本篇文章讲解C语言调用mysql数据库的存储过程的方法
下面假设有一张sc表,保存学生选课记录,有课程号,学号,平时分,卷面分,总分。
建立数据库表过程:
create table class(
cno varchar(8) not null,
sno varchar(8) not null,
ordinary_score int,
last_score int,
all_score int
);
存储过程
由括号包围的参数列必须总是存在。如果没有参数,也该使用一个空参数列()。每个参数 默认都是一个IN参数。要指定为其它参数,可在参数名之前使用关键词IN(默认,可缺省) OUT或INOUT。
IN参数是只传入
OUT参数是只传出
INOUT参数是既传入又传入,即双向传递
指定参数为IN, OUT, 或INOUT 只对PROCEDURE是合法的。(FUNCTION参数总是被认为是IN参数)
建立存储过程,传入平时分x,卷面分y,平时分所占的比率pert,学号,课程号;建立过程如下
<code class="hljs oxygene">delimiter // CREATE PROCEDURE cal_grade(x INT,y INT,out t int,pert float,s VARCHAR(8),c VARCHAR(8)) LABEL_PROC: BEGIN IF ( x < 0 || x > 100 ) THEN SET t = -1; LEAVE LABEL_PROC; END IF; IF ( y < 0 || y > 100 ) THEN SET t = -2; LEAVE LABEL_PROC; END IF; SET t = ROUND( x*pert + y*(1-pert) ); UPDATE sc SET ordinary_score=x,last_score=y WHERE sno=s AND cno=c AND tno=tn; END LABEL_PROC // delimiter ; </code>
<strong>C语言调用</strong>
<code class="hljs oxygene"><code class="hljs perl">#include <stdio.h> #include "mysql.h" int main() { MYSQL *my_connection; MYSQL_RES *res_ptr; MYSQL_ROW sqlrow; char buf[100]; my_connection = mysql_init (NULL); //下面连接的最后一个参数必须为CLIENT_MULTI_STATEMENTS,不然就会报错select error: PROCEDURE *** can’t return a result set in the given context my_connection = mysql_real_connect (my_connection, "localhost", "root", "root", "test", 0, NULL, CLIENT_MULTI_STATEMENTS); sprintf (buf, "call cal_grade(%d,%d,@t,%f,%s,%s)", 10, 10, 0.3, 123, 456); if ( mysql_query (my_connection, buf) ) sprintf (stderr, mysql_error (my_connection)); else { //获得返回参数@t,@t是传出参数 mysql_query (my_connection, "select @t"); res_ptr = mysql_store_result (my_connection); if (res_ptr) { sqlrow = mysql_fetch_row (res_ptr); if (!strcmp (sqlrow[0], "-1")) printf ("平时分不在范围之内\n"); else if (!strcmp (sqlrow[0], "-2")) printf ("卷面分不在范围之内\n"); else printf ("总分为:%s\n", sqlrow[0]); } mysql_free_result (res_ptr); } mysql_close (my_connection); return 0; }</stdio.h></code></code>

InnoDB uses redologs and undologs to ensure data consistency and reliability. 1.redologs record data page modification to ensure crash recovery and transaction persistence. 2.undologs records the original data value and supports transaction rollback and MVCC.

Key metrics for EXPLAIN commands include type, key, rows, and Extra. 1) The type reflects the access type of the query. The higher the value, the higher the efficiency, such as const is better than ALL. 2) The key displays the index used, and NULL indicates no index. 3) rows estimates the number of scanned rows, affecting query performance. 4) Extra provides additional information, such as Usingfilesort prompts that it needs to be optimized.

Usingtemporary indicates that the need to create temporary tables in MySQL queries, which are commonly found in ORDERBY using DISTINCT, GROUPBY, or non-indexed columns. You can avoid the occurrence of indexes and rewrite queries and improve query performance. Specifically, when Usingtemporary appears in EXPLAIN output, it means that MySQL needs to create temporary tables to handle queries. This usually occurs when: 1) deduplication or grouping when using DISTINCT or GROUPBY; 2) sort when ORDERBY contains non-index columns; 3) use complex subquery or join operations. Optimization methods include: 1) ORDERBY and GROUPB

MySQL/InnoDB supports four transaction isolation levels: ReadUncommitted, ReadCommitted, RepeatableRead and Serializable. 1.ReadUncommitted allows reading of uncommitted data, which may cause dirty reading. 2. ReadCommitted avoids dirty reading, but non-repeatable reading may occur. 3.RepeatableRead is the default level, avoiding dirty reading and non-repeatable reading, but phantom reading may occur. 4. Serializable avoids all concurrency problems but reduces concurrency. Choosing the appropriate isolation level requires balancing data consistency and performance requirements.

MySQL is suitable for web applications and content management systems and is popular for its open source, high performance and ease of use. 1) Compared with PostgreSQL, MySQL performs better in simple queries and high concurrent read operations. 2) Compared with Oracle, MySQL is more popular among small and medium-sized enterprises because of its open source and low cost. 3) Compared with Microsoft SQL Server, MySQL is more suitable for cross-platform applications. 4) Unlike MongoDB, MySQL is more suitable for structured data and transaction processing.

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.


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