之前在springboot+mybatis环境的坑和sql语句简化技巧的第2点提到，数据库的一对多查询可以一次查询多级数据，并且把拿到的数据按id聚合，使父级表和子级表都有数据。
但是这种查询，必然要查询大量的重复父数据，如果不用这种方法，而是分级查询，效果会如何？
要知道这2种数据的查询效率如何，用Python可以简单查询到总时长。
首先用pip install MySQL-python这条指令安装，至于出错解决方法就是https://www.cnblogs.com/superxuezhazha/p/6619036.html这篇文章的事了。
上代码：
import MySQLdb
import json
import uuid
import random
import traceback
import time
plan_id = 'assssss'
use_times = 0
def noSubUuid(namespace=None):
global use_times
if namespace == None:
use_times = use_times + 1
return str(uuid.uuid3(uuid.NAMESPACE_DNS,str(use_times))).replace('-','')
else:
return str(uuid.uuid3(uuid.NAMESPACE_DNS,namespace)).replace('-','')
# Add Sample Data.生成示例数据
def addData(cursor, db):
try:
start = 18
user_ids = []
user_number_id = 490
for _ in range(600):
user_id = noSubUuid()
insertUserSql = 'insert into user VALUES (%d,\'%s\',\'%s\',\'YWRtaW4=\',\'%s\',2,0,1,NULL,NULL,NULL,\'2018-08-21 07:20:13\',NULL,NULL,NULL,\'my_ass_bdpf\',\'MXQ2NWRhNDNXNmM0OWQ1dG9rZW5fc2FsdA==\',\'2bbf024395e84adf80e2e72c6330ea57\')'%(user_number_id,user_id,noSubUuid()[20:],noSubUuid())
print(insertUserSql)
cursor.execute(insertUserSql)
user_ids.append(user_id)
user_number_id = user_number_id+1
line_id = 490
man_num_id = 490
study_num_id = 590
limitNum = 450
for _ in range(400):
start = 0
manage_id = noSubUuid()
insertLineSql = 'insert into experiment_teaching_plan_resource_line values (%d,\'%s\',\'%s\',\'%s\')'%(line_id,noSubUuid(),plan_id,manage_id)
print(insertLineSql)
cursor.execute(insertLineSql)
line_id = line_id + 1
insertManaSql = 'insert into resource_management values (%d,\'%s\',\'%s\',\'%s\',\'%s\',\'%s\',\'%s\',\'20180109000000\',\'my_ass_bdpf\',4)'%(man_num_id,noSubUuid(),noSubUuid(),noSubUuid(),manage_id,noSubUuid(),noSubUuid())
print(insertManaSql)
man_num_id = man_num_id + 1
cursor.execute(insertManaSql)
for user_id in user_ids:
if(start >= limitNum):
return
if(random.randint(0, 2) == 1):
insertStudSql = 'insert into course_resource_study values (%d,\'%s\',\'%s\',\'%s\',null,null,null)'%(study_num_id,noSubUuid(),manage_id,noSubUuid())
print(insertStudSql)
cursor.execute(insertStudSql)
study_num_id = study_num_id + 1
start = start + 1
#
db.commit()
except Exception as e:
print(traceback.format_exc())
db.rollback()
# Rollback Sample Data.如果数据量过大对服务器造成影响，可以回滚示例数据
def rollbackData(cursor, db):
try:
cursor.execute('delete from course_resource_study where student_id in (select uid from user where user_col3 = \'my_ass_bdpf\')')
cursor.execute('delete from user where user_col3 = \'my_ass_bdpf\'')
cursor.execute('delete from experiment_teaching_plan_resource_line where resource_management_id in (select rm.resource_management_id COLLATE utf8_general_ci from resource_management rm where experimental_time = \'my_ass_bdpf\')')
cursor.execute('delete from resource_management where experimental_time = \'my_ass_bdpf\'')
db.commit()
except Exception as e:
print(traceback.format_exc())
db.rollback()
# Query data like mybatis collection query.像Mybatis的collection查询一样查询数据
def SelectAtOnce(cursor, db):
sql = 'select etp.*,rm.*,crs.* '\
+ 'from experiment_teaching_plan etp '\
+ 'JOIN experiment_teaching_plan_resource_line etpl ON etp.id=etpl.teaching_plan_id '\
+ 'JOIN resource_management rm ON rm.resource_management_id=etpl.resource_management_id COLLATE utf8_general_ci '\
+ 'JOIN course_resource_study crs ON rm.resource_management_id=crs.resource_management_id '\
+ 'where etp.id=\'assssss\''
cnt = cursor.execute(sql)
# Query data step by step.分级查询数据
def SelectByStep(cursor, db):
cursor.execute('select * from experiment_teaching_plan where id=\'assssss\'')
results = cursor.fetchall()
plan_id = results[0][0]
