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怎么实现数据库分区表+dblink异步调用并行-创新互联
本篇内容介绍了“怎么实现数据库分区表+dblink异步调用并行”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！
分区表 + dblink 异步调用 并行
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
dblink 异步调用封装
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
“怎么实现数据库分区表+dblink异步调用并行”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-成都网站建设公司网站，小编将为大家输出更多高质量的实用文章！
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