When using the `split` filter to process a large amount of data, are there any recommended practices to optimize performance?

Manage website content in Anqi CMS, splitFilter is undoubtedly a very practical tool, which can help us easily split strings into arrays according to specified delimiters, and then flexibly display the data. However, when the amount of data being processed is very large, or the page on thesplitWhen the filter is called very frequently, we may start to pay attention to its performance.After all, a smooth user experience and efficient server response speed are goals that any website operator seeks.

Then, in usingsplitWhat are some recommended practices to optimize performance when processing a large amount of data with a filter?

UnderstandingsplitThe principle of the filter.

First, let's briefly reviewsplitThe role of the filter. It receives a string and a delimiter, and then splits the string into an array of strings. For example,"item1,item2,item3"|split:","It will return an array containing "item1", "item2", "item3". The template engine of Anq CMS is implemented based on Go language, which meanssplitThe filter is executed on the server side, not in the user's browser. Each callsplitis a string processing operation performed on the server.

Under small data volumes and low concurrency scenarios,splitefficiency is usually not an issue. But if a page needs to handle a very long string, or there are a lot of repeatedsplitPerform an operation, even looping through each elementsplitThen, the cumulative effect of these operations may impact server performance, causing page loading to slow down.

OptimizationsplitPractice of filter performance**

1. Data preprocessing and backend optimization

This is the most fundamental and effective method. It is better to perform string splitting in the backend (Go language part) before the data is read and ready to be passed to the template, rather than letting the template engine do it with each page request.

Practical suggestions:

• Move the slicing logic forward:If your content field (such as article keywords, tags, etc.) is stored in the database in the form of a comma-separated string and needs to be displayed as a list on the front end, then in the Go language processing layer (Controller or Service layer), these strings will be split into Go'sslice(equivalent to an array), then pass it directly to the template.sliceObject passed to the template.
• Example:Suppose there is a field in the database.Tagsstored as."SEO,营销,内容管理"In the Go backend, you can handle it like this:

  
  // 假设 archive.Tags 是从数据库读取的字符串
  tagsStr := archive.Tags
  tagsSlice := strings.Split(tagsStr, ",") // 在Go后端完成切割
  // 将 tagsSlice 传递给模板
  data["ArchiveTags"] = tagsSlice
  

  In the template, you can directly iterateArchiveTagsthis array without calling it againsplitFilter:

  
  {% for tag in ArchiveTags %}
      <span>{{ tag }}</span>
  {% endfor %}
  

  Thus, the computational cost of string splitting is moved to the data preparation stage, and the processed array is directly consumed during template rendering, greatly improving efficiency.

2. Avoid redundancy.splitOperate, make good use of variable assignment

Inside the template, if a string is cut into an array and used multiple times, avoid calling it repeatedlysplit. Anqicms template engine supportssetLabels to define variables, we can use it tosplitStore the result after, for subsequent reuse.

Practical suggestions:

• UsesetLabel caching results:If in the template,splitThe result needs to be referenced multiple times, only cut once and assign the result to a variable.

  
  {# 假设 item.Keywords 是一个逗号分隔的字符串 #}
  {% set keywordsArray = item.Keywords|split:"," %}
  
  <div>
      {% for keyword in keywordsArray %}
          <span class="keyword-tag">{{ keyword }}</span>
      {% endfor %}
  </div>
  
  <p>文章的第一个关键词是：{{ keywordsArray|first }}</p>
  <p>文章的关键词总数是：{{ keywordsArray|length }}</p>
  

  By{% set keywordsArray = ... %},item.KeywordsOnly cut once, all subsequent operations on the keyword array directly used it.keywordsArrayAvoided unnecessary repeated calculations.

3. Using the cache mechanism of Anqi CMS.

AnQi CMS as an enterprise-level content management system, built-in powerful caching mechanism, including static cache. If most of the content of a page (including the content involvingsplitThe part of the operation is relatively stable and does not change frequently, so using page cache or local cache can completely avoid the performance problem of repeated calculation.

Practical suggestions:

• Enable page static cache:If the entire page content is stable, you can configure page staticization or caching strategy in the AnQi CMS backend. Once the page is generated as static HTML, subsequent visits will directly return the static file, without involving any template engine calculations, includingsplitfilter.
• Consider fragment caching (if supported):For pages with poor dynamicity but complexsplitThe logical module, if the CMS template engine supports fragment caching (for example, some template engines'{% cache %}Consider caching these modules. This way, even if the main page changes dynamically, the cached fragments do not need to be re-rendered.

4. Carefully evaluate the amount of data, simplify the input.

Sometimes, the problem is not insplitThe filter itself, but input tosplitThe string is too long, or contains too many elements, resulting in a very large array after cutting, which affects the subsequent traversal and rendering.

Practical suggestions:

• Limit the length of the content field:When editing the content model in the background, for the purpose ofsplitThe field operation, consider whether it needs to limit its maximum length or element count. For example, does the number of tags in an article really need to exceed 50?
• Only pass necessary data:In the backend code, ensure that only the data required by the template is passed. Avoid passing a long string if only a part of it is needed by the template.

Summary

Used in AnQi CMSsplitWhen filtering, the core of performance optimization for handling large amounts of data lies inBreak it down into parts, pre-process, reduce repetition, and make good use of caching.Prior in the backend (Go language level) to preprocess the data, convert the string directly into an array and pass it to the template; within the template, throughsetAvoid duplicate cuts of tags; take full advantage of the powerful caching capabilities of Anqi CMS.These practices can effectively reduce the computational burden on the server, ensuring stable and efficient performance under high traffic and large data volumes.

Frequently Asked Questions (FAQ)

Q1:splitFilters andmake_listWhat are the differences between filters?

A1: splitThe filter is used to split strings based on the separator you provide, for example{{ "apple,banana"|split:"," }}You will get["apple", "banana"]Howevermake_listThe filter splits each UTF-8 character in a string into a separate element to form an array. For example{{ "你好"|make_list }}You will get["你", "好"]When processing a string with specific delimiters,splitIs preferred; if it is necessary to process character by character,make_listit is more convenient.

Q2: I feel that the website has slowed down, it must besplita problem with the filter?

A2:not necessarily. AlthoughsplitThe filter may become a performance bottleneck when processing large amounts of data, but there are many reasons why a website slows down, such as inefficient database queries, network latency, slow loading of static resources like images, other complex template logic, insufficient server resources, and so on.Before optimization, it is recommended to perform a performance analysis to determine the real bottleneck.For example, you can use the browser's developer tools (F12) to view the time of network requests, or monitor CPU and memory usage on the server.

Q3: If my data is indeed very large and must be displayed in the template, are there any other options besides the aforementioned methods?

A3:If all backend optimizations and caching strategies have been exhausted, and the data volume is still so large as to affect server performance, you may need to reconsider the way content is displayed or the architecture design.For example, consider transferring some of the data processing and display logic to the front-end (JavaScript), dynamically loading and slicing data through AJAX requests, which can reduce the pressure on server-side rendering.But this method requires a balance of SEO impact, because search engines may not be able to crawl content loaded dynamically through JavaScript.