮助到别人

如果使用地图查找，就有一个有效的解决方案。如果父母总是在他们的孩子之前，你可以合并两个for循环。它支持多个根。它在悬垂的分支上给出一个错误，但可以修改为忽略它们。它不需要第三方库。就我所知，这是最快的解决方法。

function list_to_tree(list) { var map = {}, node, roots = [], i; for (i = 0; i < list.length; i += 1) { map[list[i].id] = i; // initialize the map list[i].children = []; // initialize the children } for (i = 0; i < list.length; i += 1) { node = list[i]; if (node.parentId !== "0") { // if you have dangling branches check that map[node.parentId] exists list[map[node.parentId]].children.push(node); } else { roots.push(node); } } return roots; } var entries = [{ "id": "12", "parentId": "0", "text": "Man", "level": "1", "children": null }, { "id": "6", "parentId": "12", "text": "Boy", "level": "2", "children": null }, { "id": "7", "parentId": "12", "text": "Other", "level": "2", "children": null }, { "id": "9", "parentId": "0", "text": "Woman", "level": "1", "children": null }, { "id": "11", "parentId": "9", "text": "Girl", "level": "2", "children": null } ]; console.log(list_to_tree(entries));

如果你喜欢复杂性理论，这个解决方案是Θ(n log(n))。递归过滤器的解决方案是Θ(n^2)，这对于大型数据集可能是一个问题。