mysql problems

本文记录了一次在Vista 64位系统上安装MySQL 5.0数据库时遇到的服务安装失败问题。通过检查发现,使用普通用户权限进行操作会导致安装服务被拒绝。文章提供了正确的解决方案:使用管理员权限重新执行安装命令。

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今天在一台机器(OS为vista 64bit)上装MySQL5.0数据库,看了下机器,之前有安装MySQL,不过没启动服务,于是就打开cmd.exe输入mysqld --install,谁知出现Install/Remove of the Service Denied! 错误,奇怪。

 

      查了下MySQL自带手册,命令没有敲错,为什么安装服务失败呢,后来仔细一想,哦,权限不够,我用的是普通用户权限,恩,再次打开cmd.exe,不过这次要右击“Run as administrator”,恩,然后再键入mysqld --install

### LeetCode MySQL Problems and Solutions #### Problem 1: Sales Analysis III Given three tables `Product`, `Sales` with the following structure: | Column Name | Type | |-------------|----------| | product_id | int | | product_name| varchar | | Column Name | Type | |-------------|----------| | seller_id | int | | product_id | int | | buyer_id | int | | sale_date | date | | quantity | int | | price | int | The task is to find products that were only sold in a specific year. ```sql SELECT DISTINCT p.product_id, p.product_name FROM Product AS p JOIN Sales AS s ON p.product_id = s.product_id WHERE YEAR(s.sale_date) = '2018' AND p.product_id NOT IN ( SELECT product_id FROM Sales WHERE YEAR(sale_date) != '2018') ``` This query selects distinct product IDs and names from the `Product` table where sales occurred exclusively in 2018 by filtering out any products sold outside this period[^1]. #### Problem 2: Big Countries A world table contains columns like name, continent, area, population, gdp. The goal is to list all countries larger than 3 million square kilometers or having more than 25 million people. ```sql SELECT name, population, area FROM world WHERE area > 3000000 OR population > 25000000; ``` This SQL statement retrieves country information based on specified size criteria using logical operators[^2]. #### Problem 3: Duplicate Emails With a Person table containing id and email fields, identify duplicate emails within it. ```sql SELECT Email , COUNT(*) as num FROM Person GROUP BY Email HAVING COUNT(*) > 1; ``` By grouping entries according to their email addresses and applying HAVING clause, one can easily spot duplicates[^3]. --related questions-- 1. How does JOIN operation work between two tables? 2. What are common aggregate functions used alongside GROUP BY statements? 3. Can you explain how subqueries function inside main queries? 4. In what scenarios should window functions be preferred over traditional aggregation methods?
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