Efficient PHP database search: Optimizing keyword matching algorithm

Efficient PHP database search: Optimizing keyword matching algorithm, specific code examples are required

Introduction:
With the rapid development of the Internet, a large amount of data is stored in in the database. Efficiently searching these data has become one of the important issues faced by developers. This article will introduce how to improve the efficiency of PHP database search by optimizing the keyword matching algorithm, and provide specific code examples.

1. Problem Analysis
1.1 Challenges of Database Search
When performing search operations in large-scale databases, traditional linear search methods are often inefficient. When the amount of data increases, the time complexity of the search operation will also increase exponentially, resulting in a decrease in the performance of the entire system.

1.2 Keyword matching algorithm
Keyword matching algorithm is an important part of database search. Common matching algorithms include full-text search, fuzzy search, and regular expression matching. These algorithms suffer from inefficiency when processing large-scale data.

2. Optimization algorithm design
In order to improve the efficiency of PHP database search, we can improve the keyword matching process through the following optimization algorithm:

2.1 Inverted index
Inverted Indexing is a common optimization technique that can speed up keyword searches. The inverted index establishes a mapping relationship between keywords and the document location where the keywords are located to facilitate quick search. In the database, we can achieve more efficient searches by creating an inverted index.

2.2 Word segmentation technology
Word segmentation technology plays an important role in keyword matching. By splitting the search keywords, more keywords can be extracted to expand the matching scope. In PHP, you can use word segmentation extension plug-ins such as Scws to implement the word segmentation function.

2.3 Caching Mechanism
In order to reduce the frequency of database searches, a caching mechanism can be introduced to improve search efficiency. Caching search results in memory can effectively reduce I/O overhead, thereby speeding up search response.

3. Code Example
The following is a simple PHP code example for implementing keyword-based database search:

send_text($keywords); $tokens = $tokenizer->get_result(); // 初始化查询语句 $sql = "SELECT * FROM mytable WHERE "; // 构建查询条件 foreach ($tokens as $token) { $sql .= "content LIKE '%$token%' OR "; } // 去除最后一个OR $sql = substr($sql, 0, -3); // 执行查询 $query = $conn->prepare($sql); $query->execute(); $results = $query->fetchAll(PDO::FETCH_ASSOC); // 打印结果 foreach ($results as $result) { echo $result['content']; } // 关闭数据库连接 $conn = null; ?>

In the above code example, we first use the Scws word segmentation plug-in Split the search keywords and then construct the query statement. Finally, execute the query and print the results.

4. Summary
By optimizing the keyword matching algorithm, we can improve the efficiency of PHP database search. Inverted index, word segmentation technology and caching mechanism are important means to achieve optimization. By rationally utilizing these technologies, we can improve system performance and user experience when facing large-scale data searches.

References:
[1] Robert, Design and implementation of text search engine based on inverted index[J]. Chemical Automation and Instrumentation, 2019, 36(2):131-134.
[2] He Fan, Zhang Wei. Research on database keyword search algorithm[J]. Computer Frontiers and Applications, 2018(4):115-117.

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