Defer loading of JavaScript

通过延迟加载不立即使用的JavaScript函数减少初始下载大小,允许并行下载其他资源,加快页面渲染速度。解析和执行脚本会阻止浏览器渲染网页,直到处理完成。通过懒加载技术可以避免这些延迟,提高用户体验。
:lol:
Defer loading of JavaScript
Overview

Deferring loading of JavaScript functions that are not called at startup reduces the initial download size, allowing other resources to be downloaded in parallel, and speeding up execution and rendering time.
Details

Like stylesheets, scripts must be downloaded, parsed, and executed before the browser can begin to render a web page. Again, even if a script is contained in an external file that is cached, processing of all elements below the script is blocked until the browser loads the code from disk and executes it. However, for some browsers, the situation is worse than for stylesheets: while JavaScript is being processed, the browser blocks all other resources from being downloaded. For AJAX-type applications that use many bytes of JavaScript code, this can add considerable latency.

For many script-intensive applications, the bulk of the JavaScript code handles user-initiated events, such as mouse-clicking and dragging, form entry and submission, hidden elements expansion, and so on. All of these user-triggered events occur after the page is loaded and the onload event is triggered. Therefore, much of the delay in the "critical path" (the time to load the main page at startup) could be avoided by deferring the loading of the JavaScript until it's actually needed. While this "lazy" method of loading doesn't reduce the total JS payload, it can significantly reduce the number of bytes needed to load the initial state of the page, and allows the remaining bytes to be loaded asynchronously in the background.

To use this technique, you should first identify all of the JavaScript functions that are not actually used by the document before the onload event. For any file containing more than 25 uncalled functions, move all of those functions to a separate, external JS file. This may require some refactoring of your code to work around dependencies between files. (For files containing fewer than 25 uncalled functions, it's not worth the effort of refactoring.)

Tip: Use the Page Speed Profile Deferrable Javascript option to automatically identify candidates for refactoring.

Then, you insert a JavaScript event listener in the head of the containing document that forces the external file to be loaded after the onload event. You can do this by any of the usual scripting means, but we recommend a very simple scripted DOM element (to avoid cross-browser and same-domain policy issues). Here's an example (where "deferredfunctions.js" contains the functions to be lazily loaded):

<script type="text/javascript">

// Add a script element as a child of the body
function downloadJSAtOnload() {
var element = document.createElement("script");
element.src = "deferredfunctions.js";
document.body.appendChild(element);
}

// Check for browser support of event handling capability
if (window.addEventListener)
window.addEventListener("load", downloadJSAtOnload, false);
else if (window.attachEvent)
window.attachEvent("onload", downloadJSAtOnload);
else window.onload = downloadJSAtOnload;

</script>
### 关于 B+ 树批量加载的方法 #### 批量加载的概念 批量加载是指一次性将大量数据插入到 B+ 树中,而不是逐条插入。这种方法可以显著减少磁盘 I/O 操作次数,提升构建索引的速度。 #### 预分配空间 为了高效地执行批量加载操作,通常会在初始化阶段预估所需的空间并预先分配节点。这样可以在后续的数据插入过程中避免频繁调整内存布局带来的开销[^1]。 ```cpp // C++ 示例:预分配固定大小的缓冲区用于存储新创建的内部节点和叶子节点 std::vector<Node*> preAllocatedNodes; preAllocatedNodes.reserve(expectedNumberOfNodes); ``` #### 排序输入数据 由于 B+ 树是一种有序的数据结构,在进行大批量数据装载之前先对外部文件中的记录按照键值顺序排序是非常重要的一步。这有助于最小化树的高度增长以及降低分裂频率[^2]。 ```sql -- SQL 示例:对要导入 MySQL 表的数据集按主键字段升序排列后再写入临时表 INSERT INTO temp_table SELECT * FROM source_data ORDER BY primary_key_column; ``` #### 使用外部排序算法 当待处理的数据量超出可用 RAM 容限时,则需采用多趟外存归并的方式完成整个集合的初步整理工作。此过程涉及多次读取/写出硬盘上的片段直至最终获得完全排好序的结果列表为止[^3]。 #### 构建平衡子树 对于已经经过上述准备步骤得到的一组连续且已排序好的元素序列来说,可以直接从中选取中间位置的那个作为根节点;接着再分别针对左半边与右半部分重复同样的逻辑递归建立左右两棵较小规模的新子树... ```python def build_balanced_bplus_tree(sorted_items, start_index=0, end_index=None): if not isinstance(end_index, int): end_index = len(sorted_items)-1 if start_index > end_index: return None mid_point = (start_index + end_index)//2 root_node = Node(key=sorted_items[mid_point]) # Recursively construct the left and right subtrees. root_node.left_child = build_balanced_bplus_tree(sorted_items, start_index , mid_point-1 ) root_node.right_child = build_balanced_bplus_tree(sorted_items, mid_point+1, end_index) return root_node ``` 通过以上几个方面的工作,能够有效地实现 B+ 树的大规模快速加载功能,这对于诸如数据库管理系统之类的应用场景而言至关重要。
评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值