2018-8-25未命名文件

Posted 2021-01-01 cerofang

2018-8-25未命名文件

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小书匠

type(None) 16:35:39
elasticSearch解决大数据量字段模糊查询，建立数据索引库，全文检索方式查询。
全文检索：检索文本中的每个词与搜索项进行对此。
全文索引：采用分词器，对文本每个词进行切分，建立词条，方便进行查找。

Lucene 就是一套 全文检索编程API ， 基于Lucene 对数据建立索引，进行查询
现在企业开发中，更常用是的 solr 搜索服务器和 ElasticSearch 搜索服务器
1.索引对象： 存储数据的表结构 ，任何搜索数据，存放在索引对象上
2.映射：数据如何存放到索引对象上，需要有一个映射配置， 数据类型、是否存储、是否分词
3.文档： 一条数据记录， 存在索引对象上
4.文档类型： 一个索引对象 存放多种类型数据，数据用文档类型进行标识

ElasticSearch有什么优点呢?
1 分布式实时文件存储，可将每一个字段存入索引，使其可以被检索到。?
2 实时分析的分布式搜索引擎。?
分布式：索引分拆成多个分片，每个分片可有零个或多个副本。集群中的每个数据节点都可承载一个或多个分片，并且协调和处理各种操作；?
负载再平衡和路由在大多数情况下自动完成。?
3 可以扩展到上百台服务器，处理PB级别的结构化或非结构化数据。也可以运行在单台PC上（已测试）?
支持插件机制，分词插件、同步插件、Hadoop插件、可视化插件等。

select * from students where name != "周杰伦";

select * from students where is_delete=0;

select * from students where id > 3 and gender = 0;

select * from student where name like "黄%";

select * from students where id between 3 and 8;

select * from students where height is null;

select * from students order by id desc;

select * from students where gender=1 order by id asc;

select * from students order by height desc, id asc;

select count(*) from students;

sel

select max(height) from students;

select sum(age) from students;

select avg(age) from students;

select sum(age) from students where gender = 1;

select avg(age) from students where gender = 1;

select sum(age)/count(*) from students;

select sum(age)/count(*) from students where gender = 1;

select gender from students group by gender;

select gender,group_concat(name) from students group by gender;

select gender,group_concat(name) from students group by gender;

select gender,avg(age) from students group by gender;

select gender,count(*) from students group by gender;

select gender,count() from students group by gender having count() > 2;

select gender,count(*) from students group by gender having gender = "男";

select gender,count(*) from students group by gender with rollup;

select gender,count(*),sum(age) from students group by gender with rollup;

select gender,group_concat(age) from students group by gender with rollup;

select * from students limit 0,4;

select * from students limit 2,2;

select * from students inner join classes on students.cls_id = classes.id;

select * from students inner join classes on students.cls_id = classes.id;

select * from students as s inner join classes as c on s.cls_id = c.id;

select * from students as s left join classes as c on s.cls_id = c.id;

select * from students as s right join classes c on s.cls_id = c.id;

select * from students order by id desc limt 0,2;

select * from students where age > (select avg(age) from students) ;

select * from students where age > (select avg(age) from students);

select * from classes where id in (select cls_id from students);

select * from students where (age,height) = (select max(age),max(height) from students);

select distinct gender from students;

select gender ,count(*) from students group by gender;

select gender,group_concat(name) from students group by gender;

select cls_id,group_concat(name) from students group by cls_id;

select * from students order by id desc;

select gender,count() from students group by gender having count() >2;

select gender,count(*) from students group by gender with rollup;

select * from students order by id desc limit 0,10;

select * from students inner join classes on students.cls_id = classes.id;

select students.name,classes.name from students inner join classes on students.cls_id = classes.id;

select students.name as a,classes.name as b from students inner join classes on students.cls_id = classes.id;

select * from students as s left join classes as c on s.cls_id = c.id;

select * from students as s right join classes as c on s.cls_id = c.id;

create table booktest_areainfo(
aid int primary key,
atitle varchar(20),
pid int
);

select count(*) from booktest_areainfo where pid is null;

select atitle from booktest_areainfo where pid is null;

select city.* from booktest_areainfo as city inner join booktest_areainfo as province on city.pid = province.aid where province.atitle="湖北省";

数据库商品类表格的设计开发，

1,Django_Contab实现网站首页静态化页面的定时更新；
2,Redis数据库缓存高频数据，加快网站的响应速度；
3，账号（用户名，电话号） + 密码模式实现切换登录，QQ，微信，微博等第三方登录方式的引入，实现用户多渠道登录实现；
4,Celery搭配Admin站点类实现详情页面的后台数据变动实时同步更新详情静态化页面；
5,基于Cookie和Redis对传统购物车的优化，未登录用户购物车数据暂存Cookies，登录后同步数据到Redis中，提高用户购物体验；
6，订单模块的开发，Django中的Atomic来控制订单模块数据库事务的执行，乐观锁防止高并发下的超卖现象；
7，Docker来部署FastDFS,重载Django原生的文件管理类，将FastDFS融入到项目中，实现海量文件的存储；
8，sql数据库双机热备,主从配置实现读写分离，提高数据库性能；
9，Celery开启进程订阅redis数据过期信号，并相应的操作数据库进行库存的增加；
10，X-admin来搭建后台站点管理，实现用户权限管理；