PostgreSQL VOPS 向量计算 + DBLINK异步并行 - 单实例 10亿 聚合计算跑进2秒

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简介:

标签

PostgreSQL , 聚合 , vops , 向量计算 , jit , llvm , dblink 异步调用 , parallel hash agg


背景

目前PostgreSQL已内置了并行计算的能力(透明和非透明)。

结合列存+向量计算,PostgreSQL 统计分析能力到底能有多强?

本文以vops(向量计算) + 并行计算为例,演示了单实例PostgreSQL 10亿数据量的count,avg,min,max,sum查询,耗时不到2秒。

我们可以大胆的预见PostgreSQL支持列存和向量计算后,OLAP能力会有多强。

相关文档:

《PostgreSQL 11 preview - parallel hash (含hash JOIN , hash agg等) 性能极大提升》

《PostgreSQL dblink异步调用实现 并行hash分片JOIN - 含数据交、并、差 提速案例 - 含dblink VS pg 11 parallel hash join VS pg 11 智能分区JOIN》

《PostgreSQL 向量化执行插件(瓦片式实现-vops) 10x提速OLAP》

DEMO

1、创建生成dblink连接的函数,重复创建不报错。

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;       

2、生成10亿条数据,并按哈希分成56份(如果是多张表的话,请都按被JOIN的字段进行HASH分区)。

为了测试方便,这里将数据按同样的RANGE分成了56份,实际上使用HASH效果一样。

create unlogged table a(id int, c1 int);    
    
do language plpgsql $$    
declare    
begin    
  for i in 0..55 loop    
    execute format('create unlogged table a%s (like a) inherits (a)', i);    
  end loop;    
end;    
$$;    

生成10亿测试数据

do language plpgsql $$    
declare    
begin    
  for i in 0..55 loop           
    perform conn('link'||i,  'hostaddr=127.0.0.1 port=1921 user=postgres dbname=postgres');           
    perform dblink_send_query('link'||i, format('insert into a%s select generate_series(%s, %s), random()*99', i, i*17857142+1, (i+1)*17857142));          
  end loop;       
end;    
$$;    

1、普通分片表10亿

1、空间占用,34GB

postgres=# \dt+ a*  
                    List of relations  
 Schema | Name | Type  |  Owner   |  Size   | Description   
--------+------+-------+----------+---------+-------------  
 public | a    | table | postgres | 0 bytes |   
 public | a0   | table | postgres | 617 MB  |   
 public | a1   | table | postgres | 617 MB  |   
 public | a10  | table | postgres | 617 MB  |   
 public | a11  | table | postgres | 617 MB  |   
 public | a12  | table | postgres | 617 MB  |   
 public | a13  | table | postgres | 617 MB  |   
 public | a14  | table | postgres | 617 MB  |   
 public | a15  | table | postgres | 617 MB  |   
 public | a16  | table | postgres | 617 MB  |   
.............  

2、已使用DBLINK异步调用,防止再度并行,设置参数

alter role postgres set max_parallel_workers_per_gather=0;  
alter role postgres set work_mem='2GB';  

重新进入,参数生效

3、分片并行group by聚合函数

create or replace function get_res() returns setof record as $$    
declare    
begin    
  for i in 0..55 loop           
    perform conn('link'||i,  'hostaddr=127.0.0.1 port=1921 user=postgres dbname=postgres');           
    perform 1 from dblink_get_result('link'||i) as t(c1 int, cnt int8, min int, max int, sum int8);          
    perform dblink_send_query('link'||i, format('select c1,count(*),min(id),max(id),sum(id) from a%s group by c1', i));          
  end loop;       
  for i in 0..55 loop    
    return query select * from dblink_get_result('link'||i) as t(c1 int, cnt int8, min int, max int, sum int8);    
  end loop;    
end;    
$$ language plpgsql strict;    

4、查询耗时,9.6秒。

select c1, sum(cnt), sum(sum)/sum(cnt)::float8, min(min), max(max), sum(sum) from get_res() as t(c1 int, cnt int8, min int, max int, sum int8) group by c1;  
  
