PostgreSQL 11 相似图像搜索插件 imgsmlr 性能测试与优化 2 - 单机分区表 (dblink 异步调用并行) (4亿图像)

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背景

《PostgreSQL 11 相似图像搜索插件 imgsmlr 性能测试 1 - 单机单表 (4亿图像)》

使用分区表+dblink异步接口并行调用。(内核层面直接支持imgsmlr gist index scan并行更好)

1、创建分区表

create table t_img (id int primary key, sig signature) partition by hash (id);    

2、创建64个分区

do language plpgsql $$  
declare  
  i int;  
begin  
  for i in 0..63   
  loop  
    execute format('create table t_img%s partition of t_img for values WITH (MODULUS 64, REMAINDER %s)', i, i);   
  end loop;  
end;  
$$;  

3、创建图像特征值字段索引

create index idx_t_img_1 on t_img using gist(sig);  

4、写入4亿随机图像特征值

vi test.sql  
\set id random(1,2000000000)  
insert into t_img values (:id, gen_rand_img_sig(10)) on conflict(id) do nothing;  
pgbench -M prepared -n -r -P 1 -f ./test.sql -c 64 -j 64 -t 10000000  

1、创建dblink插件

create extension if not exists dblink;      

2、创建一个建立连接函数,不报错

create or replace function conn(        
  name,   -- dblink名字        
  text    -- 连接串,URL        
) returns void as $$          
declare          
begin          
  perform dblink_connect($1, $2);         
  return;          
exception when others then          
  return;          
end;          
$$ language plpgsql strict;      

3、编写一个函数,输入参数为分区数,图像特征值。开启64个并行同时搜索每个分区,返回一条最相似的图像记录。

create or replace function parallel_img_search(  
  v_mod int,   -- 分区数  
  v_sig signature,  -- 图像特征值  
  conn text default format('hostaddr=%s port=%s user=%s dbname=%s application_name=', '127.0.0.1', current_setting('port'), current_user, current_database())  -- dblink连接  
)  
returns setof record as  
$$  
declare  
  app_prefix text := 'abc';     
  sql text;  
  ts1 timestamp;  
begin  
  for i in 0..v_mod loop  
    perform conn(app_prefix||i,  conn||app_prefix||i);   
    perform id,sig from dblink_get_result(app_prefix||i, false) as t(id int, sig signature);   
    sql := format('select * from t_img%s order by sig <-> %L limit 1', i, v_sig);  
    perform dblink_send_query(app_prefix||i, sql);     
  end loop;  
  
  ts1 := clock_timestamp();  
  for i in 0..v_mod loop  
    return query select id,sig from dblink_get_result(app_prefix||i, false) as t(id int, sig signature);    
  end loop;  
  raise notice '%', clock_timestamp()-ts1;  
    
  return;  
end;  
$$ language plpgsql strict;  

4、创建一个stable函数,用于生成随机图像特征值。

create or replace function get_rand_img_sig(int) returns signature as $$  
  select ('('||rtrim(ltrim(array(select (random()*$1)::float4 from generate_series(1,16))::text,'{'),'}')||')')::signature;  
$$ language sql strict stable;  

例子

postgres=# select get_rand_img_sig(10);  
                                                                         get_rand_img_sig                                                                           
------------------------------------------------------------------------------------------------------------------------------------------------------------------  
 (3.970030, 2.340900, 0.946223, 5.951010, 6.560340, 7.922950, 6.646290, 0.430310, 7.690120, 5.799870, 1.337850, 1.319830, 3.178170, 6.439380, 0.925341, 2.215810)  
(1 row)  
  
Time: 0.345 ms  

5、写入约2.98亿图像特征值。

postgres=# select count(*) from t_img;  
   count     
-----------  
 297915819  
(1 row)  

