Practical sharing of database search optimization cases driven by Java technology

Practical sharing of database search optimization cases driven by Java technology

Abstract: This article will introduce how to use Java technology to optimize database search operations. We will share a practical case to explain in detail the specific optimization process and code implementation.

Keywords: Java technology, database search, optimization, actual combat

1. Introduction

Database search is one of the common and important functions in applications. As the amount of data increases and access requirements increase, how to perform database searches quickly and efficiently becomes a challenge. This article will share a practical case using Java technology to optimize database search operations and provide specific code examples.

2. Problem Analysis

In our case, we have an order management system that contains order information and product information tables. Users can search order information by keywords and sort by different fields. The original search implementation uses the LIKE operator of the SQL statement for fuzzy matching, but as the amount of data increases, the search speed gradually slows down.

3. Optimization plan

In order to improve the performance of database search, we have used the following optimization plan.

1. Using full-text index

Full-text index is a special type of index that can speed up the search of text content. We created a full-text index on the key fields of the order information table, such as order number, customer name, etc. This way, when searching, the database engine uses the full-text index to speed up the query, rather than scanning the data item by item.

2. Using parameterized queries

The original search implementation used string splicing to construct SQL query statements, resulting in the SQL statement being recompiled for each search, which increased The cost of the query. In order to reduce query overhead, we use parameterized queries. By using precompiled SQL statements and parameters, the database query plan generation process can be reduced and query performance improved.

3. Paging query

For search results of large amounts of data, we use paging query to optimize. Users can display the results in pages by setting the number of records and page numbers displayed on each page. By limiting the number of records returned per page, you can reduce database query and network transmission pressure.

4. Result Caching

In order to further improve the search speed, we use result caching. Each time a search is performed, we first check the cache to see if there are identical search results. If it exists in the cache, the result will be obtained directly from the cache, avoiding queries to the database. If it is not in the cache, a database query is made and the results are stored in the cache. This can significantly reduce the number of accesses to the database and increase search speed.

4. Code Example

The following is a code example of the optimized search we implemented in Java.

public class OrderSearch {

    // 全文索引字段名
    private static final String[] INDEX_FIELDS = {"orderNo", "customerName"};

    // 搜索结果缓存
    private static Map<String, List<Order>> cache = new HashMap<>();

    public List<Order> search(String keyword, String sortBy, int pageSize, int pageNum) {
        String cacheKey = generateCacheKey(keyword, sortBy, pageSize, pageNum);
        if (cache.containsKey(cacheKey)) {
            return cache.get(cacheKey);
        }

        List<Order> orders = new ArrayList<>();

        // 构建SQL查询语句
        String sql = "SELECT * FROM order_info WHERE ";
        for (String field : INDEX_FIELDS) {
            sql += field + " LIKE '%" + keyword + "%' OR ";
        }
        sql = sql.substring(0, sql.lastIndexOf(" OR "));

        // 添加排序条件
        sql += "ORDER BY " + sortBy;

        // 添加分页条件
        int offset = (pageNum - 1) * pageSize;
        sql += " LIMIT " + offset + ", " + pageSize;

        // 执行SQL查询...
        // 将查询结果转为Order对象，并添加到orders列表中...

        // 将结果存入缓存
        cache.put(cacheKey, orders);

        return orders;
    }

    private String generateCacheKey(String keyword, String sortBy, int pageSize, int pageNum) {
        return keyword + "_" + sortBy + "_" + pageSize + "_" + pageNum;
    }
}

In the above code, we use full-text indexing, parameterized query, paging query and result caching technology to optimize database search operations. Through these optimization measures, we successfully improved search performance.

5. Summary

Through the case sharing in this article, we have learned how to use Java technology to optimize database search operations. Full-text indexing, parameterized queries, paging queries and result caching are all effective optimization methods. In actual development, we can choose appropriate optimization solutions based on specific needs and scenarios.

Although this article provides specific code examples, the actual optimization process may need to be adjusted based on specific environments and needs. Therefore, developers need to carefully consider and evaluate when using the optimization techniques mentioned in this article to ensure actual results.

Note: The above code is a simplified example and may not include complete exception handling and resource release codes. Please improve it during actual use.

Reference:

• Oracle. (2021). Oracle Database Advanced Application Developer's Guide. Retrieved from https://docs.oracle.com/en/database/oracle/oracle -database/19/adfns/overview.html

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