  
postgres=# select c1, sum(cnt), sum(sum)/sum(cnt)::float8, min(min), max(max), sum(sum) from get_res() as t(c1 int, cnt int8, min int, max int, sum int8) group by c1;  
 c1 |   sum    |     ?column?     | min |    max    |       sum          
----+----------+------------------+-----+-----------+------------------  
  7 | 10104223 |  500196670.66755 |  13 | 999999922 | 5054098704282486  
 41 | 10098079 | 500105983.312797 |  75 | 999999899 | 5050109727865311  
 72 | 10099035 | 499987853.746656 |   3 | 999999917 | 5049394834562362  
  2 | 10098707 | 500027259.278005 | 119 | 999999881 | 5049628783461600  
 29 | 10101931 | 500172863.741008 |  16 | 999999911 | 5052711757584067  
 71 | 10099125 | 500129933.363706 |  51 | 999999877 | 5050874713281733  
  6 | 10104713 | 500020892.341227 |  20 | 999999943 | 5052567611111995  
 74 | 10098824 | 499966081.890066 | 170 | 999999890 | 5049069466977368  
 38 | 10103601 | 499961610.602928 |  89 | 999999949 | 5051412628849349  
 88 | 10103668 | 499850251.056789 |  64 | 999999780 | 5050320986394444  
 84 | 10105345 |  500042003.07277 | 271 | 999999895 | 5053096955541396  
 68 | 10098999 |   499977042.1773 |  59 | 999999857 | 5049267648971511  
 55 | 10103707 | 499960231.761415 |  45 | 999999850 | 5051451693369436  
 64 | 10102942 | 500113184.404115 |  47 | 999999693 | 5052614495470081  
 24 | 10099982 |  499936812.84724 | 190 | 999999901 | 5049352810894492  
  9 | 10104341 | 499996733.660471 |  23 | 999999915 | 5052137495791580  
 63 | 10102023 | 499895229.112864 | 353 | 999999910 | 5049953102088419  
 98 | 10097327 | 499944814.066904 |  22 | 999999919 | 5048106269587731  
 59 | 10099747 | 499892322.509487 |   2 | 999999808 | 5048785984588223  
 78 | 10107866 | 500012506.299485 |  69 | 999999740 | 5054059411999348  
 18 | 10101977 | 499926956.667668 |   4 | 999999897 | 5050250617936782  
 90 | 10096744 | 500199293.810021 |  43 | 999999875 | 5050384218580567  
 42 | 10101533 | 500126553.670129 |  12 | 999999865 | 5052044886075076  
 10 | 10095854 |  500035390.09691 |  17 | 999999719 | 5048284293251445  
 79 | 10098900 | 499957103.416255 | 114 | 999999846 | 5049016791690421  
 12 | 10105025 | 499832509.132034 | 109 | 999999799 | 5050820000591935  
 32 | 10099491 | 500129108.718979 |  84 | 999999914 | 5051049432345352  
 81 | 10106622 | 499963749.199852 | 229 | 999999944 | 5052944626865710  
 34 | 10099359 | 500111032.921868 |  52 | 999999836 | 5050800861338764  
 85 | 10103461 | 499947692.923157 |  18 | 999999904 | 5051202017489091  
 37 | 10099584 | 500057275.745026 | 104 | 999999849 | 5050370461198054  
 69 | 10097014 | 500143184.435491 |  91 | 999999720 | 5049952735249734  
 52 | 10101573 | 500040171.388144 | 355 | 999999932 | 5051192294209851  
 76 | 10101689 | 499896977.810699 | 438 | 999999843 | 5049803801883577  
 35 | 10099622 | 500114054.898034 |  44 | 999999747 | 5050962911357394  
 65 | 10103111 |  499851261.81228 |  48 | 999999726 | 5050052781579531  
 31 | 10099277 | 499845188.908577 | 112 | 999999838 | 5048075019905046  
 51 | 10099397 | 499984737.203741 |  65 | 999999933 | 5049544354961246  
 57 | 10103823 | 500008680.942373 | 100 | 999999925 | 5051999210705205  
 19 | 10102592 | 500036435.174349 |  81 | 999999939 | 5051664089700899  
 33 | 10096464 | 500058135.753455 |  66 | 999999773 | 5048818965541870  
  0 |  5048622 |  500110433.47565 | 263 | 999999912 | 2524868536874701  
 50 | 10099019 | 500071716.158314 | 177 | 999999894 | 5050233762845416  
 89 | 10102886 | 499906895.352583 |  21 | 999999941 | 5050502374361080  
 66 | 10100455 | 500019718.104865 |  11 | 999999889 | 5050426661830877  
 17 | 10099749 | 500020536.906571 | 125 | 999999900 | 5050081917601604  
 14 | 10097995 | 499872474.436678 |  50 | 999999887 | 5047709747499202  
 87 | 10100597 | 499967794.215203 |  14 | 999999907 | 5049973202346696  
 67 | 10105426 | 500125756.387578 | 245 | 999999866 | 5053983821868692  
 96 | 10099064 | 499905578.187197 | 243 | 999999892 | 5048578428069509  
 61 | 10100503 | 500007920.183475 |  28 | 999999903 | 5050331497836948  
  3 | 10101198 | 499940146.381583 |  30 | 999999883 | 5049994406749350  
 39 | 10098880 | 500243255.820608 |  32 | 999999920 | 5051896611341620  
 11 | 10101799 | 500096301.902747 | 129 | 999999916 | 5051872322464871  
 43 | 10107301 |  500040498.08918 | 163 | 999999842 | 5054059826377266  
  5 | 10100558 | 499863342.325278 |  31 | 999999940 | 5048898681230323  
 75 | 10101250 | 500037496.222365 |  63 | 999999928 | 5051003758716163  
 97 | 10103503 | 500029746.921376 | 123 | 999999921 | 5052052048109365  
 21 | 10102929 | 500098408.485223 | 446 | 999999926 | 5052458713939206  
 93 | 10105004 | 499972842.513604 |  25 | 999999852 | 5052227573491343  
 60 | 10105650 | 499950744.869079 | 209 | 999999873 | 5052327244886207  
 27 | 10102588 | 499797776.872304 |  41 | 999999858 | 5049251023056813  
 45 | 10100466 | 499847713.021728 |  38 | 999999841 | 5048694830553717  
 70 | 10103640 | 500126978.162685 | 238 | 999999801 | 5053102941643626  
 91 | 10102311 |    499764530.032 |   1 | 999999950 | 5048776709152101  
 22 | 10099804 | 500243130.452219 | 250 | 999999867 | 5052357569913843  
 49 | 10099635 | 500022230.537738 |  19 | 999999896 | 5050042020317004  
 13 | 10100454 | 499986238.143486 |  53 | 999999646 | 5050087999001322  
 86 | 10099751 |  499991374.31582 |   7 | 999999782 | 5049788382737577  
 26 | 10105606 | 500021405.572664 |   6 | 999999938 | 5053019316283545  
  1 | 10095409 | 500001476.917716 | 206 | 999999776 | 5047719410088402  
 58 | 10099972 | 499913934.276812 |  35 | 999999792 | 5049116738605642  
 25 | 10104666 | 500031883.894369 | 137 | 999999510 | 5052655176103381  
 82 | 10101286 | 499966805.257835 |  10 | 999999534 | 5050307690415695  
 44 | 10104380 | 499990027.500454 |   9 | 999999872 | 5052089234075034  
 20 | 10100166 | 500033955.063915 | 130 | 999999908 | 5050425951782085  
 23 | 10099118 | 500033099.525857 |  58 | 999999918 | 5049893276017372  
 92 | 10097628 | 499985682.503551 |  79 | 999999951 | 5048669427246965  
 62 | 10098974 |  500002801.70268 |  33 | 999999765 | 5049515294322520  
 53 | 10104969 | 500071097.824301 |   5 | 999999948 | 5053202941310532  
 56 | 10099521 |  499829373.88272 | 157 | 999999902 | 5048037257945384  
 40 | 10098880 |  500118160.98974 | 202 | 999999731 | 5050633293656069  
 73 | 10102325 | 499981690.451386 |  62 | 999999809 | 5050977530989301  
 95 | 10102589 | 499885307.442653 |  74 | 999999770 | 5050135808231760  
  4 | 10094812 | 499884810.734528 |  37 | 999999815 | 5046243186020638  
 30 | 10097653 | 499985894.883754 | 127 | 999999861 | 5048684071430626  
 77 | 10097737 | 500019227.640071 |  34 | 999999751 | 5049062655652572  
 15 | 10100451 | 499990119.574357 |  86 | 999999946 | 5050125703244929  
 36 | 10097433 | 499910715.309699 |  60 | 999999952 | 5047814953821765  
 94 | 10097423 | 500030504.883845 | 102 | 999999930 | 5049019520715746  
 83 | 10097518 | 499986390.218504 |   8 | 999999777 | 5048621574986367  
 28 | 10102778 | 499892202.902798 | 147 | 999999929 | 5050299949857921  
 48 | 10095113 | 500116265.596128 | 171 | 999999942 | 5048730214330929  
 46 | 10101708 | 499972043.149036 |  24 | 999999878 | 5050571588054961  
 99 |  5051395 | 499818438.433132 |  39 | 999999936 | 2524780360808931  
 47 | 10106118 | 500030970.343216 |  29 | 999999844 | 5053371989943041  
 54 | 10096312 |  500084305.08323 |  77 | 999999934 | 5049007170423474  
 16 | 10104458 | 500003081.506687 |  36 | 999999800 | 5052260136954892  
 80 | 10102160 | 499846266.993651 |  54 | 999999945 | 5049526964572583  
  8 | 10103060 | 500007130.726843 | 136 | 999999891 | 5051602042161142  
(100 rows)  
  
