大橙子网站建设,新征程启航
为企业提供网站建设、域名注册、服务器等服务
本篇内容介绍了“怎么使用PostgreSQL中Hash索引”的有关知识,在实际案例的操作过程中,不少人都会遇到这样的困境,接下来就让小编带领大家学习一下如何处理这些情况吧!希望大家仔细阅读,能够学有所成!
创新互联建站专注于津南网站建设服务及定制,我们拥有丰富的企业做网站经验。 热诚为您提供津南营销型网站建设,津南网站制作、津南网页设计、津南网站官网定制、成都微信小程序服务,打造津南网络公司原创品牌,更为您提供津南网站排名全网营销落地服务。
逻辑结构
可以把Hash Index理解为一个Hash Table,每个Hash bucket存储根据Hash Function计算得到的对应的索引条目,为了节省空间,Hash索引条目只存储Hash Code(即Hash Value) + TID而不存储Hash Key(即索引键值),扫描索引后还必须读取相应的数据表行,因此Index Only Scan不适用于Hash Index.
testdb=# drop table if exists t_idx1; DROP TABLE testdb=# create table t_idx1(id int,c1 varchar(20)); CREATE TABLE testdb=# create index idx_t_idx1_id on t_idx1 using hash(id); CREATE INDEX testdb=# insert into t_idx1 select generate_series(1,100000); INSERT 0 100000 testdb=# analyze t_idx1; ANALYZE testdb=# explain verbose select * from t_idx1 where id = 1; QUERY PLAN ------------------------------------------------------------------------------------ Index Scan using idx_t_idx1_id on public.t_idx1 (cost=0.00..8.02 rows=1 width=62) Output: id, c1 Index Cond: (t_idx1.id = 1) (3 rows) testdb=# -- 不能实现Index Only Scan testdb=# explain verbose select id from t_idx1 where id = 100; QUERY PLAN ----------------------------------------------------------------------------------- Index Scan using idx_t_idx1_id on public.t_idx1 (cost=0.00..8.02 rows=1 width=4) Output: id Index Cond: (t_idx1.id = 100) (3 rows)
而普通的B-Tree索引是可以Index Only Scan的:
testdb=# create table t_idx2(id int,c1 varchar(20)); CREATE TABLE testdb=# insert into t_idx2 select generate_series(1,100000); INSERT 0 100000 testdb=# create index idx_t_idx2_id on t_idx2 using btree(id); CREATE INDEX testdb=# analyze t_idx2; ANALYZE testdb=# explain verbose select id from t_idx2 where id = 100; QUERY PLAN ---------------------------------------------------------------------------------------- Index Only Scan using idx_t_idx2_id on public.t_idx2 (cost=0.29..8.31 rows=1 width=4) Output: id Index Cond: (t_idx2.id = 100) (3 rows)
有四种页面,分别是Meta page,Bucket Page,Overflow page和Bitmap page.
页面类型 | 说明 |
---|---|
Meta page | page number zero, which contains information on what is inside the index. |
Bucket pages | main pages of the index, which store data as «hash code — TID» pairs. |
Overflow pages | structured the same way as bucket pages and used when one page is insufficient for a bucket |
Bitmap pages | which keep track of overflow pages that are currently clear and can be reused for other buckets |
使用pageinspect插件可查看index中的相关信息
testdb=# select hash_page_type(get_raw_page('idx_t_idx1_id',0)); hash_page_type ---------------- metapage (1 row) testdb=# select hash_page_type(get_raw_page('idx_t_idx1_id',1)); hash_page_type ---------------- bucket (1 row) testdb=# \x Expanded display is on. testdb=# select * from hash_page_stats(get_raw_page('idx_t_idx1_id',1)); -[ RECORD 1 ]---+----------- live_items | 189 dead_items | 0 page_size | 8192 free_size | 4368 hasho_prevblkno | 256 hasho_nextblkno | 4294967295 hasho_bucket | 0 hasho_flag | 2 hasho_page_id | 65408 testdb=# select * from hash_page_stats(get_raw_page('idx_t_idx1_id',2)); -[ RECORD 1 ]---+----------- live_items | 201 dead_items | 0 page_size | 8192 free_size | 4128 hasho_prevblkno | 257 hasho_nextblkno | 4294967295 hasho_bucket | 1 hasho_flag | 2 hasho_page_id | 65408
“怎么使用PostgreSQL中Hash索引”的内容就介绍到这里了,感谢大家的阅读。如果想了解更多行业相关的知识可以关注创新互联网站,小编将为大家输出更多高质量的实用文章!