openGauss每日一练第20天

1.tsvector
–把一个字符串按照空格进行分词，分词的顺序是按照长短和字母排序的, 自动去掉分词中重复的词条

SELECT 'The Fat Rats'::tsvector;


–词条位置常量也可以放到词汇中

SELECT 'a:1 fat:2 cat:3 sat:4 on:5 a:6 mat:7 and:8 ate:9 a:10 fat:11 rat:12'::tsvector;


–拥有位置的词汇甚至可以用一个权来标记，反映文档结构，这个权可以是A，B，C或D。默认的是D，因此输出中不会出现

SELECT 'a:1A fat:2B,4C cat:5D'::tsvector;


–to_tsvector函数对这些单词进行规范化处理, 罗列出词条并连同它们文档中的位置

SELECT to_tsvector('english', 'The Fat Rats');

2.tsquery
SELECT 'fat & rat'::tsquery;

–规范化转为tsquery类型

SELECT to_tsquery('Fat:ab & Cats');
3.基本文本匹配
–全文检索基于匹配算子@@，当一个tsvector匹配到一个tsquery时，则返回true, tsvector和tsquery两种数据类型可以任意排序。

SELECT 'a fat cat sat on a mat and ate a fat rat'::tsvector @@ 'cat & rat'::tsquery AS RESULT;
SELECT 'fat & cow'::tsquery @@ 'a fat cat sat on a mat and ate a fat rat'::tsvector AS RESULT;
– to_tsvector和to_tsquery标准化处理

SELECT to_tsvector('fat cats ate fat rats') @@ to_tsquery('fat & rat') AS RESULT;
SELECT to_tsvector('fat cats ate fat rats') @@ to_tsquery('fat & cow') AS RESULT;
4.分词器
–查看所有分词器

\dF
–查看默认分词器

show default_text_search_config;
5.表和索引
CREATE SCHEMA tsearch;
CREATE TABLE tsearch.pgweb(id int, body text, title text, last_mod_date date);
INSERT INTO tsearch.pgweb VALUES(1, 'China, officially the People''s Republic of China(PRC), located in Asia, is the world''s most populous state.', 'China', '2010-1-1');
INSERT INTO tsearch.pgweb VALUES(2, 'America is a rock band, formed in England in 1970 by multi-instrumentalists Dewey Bunnell, Dan Peek, and Gerry Beckley.', 'America', '2010-1-1');
INSERT INTO tsearch.pgweb VALUES(3, 'England is a country that is part of the United Kingdom. It shares land borders with Scotland to the north and Wales to the west.', 'England','2010-1-1');
–将body字段中包含america的行打印出来

SELECT id, body, title FROM tsearch.pgweb WHERE to_tsvector(body) @@ to_tsquery('america');
–检索出在title或者body字段中包含china和asia的行

SELECT title FROM tsearch.pgweb WHERE to_tsvector(title || ' ' || body) @@ to_tsquery('china & asia');
–为了加速文本搜索，可以创建GIN索引(指定english配置来解析和规范化字符串)

CREATE INDEX pgweb_idx_1 ON tsearch.pgweb USING gin(to_tsvector('english', body));
–连接列的索引

CREATE INDEX pgweb_idx_3 ON tsearch.pgweb USING gin(to_tsvector('english', title || ' ' ||body));
–查看索引定义

\d+ tsearch.pgweb
6.清理数据
drop schema tsearch cascade;

课程作业
1.用tsvector @@ tsquery和tsquery @@ tsvector完成两个基本文本匹配
SELECT 'my name is dai'::tsvector @@ 'name & dai'::tsquery AS RESULT;
SELECT 'dai & name'::tsquery @@ 'my name is dai'::tsvector AS RESULT;
2.创建表且至少有两个字段的类型为 text类型，在创建索引前进行全文检索
create schema dai;
create table dai.student
(student_id INTEGER,
student_name text,
student_city text
);
insert into hc.student(student_id,student_name,student_city) values(1,'dai','he come from zhengzhou'),(2,'zhang','she come from guangzhou'),(3,'wang','he come from shanghai');
SELECT student_id, student_name, student_city FROM dai.student WHERE to_tsvector(student_city) @@ to_tsquery('zhengzhou');
3.创建GIN索引
CREATE INDEX student_idx_1 ON dai.student USING gin(to_tsvector('english', student_city));
4.清理数据
drop schema hc cascade;