Time: 9608.447 ms (00:09.608)  

5、CPU资源

top - 16:25:09 up 30 days, 21:12,  2 users,  load average: 15.10, 6.80, 6.63  
Tasks: 522 total,  57 running, 465 sleeping,   0 stopped,   0 zombie  
%Cpu(s): 99.8 us,  0.2 sy,  0.0 ni,  0.0 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st  
KiB Mem : 23094336+total,  9608932 free,  5427976 used, 21590646+buff/cache  
KiB Swap:        0 total,        0 free,        0 used. 10311448+avail Mem   

2、VOPS瓦片式存储表10亿

1、创建VOPS表

create unlogged table b(id vops_int4, c1 vops_int4);    
  
do language plpgsql $$    
declare    
begin    
  for i in 0..55 loop    
    execute format('create unlogged table b%s (like b) inherits (b)', i);    
  end loop;    
end;    
$$;    

2、将10亿原始数据转换为vops

do language plpgsql $$    
declare    
begin    
  for i in 0..55 loop    
    perform conn('link'||i,  'hostaddr=127.0.0.1 port=1921 user=postgres dbname=postgres');           
    perform dblink_send_query('link'||i, format('select populate(''b%s''::regclass, ''a%s''::regclass)', i, i));         
  end loop;    
end;    
$$;    

3、数据样例

postgres=# select * from b0 limit 2;  
-[ RECORD 1 ]----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------  
id | {1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64}  
c1 | {91,59,72,18,53,26,86,83,44,82,66,42,7,87,66,29,10,85,49,6,89,98,9,46,93,7,42,61,47,3,5,39,62,77,58,16,4,45,99,49,27,66,90,35,55,58,64,65,44,14,71,34,13,80,80,7,87,23,68,36,26,73,75,88}  
-[ RECORD 2 ]----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------  
id | {65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128}  
c1 | {51,33,6,55,78,5,5,7,72,95,41,27,54,6,92,98,19,64,34,32,45,15,39,33,38,9,69,64,82,45,53,34,78,59,90,57,64,94,64,37,91,6,64,46,12,58,45,31,23,79,64,68,94,4,2,33,13,71,97,95,17,51,30,95}  
  
postgres=# select * from a0 limit 2;  
-[ RECORD 1 ]  
id | 1  
c1 | 91  
-[ RECORD 2 ]  
id | 2  
c1 | 59  