使用dblink异步调用并行查询64个分区

使用dblink异步调用接口,查询所有分区,耗时:394毫秒

postgres=# select * from  parallel_img_search(63, '(3.970030, 2.340900, 0.946223, 5.951010, 6.560340, 7.922950, 6.646290, 0.430310, 7.690120, 5.799870, 1.337850, 1.319830, 3.178170, 6.439380, 0.925341, 2.215810)'::signature) as t (id int, sig signature) order by sig <-> '(3.970030, 2.340900, 0.946223, 5.951010, 6.560340, 7.922950, 6.646290, 0.430310, 7.690120, 5.799870, 1.337850, 1.319830, 3.178170, 6.439380, 0.925341, 2.215810)'::signature limit 1;  
  
  
NOTICE:  00:00:00.394257  
     id     |                                                                               sig                                                                                  
------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------  
 1918283556 | (3.122560, 2.748080, 1.133250, 5.426950, 6.626340, 6.876810, 7.959190, 0.798523, 8.638600, 5.075110, 1.366100, 0.899454, 2.980070, 4.580630, 0.986704, 1.582110)  
(1 row)  
  
Time: 741.161 ms  

直接查询单个分区耗时:238毫秒

postgres=# explain (analyze,verbose,timing,costs,buffers) select sig from t_img48 order by sig <-> '(3.970030, 2.340900, 0.946223, 5.951010, 6.560340, 7.922950, 6.646290, 0.430310, 7.690120, 5.799870, 1.337850, 1.319830, 3.178170, 6.439380, 0.925341, 2.215810)' limit 1;  
                                                                                                    QUERY PLAN                                                                                                       
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------  
 Limit  (cost=0.36..0.37 rows=1 width=72) (actual time=231.287..231.288 rows=1 loops=1)  
   Output: id, sig, ((sig <-> '(3.970030, 2.340900, 0.946223, 5.951010, 6.560340, 7.922950, 6.646290, 0.430310, 7.690120, 5.799870, 1.337850, 1.319830, 3.178170, 6.439380, 0.925341, 2.215810)'::signature))  
   Buffers: shared hit=11881  
   ->  Index Scan using t_img48_sig_idx on public.t_img48  (cost=0.36..41619.32 rows=4466603 width=72) (actual time=231.285..231.285 rows=1 loops=1)  
         Output: id, sig, (sig <-> '(3.970030, 2.340900, 0.946223, 5.951010, 6.560340, 7.922950, 6.646290, 0.430310, 7.690120, 5.799870, 1.337850, 1.319830, 3.178170, 6.439380, 0.925341, 2.215810)'::signature)  
         Order By: (t_img48.sig <-> '(3.970030, 2.340900, 0.946223, 5.951010, 6.560340, 7.922950, 6.646290, 0.430310, 7.690120, 5.799870, 1.337850, 1.319830, 3.178170, 6.439380, 0.925341, 2.215810)'::signature)  
         Buffers: shared hit=11881  
 Planning Time: 0.060 ms  
 Execution Time: 237.818 ms  
(9 rows)  
  
Time: 238.242 ms  

相比于第一篇文档:单表4.39亿图像,以图搜图耗时4.2秒。使用dblink异步接口(64并行,2.98亿),以图搜图耗时394毫秒,有较大性能提升。

小结

使用dblink异步调用,并没有达到238毫秒,而是394毫秒。

使用dblink异步调用后,每秒处理的索引数据约15 GB。

postgres=# select pg_size_pretty(11881*64*8192::numeric/0.394);  
 pg_size_pretty   
----------------  
 15 GB  
(1 row)  
  
Time: 0.258 ms  

瓶颈可能到了内存COPY上面。

下一篇我们看一下使用citus 多机的情况 。

参考

https://github.com/postgrespro/imgsmlr

《PostgreSQL 相似搜索插件介绍大汇总 (rum,pg_trgm,smlar,imgsmlr,pg_similarity) (rum,gin,gist)》

《PostgreSQL dblink异步调用实践,跑并行多任务 - 例如开N个并行后台任务创建索引, 开N个后台任务跑若干SQL》

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