JS数据结构描述之广度遍历和深度遍历

文章来源：http://www.html-js.com/articl...

简单的遍历一个树形结构数据的几种方法、非递归方法效率最好。

一：数据模型:

(function (window, undefined) {
    var treeNodes = [
       {
            id: 1,
            name: '1',
            children: [
                 {
                      id: 11,
                      name: '11',
                      children: [
                           {
                                id: 111,
                                name: '111',
                                children:[]
                           },
                           {
                                id: 112,
                                name: '112'
                           }
                      ]
                 },
                 {
                      id: 12,
                      name: '12',
                      children: []
                 }
            ],
            users: []
       },
       {
            id: 2,
            name: '2',
            children: [
                {
                    id: 22,
                    name: '22',
                    children: []
                }
            ]
       }
    ];

二：递归实现

    var parseTreeJson = function(treeNodes){
      if (!treeNodes || !treeNodes.length) return;

       for (var i = 0, len = treeNodes.length; i < len; i++) {

            var childs = treeNodes[i].children;

            console.log(treeNodes[i].id);

            if(childs && childs.length > 0){
                 parseTreeJson(childs);
            }
       }
    };

    console.log('------------- 递归实现 ------------------');
    parseTreeJson(treeNodes);

三：非递归广度优先实现

var iterator1 = function (treeNodes) {
    if (!treeNodes || !treeNodes.length) return;

    var stack = [];

    //先将第一层节点放入栈
    for (var i = 0, len = treeNodes.length; i < len; i++) {
        stack.push(treeNodes[i]);
    }

    var item;

    while (stack.length) {
        item = stack.shift();

        console.log(item.id);

        //如果该节点有子节点，继续添加进入栈底
        if (item.children && item.children.length) {
            //len = item.children.length;

            // for (i = 0; i < len; i++) {
            //  stack.push(item.children[i]);
            // }

            stack = stack.concat(item.children);
        }
    }
};

console.log('------------- 非递归广度优先实现 ------------------');
iterator1(treeNodes);

四：非递归深度优先实现

 var iterator2 = function (treeNodes) {
        if (!treeNodes || !treeNodes.length) return;

        var stack = [];

        //先将第一层节点放入栈
        for (var i = 0, len = treeNodes.length; i < len; i++) {
            stack.push(treeNodes[i]);
        }

        var item;

        while (stack.length) {
            item = stack.shift();

            console.log(item.id);

            //如果该节点有子节点，继续添加进入栈顶
            if (item.children && item.children.length) {
                // len = item.children.length;

                // for (; len; len--) {
                //  stack.unshift(item.children[len - 1]);
                // }
                stack = item.children.concat(stack);
            }
        }
    };

    console.log('------------- 非递归深度优先实现 ------------------');
    iterator2(treeNodes);
})(window);