4、空间占用,8.7GB

postgres=# \dt+ b*  
                    List of relations  
 Schema | Name | Type  |  Owner   |  Size   | Description   
--------+------+-------+----------+---------+-------------  
 public | b    | table | postgres | 0 bytes |   
 public | b0   | table | postgres | 156 MB  |   
 public | b1   | table | postgres | 156 MB  |   
 public | b10  | table | postgres | 156 MB  |   
 public | b11  | table | postgres | 156 MB  |   
 public | b12  | table | postgres | 156 MB  |   
 public | b13  | table | postgres | 156 MB  |   
 public | b14  | table | postgres | 156 MB  |   
 public | b15  | table | postgres | 156 MB  |   
 public | b16  | table | postgres | 156 MB  |   
 public | b17  | table | postgres | 156 MB  |   
 public | b18  | table | postgres | 156 MB  |   
 public | b19  | table | postgres | 156 MB  |   
 public | b2   | table | postgres | 156 MB  |   
 public | b20  | table | postgres | 156 MB  |   

5、vops(瓦片式存储)分片表并行聚合

create or replace function get_res_vops() returns setof record as $$    
declare    
begin    
  for i in 0..55 loop           
    perform conn('link'||i,  'hostaddr=127.0.0.1 port=1921 user=postgres dbname=postgres');           
    perform 1 from dblink_get_result('link'||i) as t(c1 int, cnt int8, aggs int8[]);          
    perform dblink_send_query('link'||i, format('select (reduce(map(c1, ''min,max,sum'', id,id,id))).* from b%s', i));          
  end loop;       
  for i in 0..55 loop    
    return query select * from dblink_get_result('link'||i) as t(c1 int, cnt int8, aggs int8[]);    
  end loop;    
end;    
$$ language plpgsql strict;    

6、查询耗时,1.97秒

select c1, sum(cnt), sum(aggs[3])/sum(cnt)::float8, min(aggs[1]), max(aggs[2]), sum(aggs[3]) from ( select * from get_res_vops() as t(c1 int, cnt int8, aggs int8[])) t group by c1;  
  