cursor.execute('select * from experiment_teaching_plan_resource_line where teaching_plan_id=\'%s\''%(plan_id,))
ids = ','.join(list(map(lambda a:"'" + a[3] + "'",cursor.fetchall())))
cursor.execute('select * from resource_management where resource_management_id in (%s)'%ids)
ids = ','.join(list(map(lambda a:"'" + a[4] + "'",cursor.fetchall())))
cursor.execute('select * from course_resource_study where resource_management_id in (%s)'%ids)
#
if __name__ == '__main__':
db = MySQLdb.connect("localhost", "root", "acmicpc", "my_ass_bdpf", charset='utf8')
cursor = db.cursor()
addData(cursor, db)
#rollbackData(cursor, db) start = time.time()
SelectAtOnce(cursor, db)
mid = time.time()
print(mid - start) SelectByStep(cursor, db)
print(time.time() - mid) cursor.close()
db.close()
#
插入、回滚、查询一条龙
mysql代码：
DROP TABLE IF EXISTS `resource_management`;
CREATE TABLE `resource_management` (
`id` int(10) NOT NULL AUTO_INCREMENT COMMENT '自增ID',
`course_structure_id` varchar(255) COLLATE utf8_unicode_ci NOT NULL COMMENT '课程体系ID',
`course_classification_id` varchar(255) COLLATE utf8_unicode_ci NOT NULL COMMENT '课程分类ID',
`course_content_id` varchar(32) COLLATE utf8_unicode_ci NOT NULL COMMENT '课程内容ID',
`resource_management_id` varchar(32) COLLATE utf8_unicode_ci NOT NULL COMMENT '实验主键ID',
`resource_management_name` varchar(100) COLLATE utf8_unicode_ci NOT NULL COMMENT '实验名称',
`resource_management_desc` varchar(200) COLLATE utf8_unicode_ci DEFAULT NULL COMMENT '描述',
`create_time` timestamp NULL DEFAULT CURRENT_TIMESTAMP COMMENT '创建时间',
`experimental_time` varchar(255) COLLATE utf8_unicode_ci NOT NULL COMMENT '实验时长',
`resource_order` int(255) NOT NULL COMMENT '文档顺序',
PRIMARY KEY (`id`),
UNIQUE KEY `UNIQUE_VIDEONAME` (`resource_management_name`,`course_content_id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8 COLLATE=utf8_unicode_ci COMMENT='实验基本信息表'; #
# Data for table "experiment_teaching_plan"
# INSERT INTO `experiment_teaching_plan` VALUES ('27421b344b7242a980e139dd3c25f11e','5b3fb1014c62492cb2193686bdf90d45','ass','assss','2019-01-10 16:22:27'),('assssss','27adf7cee44347b4847943c1548887c4','my_test','my_test','2019-04-05 11:23:42'),('ferhh','gfjtjtjtr','在哪?','deswrtyuio','0000-00-00 00:00:00'); DROP TABLE IF EXISTS `experiment_teaching_plan_resource_line`;
CREATE TABLE `experiment_teaching_plan_resource_line` (
`id` int(11) NOT NULL AUTO_INCREMENT COMMENT '自增ID',
`resource_line_id` varchar(32) NOT NULL COMMENT '中间表ID',
`teaching_plan_id` varchar(32) NOT NULL COMMENT '课程教学计划表主键ID',
`resource_management_id` varchar(32) NOT NULL COMMENT '课程资源表主键ID',
PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8 COMMENT='课程教学计划和资料库关联'; DROP TABLE IF EXISTS `course_resource_study`;
CREATE TABLE `course_resource_study` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`student_id` varchar(32) CHARACTER SET utf8 COLLATE utf8_unicode_ci NOT NULL COMMENT '学生ID',
`resource_management_id` varchar(32) CHARACTER SET utf8 COLLATE utf8_unicode_ci NOT NULL COMMENT '实验ID',
`course_content_id` varchar(32) CHARACTER SET utf8 COLLATE utf8_unicode_ci NOT NULL COMMENT '实验内容ID',
`experiment_summary` longtext COMMENT '实验总结',
`create_time` timestamp NULL DEFAULT CURRENT_TIMESTAMP COMMENT '创建时间',
`update_time` timestamp NULL DEFAULT NULL COMMENT '更新时间',
PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8 COMMENT='学生实验学习关系表';
写好之后把这段mysql代码在mysql服务器上运行，之后用这段python代码查询。
结果如下：
可以看到，包含大量重复父级数据的查询（这次数据量有80104条）会严重影响查询效率，如果数据量再大一些，或者查询级数再深一些，可能就会彻底堵死整个http请求，使某个客户端得不到回应。
如果考虑到mybatis的collection查询比分级查询快的情况，数据量事实上小得不值一提了（这个例子有80000条数据，稍微有点用的网站储存的数据可能都不止一点）
所以Mybatis的这种collection查询功能不是特别推荐（应该说凡是大数据量的系统都不应该用这种查询），分开查代码会麻烦一些，但是后期数据量上来的话性能占优。