1.名词解释：达梦数据库中的HJ_BUF_GLOBAL_SIZE是所有哈希连接操作可用的最大哈希缓冲区大小，单位为兆字节（MB）

2.达梦压测报错：

3.找到达梦数据库安装文件

4.压力测试脚本
 

import http.client
import multiprocessing
import time
from urllib.parse import urlparse
import json  # 新增json模块用于解析响应内容


def send_request(url):
    try:
        parsed_url = urlparse(url)
        if parsed_url.scheme == 'http':
            conn = http.client.HTTPConnection(parsed_url.netloc)
        else:
            conn = http.client.HTTPSConnection(parsed_url.netloc)
        conn.request("GET", parsed_url.path)
        response = conn.getresponse()
        # 读取完整响应内容
        response_body = response.read().decode('utf-8')
        status_code = response.status
        conn.close()

        # 尝试解析JSON（针对接口返回的JSON格式）
        try:
            response_data = json.loads(response_body)
            actual_code = response_data.get('code', status_code)  # 优先使用业务code
            return actual_code == 200  # 只有code=200才算真正成功
        except json.JSONDecodeError:
            return status_code == 200  # 非JSON响应则 fallback 到HTTP状态码
    except Exception as e:
        print(f"请求出错: {e}")
        return False


def stress_test(url, num_requests):
    results = []
    for _ in range(num_requests):
        start_time = time.time()
        is_success = send_request(url)  # 现在返回布尔值
        end_time = time.time()
        elapsed_time = end_time - start_time
        results.append((is_success, elapsed_time))
    return results


def run_single_stress_test(url, num_requests_per_process, all_results):
    results = stress_test(url, num_requests_per_process)
    all_results.extend(results)


def run_stress_test(url, num_processes, num_requests_per_process):
    processes = []
    manager = multiprocessing.Manager()
    all_results = manager.list()

    for _ in range(num_processes):
        p = multiprocessing.Process(target=run_single_stress_test,
                                    args=(url, num_requests_per_process, all_results))
        processes.append(p)
        p.start()

    for p in processes:
        p.join()

    return all_results


if __name__ == "__main__":
    target_url = 'http://127.0.0.1:8088/api/aaaa/project/deptList'
    num_processes = 500
    num_requests_per_process = 5

    try:
        print("开始压力测试...")
        results = run_stress_test(target_url, num_processes, num_requests_per_process)

        # 结果分析（现在基于布尔值判断）
        total_requests = len(results)
        successful_requests = sum(1 for success, _ in results if success)
        success_rate = (successful_requests / total_requests) * 100
        total_time = sum(elapsed for _, elapsed in results)

        print("\n===== 测试结果 =====")
        print(f"总请求数: {total_requests}")
        print(f"成功请求数: {successful_requests}")
        print(f"成功率: {success_rate:.2f}%")
        print(f"总耗时: {total_time:.2f} 秒")
        print(f"平均响应时间: {total_time / total_requests:.2f} 秒")

        # 输出详细错误信息（如果有失败请求）
        if successful_requests < total_requests:
            failed = total_requests - successful_requests
            print(f"\n警告: 有 {failed} 次请求未返回code=200！")

    except Exception as e:
        print(f"发生致命错误: {e}")