  
postgres=# select c1, sum(cnt), sum(aggs[3])/sum(cnt)::float8, min(aggs[1]), max(aggs[2]), sum(aggs[3]) from ( select * from get_res_vops() as t(c1 int, cnt int8, aggs int8[])) t group by c1;  
 c1 |   sum    |     ?column?     | min |    max    |       sum          
----+----------+------------------+-----+-----------+------------------  
  7 | 10104223 |  500196670.66755 |  13 | 999999922 | 5054098704282486  
 41 | 10098079 | 500105983.312797 |  75 | 999999899 | 5050109727865311  
 72 | 10099035 | 499987853.746656 |   3 | 999999917 | 5049394834562362  
  2 | 10098707 | 500027259.278005 | 119 | 999999881 | 5049628783461600  
 29 | 10101931 | 500172863.741008 |  16 | 999999911 | 5052711757584067  
 71 | 10099125 | 500129933.363706 |  51 | 999999877 | 5050874713281733  
  6 | 10104713 | 500020892.341227 |  20 | 999999943 | 5052567611111995  
 74 | 10098824 | 499966081.890066 | 170 | 999999890 | 5049069466977368  
 38 | 10103601 | 499961610.602928 |  89 | 999999949 | 5051412628849349  
 88 | 10103668 | 499850251.056789 |  64 | 999999780 | 5050320986394444  
 84 | 10105345 |  500042003.07277 | 271 | 999999895 | 5053096955541396  
 68 | 10098999 |   499977042.1773 |  59 | 999999857 | 5049267648971511  
 55 | 10103707 | 499960231.761415 |  45 | 999999850 | 5051451693369436  
 64 | 10102942 | 500113184.404115 |  47 | 999999693 | 5052614495470081  
 24 | 10099982 |  499936812.84724 | 190 | 999999901 | 5049352810894492  
  9 | 10104341 | 499996733.660471 |  23 | 999999915 | 5052137495791580  
 63 | 10102023 | 499895229.112864 | 353 | 999999910 | 5049953102088419  
 98 | 10097327 | 499944814.066904 |  22 | 999999919 | 5048106269587731  
 78 | 10107866 | 500012506.299485 |  69 | 999999740 | 5054059411999348  
 59 | 10099747 | 499892322.509487 |   2 | 999999808 | 5048785984588223  
 18 | 10101977 | 499926956.667668 |   4 | 999999897 | 5050250617936782  
 90 | 10096744 | 500199293.810021 |  43 | 999999875 | 5050384218580567  
 42 | 10101533 | 500126553.670129 |  12 | 999999865 | 5052044886075076  
 79 | 10098900 | 499957103.416255 | 114 | 999999846 | 5049016791690421  
 10 | 10095854 |  500035390.09691 |  17 | 999999719 | 5048284293251445  
 12 | 10105025 | 499832509.132034 | 109 | 999999799 | 5050820000591935  
 32 | 10099491 | 500129108.718979 |  84 | 999999914 | 5051049432345352  
 81 | 10106622 | 499963749.199852 | 229 | 999999944 | 5052944626865710  
 34 | 10099359 | 500111032.921868 |  52 | 999999836 | 5050800861338764  
 85 | 10103461 | 499947692.923157 |  18 | 999999904 | 5051202017489091  
 37 | 10099584 | 500057275.745026 | 104 | 999999849 | 5050370461198054  
 69 | 10097014 | 500143184.435491 |  91 | 999999720 | 5049952735249734  
 52 | 10101573 | 500040171.388144 | 355 | 999999932 | 5051192294209851  
 76 | 10101689 | 499896977.810699 | 438 | 999999843 | 5049803801883577  
 35 | 10099622 | 500114054.898034 |  44 | 999999747 | 5050962911357394  
 65 | 10103111 |  499851261.81228 |  48 | 999999726 | 5050052781579531  
 31 | 10099277 | 499845188.908577 | 112 | 999999838 | 5048075019905046  
 51 | 10099397 | 499984737.203741 |  65 | 999999933 | 5049544354961246  
 57 | 10103823 | 500008680.942373 | 100 | 999999925 | 5051999210705205  
 19 | 10102592 | 500036435.174349 |  81 | 999999939 | 5051664089700899  
 33 | 10096464 | 500058135.753455 |  66 | 999999773 | 5048818965541870  
  0 |  5048622 |  500110433.47565 | 263 | 999999912 | 2524868536874701  
 50 | 10099019 | 500071716.158314 | 177 | 999999894 | 5050233762845416  
 89 | 10102886 | 499906895.352583 |  21 | 999999941 | 5050502374361080  
 66 | 10100455 | 500019718.104865 |  11 | 999999889 | 5050426661830877  
 17 | 10099749 | 500020536.906571 | 125 | 999999900 | 5050081917601604  
 14 | 10097995 | 499872474.436678 |  50 | 999999887 | 5047709747499202  
 67 | 10105426 | 500125756.387578 | 245 | 999999866 | 5053983821868692  
 87 | 10100597 | 499967794.215203 |  14 | 999999907 | 5049973202346696  
 96 | 10099064 | 499905578.187197 | 243 | 999999892 | 5048578428069509  
 61 | 10100503 | 500007920.183475 |  28 | 999999903 | 5050331497836948  
  3 | 10101198 | 499940146.381583 |  30 | 999999883 | 5049994406749350  
 39 | 10098880 | 500243255.820608 |  32 | 999999920 | 5051896611341620  
 11 | 10101799 | 500096301.902747 | 129 | 999999916 | 5051872322464871  
 43 | 10107301 |  500040498.08918 | 163 | 999999842 | 5054059826377266  
  5 | 10100558 | 499863342.325278 |  31 | 999999940 | 5048898681230323  
 75 | 10101250 | 500037496.222365 |  63 | 999999928 | 5051003758716163  
 97 | 10103503 | 500029746.921376 | 123 | 999999921 | 5052052048109365  
 21 | 10102929 | 500098408.485223 | 446 | 999999926 | 5052458713939206  
 93 | 10105004 | 499972842.513604 |  25 | 999999852 | 5052227573491343  
 60 | 10105650 | 499950744.869079 | 209 | 999999873 | 5052327244886207  
 27 | 10102588 | 499797776.872304 |  41 | 999999858 | 5049251023056813  
 45 | 10100466 | 499847713.021728 |  38 | 999999841 | 5048694830553717  
 70 | 10103640 | 500126978.162685 | 238 | 999999801 | 5053102941643626  
 91 | 10102311 |    499764530.032 |   1 | 999999950 | 5048776709152101  
 22 | 10099804 | 500243130.452219 | 250 | 999999867 | 5052357569913843  
 49 | 10099635 | 500022230.537738 |  19 | 999999896 | 5050042020317004  
 13 | 10100454 | 499986238.143486 |  53 | 999999646 | 5050087999001322  
 86 | 10099751 |  499991374.31582 |   7 | 999999782 | 5049788382737577  
 26 | 10105606 | 500021405.572664 |   6 | 999999938 | 5053019316283545  
  1 | 10095409 | 500001476.917716 | 206 | 999999776 | 5047719410088402  
 58 | 10099972 | 499913934.276812 |  35 | 999999792 | 5049116738605642  
 25 | 10104666 | 500031883.894369 | 137 | 999999510 | 5052655176103381  
 82 | 10101286 | 499966805.257835 |  10 | 999999534 | 5050307690415695  
 44 | 10104380 | 499990027.500454 |   9 | 999999872 | 5052089234075034  
 20 | 10100166 | 500033955.063915 | 130 | 999999908 | 5050425951782085  
 23 | 10099118 | 500033099.525857 |  58 | 999999918 | 5049893276017372  
 92 | 10097628 | 499985682.503551 |  79 | 999999951 | 5048669427246965  
 62 | 10098974 |  500002801.70268 |  33 | 999999765 | 5049515294322520  
 53 | 10104969 | 500071097.824301 |   5 | 999999948 | 5053202941310532  
 56 | 10099521 |  499829373.88272 | 157 | 999999902 | 5048037257945384  
 40 | 10098880 |  500118160.98974 | 202 | 999999731 | 5050633293656069  
 73 | 10102325 | 499981690.451386 |  62 | 999999809 | 5050977530989301  
 95 | 10102589 | 499885307.442653 |  74 | 999999770 | 5050135808231760  
 30 | 10097653 | 499985894.883754 | 127 | 999999861 | 5048684071430626  
  4 | 10094812 | 499884810.734528 |  37 | 999999815 | 5046243186020638  
 77 | 10097737 | 500019227.640071 |  34 | 999999751 | 5049062655652572  
 15 | 10100451 | 499990119.574357 |  86 | 999999946 | 5050125703244929  
 94 | 10097423 | 500030504.883845 | 102 | 999999930 | 5049019520715746  
 36 | 10097433 | 499910715.309699 |  60 | 999999952 | 5047814953821765  
 83 | 10097518 | 499986390.218504 |   8 | 999999777 | 5048621574986367  
 28 | 10102778 | 499892202.902798 | 147 | 999999929 | 5050299949857921  
 48 | 10095113 | 500116265.596128 | 171 | 999999942 | 5048730214330929  
 99 |  5051395 | 499818438.433132 |  39 | 999999936 | 2524780360808931  
 46 | 10101708 | 499972043.149036 |  24 | 999999878 | 5050571588054961  
 47 | 10106118 | 500030970.343216 |  29 | 999999844 | 5053371989943041  
 54 | 10096312 |  500084305.08323 |  77 | 999999934 | 5049007170423474  
 16 | 10104458 | 500003081.506687 |  36 | 999999800 | 5052260136954892  
 80 | 10102160 | 499846266.993651 |  54 | 999999945 | 5049526964572583  
  8 | 10103060 | 500007130.726843 | 136 | 999999891 | 5051602042161142  
(100 rows)  
  
