本篇內(nèi)容介紹了“怎么使用PostgreSQL中Hash索引”的有關(guān)知識(shí),在實(shí)際案例的操作過(guò)程中,不少人都會(huì)遇到這樣的困境,接下來(lái)就讓小編帶領(lǐng)大家學(xué)習(xí)一下如何處理這些情況吧!希望大家仔細(xì)閱讀,能夠?qū)W有所成!
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可以把Hash Index理解為一個(gè)Hash Table,每個(gè)Hash bucket存儲(chǔ)根據(jù)Hash Function計(jì)算得到的對(duì)應(yīng)的索引條目,為了節(jié)省空間,Hash索引條目只存儲(chǔ)Hash Code(即Hash Value) + TID而不存儲(chǔ)Hash Key(即索引鍵值),掃描索引后還必須讀取相應(yīng)的數(shù)據(jù)表行,因此Index Only Scan不適用于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=# -- 不能實(shí)現(xiàn)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)
有四種頁(yè)面,分別是Meta page,Bucket Page,Overflow page和Bitmap page.
頁(yè)面類型 | 說(shuō)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中的相關(guān)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
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標(biāo)題名稱:怎么使用PostgreSQL中Hash索引-創(chuàng)新互聯(lián)
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