对于纯JDBC连接数据库连接工具如下: public static final String DBDRIVER=com.microsoft.sqlserver.jdbc.SQLServerDriver; public static final String DBURL=jdbc:sqlserver://10.81.35.35:1433;databaseName=Company; public static final String DBUSER
对于纯JDBC连接数据库连接工具如下:
public static final String DBDRIVER="com.microsoft.sqlserver.jdbc.SQLServerDriver"; public static final String DBURL="jdbc:sqlserver://10.81.35.35:1433;databaseName=Company"; public static final String DBUSERNAMW="sa"; public static final String DBPSD="1111111"; private Connection conn=null; public DataBaseConnection(){ try{ Class.forName(DBDRIVER); conn=DriverManager.getConnection(DBURL,DBUSERNAMW,DBPSD); }catch(Exception e){ e.printStackTrace(); } } public Connection getConnection(){ return this.conn ; } public void close() throws SQLException{ if(this.conn!=null){ conn.close(); } }
然后我们便是采用PreparedStatement对SQL语句进行预处理,如下:
PreparedStatement pstm = null; String sql = "insert into Person(UserName,Password) values(?,?)"; try { pstm = this.conn.prepareStatement(sql); pstm.setString(1, person.getUserName()); pstm.setString(2, person.getPassword()); int count = pstm.executeUpdate(); if (count > 0) { flag = true; } } catch (Exception e) { throw e; } finally { try { pstm.close(); } catch (Exception e) { } }
这是我们最常用的一种操作方式,可是问题就来了,我们所要操作的,必须对sql中的字段很明确,比如我们按条件来查询的时候,我们就必须对条件的字段很清楚,可是,当数据库字段增多的时候,我们所要查询的条件规则很多,是不是每一个条件,我们就要写一个方法呢?显然,这种是直接的思维,然而这样思维却增加了很多代码的冗余,又或者说是,每次变换条件或者新增条件的时候,我们都必须对方法进行修改,甚至是增加。于是乎,我们想有没有一种方式可以传递字段名称进去查询,如where ?=?
本人亲测,这种方式是不存在的,因为预处理字段的时候,PreparedStatement会自动在字符串上加引号,那此时就不能达到我们想要的效果(如想要的是where name=? 得到的却是 where 'name'=?),本人曾经在这样的问题上纠结了很久。最终找到一种破解的方式,这里借鉴了IBatis的Map传参方式。希望同行爱好者,我们除了要学会使用框架或插件,得找个时间去研究一下它的原理(源码)哦。
对于where ?=? 显然是不可取,但是对于字符串占位就可以的。例子如下:
public List<person> findByParams(Map<string object> params) throws Exception { Iterator it = params.entrySet().iterator(); List<person> list = new ArrayList<person>(); Person person = null; String key = null; Object value = null; PreparedStatement pstm = null; while (it.hasNext()) { Map.Entry<string object> entry = (Map.Entry<string object>) it .next(); key = entry.getKey(); value = entry.getValue(); } <span style="color:#FF0000;"> String sql = String.format( "select userid,username,password from person where %s=?", key);</span> pstm = this.conn.prepareStatement(sql); pstm.setObject(1, value); ResultSet rs = pstm.executeQuery(); while(rs.next()) { person = new Person(); person.setUserID(rs.getInt(1)); person.setUserName(rs.getString(2)); person.setPassword(rs.getString(3)); } rs.close(); pstm.close(); return list; }</string></string></person></person></string></person>
哈哈 此种方式可以替代where ?=?,参照ibatis

MySQL index cardinality has a significant impact on query performance: 1. High cardinality index can more effectively narrow the data range and improve query efficiency; 2. Low cardinality index may lead to full table scanning and reduce query performance; 3. In joint index, high cardinality sequences should be placed in front to optimize query.

The MySQL learning path includes basic knowledge, core concepts, usage examples, and optimization techniques. 1) Understand basic concepts such as tables, rows, columns, and SQL queries. 2) Learn the definition, working principles and advantages of MySQL. 3) Master basic CRUD operations and advanced usage, such as indexes and stored procedures. 4) Familiar with common error debugging and performance optimization suggestions, such as rational use of indexes and optimization queries. Through these steps, you will have a full grasp of the use and optimization of MySQL.

MySQL's real-world applications include basic database design and complex query optimization. 1) Basic usage: used to store and manage user data, such as inserting, querying, updating and deleting user information. 2) Advanced usage: Handle complex business logic, such as order and inventory management of e-commerce platforms. 3) Performance optimization: Improve performance by rationally using indexes, partition tables and query caches.

SQL commands in MySQL can be divided into categories such as DDL, DML, DQL, DCL, etc., and are used to create, modify, delete databases and tables, insert, update, delete data, and perform complex query operations. 1. Basic usage includes CREATETABLE creation table, INSERTINTO insert data, and SELECT query data. 2. Advanced usage involves JOIN for table joins, subqueries and GROUPBY for data aggregation. 3. Common errors such as syntax errors, data type mismatch and permission problems can be debugged through syntax checking, data type conversion and permission management. 4. Performance optimization suggestions include using indexes, avoiding full table scanning, optimizing JOIN operations and using transactions to ensure data consistency.

InnoDB achieves atomicity through undolog, consistency and isolation through locking mechanism and MVCC, and persistence through redolog. 1) Atomicity: Use undolog to record the original data to ensure that the transaction can be rolled back. 2) Consistency: Ensure the data consistency through row-level locking and MVCC. 3) Isolation: Supports multiple isolation levels, and REPEATABLEREAD is used by default. 4) Persistence: Use redolog to record modifications to ensure that data is saved for a long time.

MySQL's position in databases and programming is very important. It is an open source relational database management system that is widely used in various application scenarios. 1) MySQL provides efficient data storage, organization and retrieval functions, supporting Web, mobile and enterprise-level systems. 2) It uses a client-server architecture, supports multiple storage engines and index optimization. 3) Basic usages include creating tables and inserting data, and advanced usages involve multi-table JOINs and complex queries. 4) Frequently asked questions such as SQL syntax errors and performance issues can be debugged through the EXPLAIN command and slow query log. 5) Performance optimization methods include rational use of indexes, optimized query and use of caches. Best practices include using transactions and PreparedStatemen

MySQL is suitable for small and large enterprises. 1) Small businesses can use MySQL for basic data management, such as storing customer information. 2) Large enterprises can use MySQL to process massive data and complex business logic to optimize query performance and transaction processing.

InnoDB effectively prevents phantom reading through Next-KeyLocking mechanism. 1) Next-KeyLocking combines row lock and gap lock to lock records and their gaps to prevent new records from being inserted. 2) In practical applications, by optimizing query and adjusting isolation levels, lock competition can be reduced and concurrency performance can be improved.


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