Time: 1972.137 ms (00:01.972)  

7、CPU资源使用

top - 16:27:44 up 30 days, 21:15,  2 users,  load average: 7.49, 6.21, 6.41  
Tasks: 522 total,  58 running, 464 sleeping,   0 stopped,   0 zombie  
%Cpu(s): 99.9 us,  0.1 sy,  0.0 ni,  0.0 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st  
KiB Mem : 23094336+total,  7251336 free,  7786940 used, 21590508+buff/cache  
KiB Swap:        0 total,        0 free,        0 used. 10075729+avail Mem  

普通单表10亿,HASH并行聚合

1、普通表并行聚合。

create unlogged table c(id int, c1 int);  
  
insert into c select * from a;  

2、空间占用,34GB

postgres=# \dt+ c  
                   List of relations  
 Schema | Name | Type  |  Owner   | Size  | Description   
--------+------+-------+----------+-------+-------------  
 public | c    | table | postgres | 34 GB |   
(1 row)  

3、并行度设置

set max_parallel_workers_per_gather =56;  
set min_parallel_table_scan_size =0;  
set min_parallel_index_scan_size =0;  
set parallel_tuple_cost =0;  
set parallel_setup_cost =0;  
  
alter table c set (parallel_workers =56);  
  
explain select c1, count(*), avg(id), min(id), max(id), sum(id) from c group by c1;  
  
postgres=# explain select c1, count(*), avg(id), min(id), max(id), sum(id) from c group by c1;  
                                          QUERY PLAN                                             
-----------------------------------------------------------------------------------------------  
 Finalize GroupAggregate  (cost=4871557.23..4871656.48 rows=100 width=60)  
   Group Key: c1  
   ->  Sort  (cost=4871557.23..4871571.23 rows=5600 width=60)  
         Sort Key: c1  
         ->  Gather  (cost=4871207.60..4871208.60 rows=5600 width=60)  
               Workers Planned: 56  
               ->  Partial HashAggregate  (cost=4871207.60..4871208.60 rows=100 width=60)  
                     Group Key: c1  
                     ->  Parallel Seq Scan on c  (cost=0.00..4603350.44 rows=17857144 width=8)  
(9 rows)  

4、聚合耗时,11.6秒

select c1, count(*), avg(id), min(id), max(id), sum(id) from c group by c1;  
  
