中文版提示词
请扮演资深性能优化工程师，帮助我分析并优化一段在处理大数据量时耗时过长的代码。我将提供以下信息：

  • 数据规模：[描述数据量，如“10万条记录”]

  • 当前耗时：[描述当前执行时间，如“约 X 秒”]

  • 相关代码：[粘贴代码块，需注明编程语言]

请完成以下任务：

  1. 从时间复杂度和空间复杂度两个维度分析性能瓶颈，指出最耗时的操作。

  2. 使用更高效的数据结构（如将 List 替换为 Set/Map）或减少循环嵌套层级来重构代码，确保输入输出接口保持不变。

  3. 输出优化后的关键代码片段，并对比说明优化前后在复杂度与实测性能上的差异。

直接输出分析、优化代码及性能对比说明，无需其他内容。

英文版提示词（English Version Prompt）
Please act as a senior performance optimization engineer to help me analyze and refactor a piece of code that runs too slowly when processing large‑scale data. I will provide:

  • Data scale: [describe the data volume, e.g., “100,000 records”]

  • Current execution time: [describe the current runtime, e.g., “around X seconds”]

  • Relevant code: [paste the code block, specifying the programming language]

Please complete the following:

  1. Analyze the performance bottleneck from both time complexity and space complexity perspectives, identifying the most expensive operations.

  2. Refactor the code using more efficient data structures (e.g., replace List with Set/Map) or reduce nested loop levels, while keeping the input/output interface unchanged.

  3. Output the optimized key code snippets, and provide a comparison of complexity and measured performance before and after optimization.

Provide directly the analysis, optimized code, and performance comparison, without any other content.