postgres=# select c1, count(*), avg(id), min(id), max(id), sum(id) from c group by c1;  
 c1 |  count   |        avg         | min |    max    |       sum          
----+----------+--------------------+-----+-----------+------------------  
  0 |  5048622 | 500110433.47564959 | 263 | 999999912 | 2524868536874701  
  1 | 10095409 | 500001476.91771596 | 206 | 999999776 | 5047719410088402  
  2 | 10098707 | 500027259.27800460 | 119 | 999999881 | 5049628783461600  
  3 | 10101198 | 499940146.38158266 |  30 | 999999883 | 5049994406749350  
  4 | 10094812 | 499884810.73452760 |  37 | 999999815 | 5046243186020638  
  5 | 10100558 | 499863342.32527777 |  31 | 999999940 | 5048898681230323  
  6 | 10104713 | 500020892.34122681 |  20 | 999999943 | 5052567611111995  
  7 | 10104223 | 500196670.66755019 |  13 | 999999922 | 5054098704282486  
  8 | 10103060 | 500007130.72684335 | 136 | 999999891 | 5051602042161142  
  9 | 10104341 | 499996733.66047128 |  23 | 999999915 | 5052137495791580  
 10 | 10095854 | 500035390.09690958 |  17 | 999999719 | 5048284293251445  
 11 | 10101799 | 500096301.90274732 | 129 | 999999916 | 5051872322464871  
 12 | 10105025 | 499832509.13203431 | 109 | 999999799 | 5050820000591935  
 13 | 10100454 | 499986238.14348563 |  53 | 999999646 | 5050087999001322  
 14 | 10097995 | 499872474.43667797 |  50 | 999999887 | 5047709747499202  
 15 | 10100451 | 499990119.57435653 |  86 | 999999946 | 5050125703244929  
 16 | 10104458 | 500003081.50668665 |  36 | 999999800 | 5052260136954892  
 17 | 10099749 | 500020536.90657104 | 125 | 999999900 | 5050081917601604  
 18 | 10101977 | 499926956.66766832 |   4 | 999999897 | 5050250617936782  
 19 | 10102592 | 500036435.17434922 |  81 | 999999939 | 5051664089700899  
 20 | 10100166 | 500033955.06391529 | 130 | 999999908 | 5050425951782085  
 21 | 10102929 | 500098408.48522305 | 446 | 999999926 | 5052458713939206  
 22 | 10099804 | 500243130.45221897 | 250 | 999999867 | 5052357569913843  
 23 | 10099118 | 500033099.52585681 |  58 | 999999918 | 5049893276017372  
 24 | 10099982 | 499936812.84723993 | 190 | 999999901 | 5049352810894492  
 25 | 10104666 | 500031883.89436929 | 137 | 999999510 | 5052655176103381  
 26 | 10105606 | 500021405.57266383 |   6 | 999999938 | 5053019316283545  
 27 | 10102588 | 499797776.87230371 |  41 | 999999858 | 5049251023056813  
 28 | 10102778 | 499892202.90279773 | 147 | 999999929 | 5050299949857921  
 29 | 10101931 | 500172863.74100823 |  16 | 999999911 | 5052711757584067  
 30 | 10097653 | 499985894.88375427 | 127 | 999999861 | 5048684071430626  
 31 | 10099277 | 499845188.90857692 | 112 | 999999838 | 5048075019905046  
 32 | 10099491 | 500129108.71897920 |  84 | 999999914 | 5051049432345352  
 33 | 10096464 | 500058135.75345487 |  66 | 999999773 | 5048818965541870  
 34 | 10099359 | 500111032.92186801 |  52 | 999999836 | 5050800861338764  
 35 | 10099622 | 500114054.89803420 |  44 | 999999747 | 5050962911357394  
 36 | 10097433 | 499910715.30969950 |  60 | 999999952 | 5047814953821765  
 37 | 10099584 | 500057275.74502613 | 104 | 999999849 | 5050370461198054  
 38 | 10103601 | 499961610.60292751 |  89 | 999999949 | 5051412628849349  
 39 | 10098880 | 500243255.82060783 |  32 | 999999920 | 5051896611341620  
 40 | 10098880 | 500118160.98974035 | 202 | 999999731 | 5050633293656069  
 41 | 10098079 | 500105983.31279751 |  75 | 999999899 | 5050109727865311  
 42 | 10101533 | 500126553.67012868 |  12 | 999999865 | 5052044886075076  
 43 | 10107301 | 500040498.08917989 | 163 | 999999842 | 5054059826377266  
 44 | 10104380 | 499990027.50045366 |   9 | 999999872 | 5052089234075034  
 45 | 10100466 | 499847713.02172761 |  38 | 999999841 | 5048694830553717  
 46 | 10101708 | 499972043.14903589 |  24 | 999999878 | 5050571588054961  
 47 | 10106118 | 500030970.34321596 |  29 | 999999844 | 5053371989943041  
 48 | 10095113 | 500116265.59612844 | 171 | 999999942 | 5048730214330929  
 49 | 10099635 | 500022230.53773765 |  19 | 999999896 | 5050042020317004  
 50 | 10099019 | 500071716.15831359 | 177 | 999999894 | 5050233762845416  
 51 | 10099397 | 499984737.20374058 |  65 | 999999933 | 5049544354961246  
 52 | 10101573 | 500040171.38814430 | 355 | 999999932 | 5051192294209851  
 53 | 10104969 | 500071097.82430129 |   5 | 999999948 | 5053202941310532  
 54 | 10096312 | 500084305.08322980 |  77 | 999999934 | 5049007170423474  
 55 | 10103707 | 499960231.76141549 |  45 | 999999850 | 5051451693369436  
 56 | 10099521 | 499829373.88272018 | 157 | 999999902 | 5048037257945384  
 57 | 10103823 | 500008680.94237251 | 100 | 999999925 | 5051999210705205  
 58 | 10099972 | 499913934.27681205 |  35 | 999999792 | 5049116738605642  
 59 | 10099747 | 499892322.50948692 |   2 | 999999808 | 5048785984588223  
 60 | 10105650 | 499950744.86907888 | 209 | 999999873 | 5052327244886207  
 61 | 10100503 | 500007920.18347482 |  28 | 999999903 | 5050331497836948  
 62 | 10098974 | 500002801.70267990 |  33 | 999999765 | 5049515294322520  
 63 | 10102023 | 499895229.11286373 | 353 | 999999910 | 5049953102088419  
 64 | 10102942 | 500113184.40411526 |  47 | 999999693 | 5052614495470081  
 65 | 10103111 | 499851261.81228049 |  48 | 999999726 | 5050052781579531  
 66 | 10100455 | 500019718.10486528 |  11 | 999999889 | 5050426661830877  
 67 | 10105426 | 500125756.38757753 | 245 | 999999866 | 5053983821868692  
 68 | 10098999 | 499977042.17730005 |  59 | 999999857 | 5049267648971511  
 69 | 10097014 | 500143184.43549093 |  91 | 999999720 | 5049952735249734  
 70 | 10103640 | 500126978.16268454 | 238 | 999999801 | 5053102941643626  
 71 | 10099125 | 500129933.36370557 |  51 | 999999877 | 5050874713281733  
 72 | 10099035 | 499987853.74665619 |   3 | 999999917 | 5049394834562362  
 73 | 10102325 | 499981690.45138629 |  62 | 999999809 | 5050977530989301  
 74 | 10098824 | 499966081.89006641 | 170 | 999999890 | 5049069466977368  
 75 | 10101250 | 500037496.22236486 |  63 | 999999928 | 5051003758716163  
 76 | 10101689 | 499896977.81069849 | 438 | 999999843 | 5049803801883577  
 77 | 10097737 | 500019227.64007143 |  34 | 999999751 | 5049062655652572  
 78 | 10107866 | 500012506.29948478 |  69 | 999999740 | 5054059411999348  
 79 | 10098900 | 499957103.41625533 | 114 | 999999846 | 5049016791690421  
 80 | 10102160 | 499846266.99365116 |  54 | 999999945 | 5049526964572583  
 81 | 10106622 | 499963749.19985233 | 229 | 999999944 | 5052944626865710  
 82 | 10101286 | 499966805.25783499 |  10 | 999999534 | 5050307690415695  
 83 | 10097518 | 499986390.21850389 |   8 | 999999777 | 5048621574986367  
 84 | 10105345 | 500042003.07276951 | 271 | 999999895 | 5053096955541396  
 85 | 10103461 | 499947692.92315683 |  18 | 999999904 | 5051202017489091  
 86 | 10099751 | 499991374.31581996 |   7 | 999999782 | 5049788382737577  
 87 | 10100597 | 499967794.21520292 |  14 | 999999907 | 5049973202346696  
 88 | 10103668 | 499850251.05678888 |  64 | 999999780 | 5050320986394444  
 89 | 10102886 | 499906895.35258341 |  21 | 999999941 | 5050502374361080  
 90 | 10096744 | 500199293.81002103 |  43 | 999999875 | 5050384218580567  
 91 | 10102311 | 499764530.03199971 |   1 | 999999950 | 5048776709152101  
 92 | 10097628 | 499985682.50355083 |  79 | 999999951 | 5048669427246965  
 93 | 10105004 | 499972842.51360445 |  25 | 999999852 | 5052227573491343  
 94 | 10097423 | 500030504.88384472 | 102 | 999999930 | 5049019520715746  
 95 | 10102589 | 499885307.44265257 |  74 | 999999770 | 5050135808231760  
 96 | 10099064 | 499905578.18719725 | 243 | 999999892 | 5048578428069509  
 97 | 10103503 | 500029746.92137618 | 123 | 999999921 | 5052052048109365  
 98 | 10097327 | 499944814.06690414 |  22 | 999999919 | 5048106269587731  
 99 |  5051395 | 499818438.43313204 |  39 | 999999936 | 2524780360808931  
(100 rows)  
  
Time: 11585.315 ms (00:11.585)  

5、CPU消耗

top - 17:25:46 up 30 days, 22:13,  2 users,  load average: 4.78, 1.92, 2.38  
Tasks: 522 total,  58 running, 464 sleeping,   0 stopped,   0 zombie  
%Cpu(s): 96.1 us,  3.6 sy,  0.0 ni,  0.0 id,  0.3 wa,  0.0 hi,  0.0 si,  0.0 st  
KiB Mem : 23094336+total, 79267856 free,  2570612 used, 14910489+buff/cache  
KiB Swap:        0 total,        0 free,        0 used. 15125537+avail Mem  

小结

目前PostgreSQL已内置了并行计算的能力(透明和非透明)。结合列存+向量计算,PostgreSQL 统计分析能力到底能有多强?

本文以vops(向量计算) + 并行计算为例,演示了单实例PostgreSQL 10亿数据量的count,avg,min,max,sum查询,耗时不到2秒。

我们可以大胆的预见PostgreSQL结合列存、向量计算,OLAP能力会有多强。

数据量 硬件 CASE 优化方法 空间占用 耗时 CPU 利用率
10亿 56核虚拟机 10亿分组聚合求count,avg,min,max,sum 普通单表HASH并行聚合 34 GB 11.6 秒 100 %
10亿 56核虚拟机 10亿分组聚合求count,avg,min,max,sum 普通多表dblink异步调用并行聚合 34 GB 9.6 秒 100 %
10亿 56核虚拟机 10亿分组聚合求count,avg,min,max,sum vops瓦片式多表dblink异步调用并行聚合 8.7 GB 1.97 秒 100 %

参考

《PostgreSQL dblink异步调用实现 并行hash分片JOIN - 含数据交、并、差 提速案例 - 含dblink VS pg 11 parallel hash join VS pg 11 智能分区JOIN》

《PostgreSQL 11 preview - parallel hash (含hash JOIN , hash agg等) 性能极大提升》

《PostgreSQL 向量化执行插件(瓦片式实现) 10x提速OLAP》

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【随手记】MySQL窗口函数计算累加和
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