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因为线上数据库较大,通常我们可以通过数据采样来构建测试库。
数据采样除了需要对数据进行均匀的抽取之外,还可能有一种需求是对数据进行加密,例如需要隐藏或加密一些敏感字段的信息。
PostgreSQL 9.5开始支持tablesample的语法,参考如下
如果是以前的版本,则可以通过自定义函数来实现数据的采样。
9.5以前的PostgreSQL,通过函数达到采样目的。
1. 指定schema, tablename, 需要采样的记录数, 采样的离散度,返回符合要求的采样记录。
离散度取值范围0-100,可以理解为数据采样的覆盖范围。
代码如下
create or replace function samp_rows(nsp name, rel name, cnt int8, dist float8 default 100.0) returns setof record as $$declare pages int8; tups float8;begin if dist<0 or dist>100 then raise notice 'dist must between 0 and 100'; return; end if; select relpages,reltuples into pages,tups from pg_class where oid=(quote_ident(nsp)||'.'||quote_ident(rel))::regclass; if not found then return; end if; if cnt >= tups then -- 输入的采样记录数大于实际的记录数, 直接返回全表 -- ctid可以反映采样的随机度, 仅用于观察, 实际使用中可以不返回ctid return query execute 'select ctid, * from '||quote_ident(nsp)||'.'||quote_ident(rel)||' t limit '||cnt; else -- 如果采样的记录数小于实际的记录数,则根据随机数的概率来返回采样结果 cnt/tups 即全离散时的采样概率 -- 离散度0-100,越大表示采样的结果越离散,可以理解为随机采样时覆盖的数据面,0表示连续采样,100则表示在所有数据中随机采样。 if dist = 100.0 then return query execute 'select ctid, * from '||quote_ident(nsp)||'.'||quote_ident(rel)||' where random() <= '||cnt/tups||' limit '||cnt; elsif (dist/100.0) <= (cnt/tups) then return query execute 'select ctid, * from '||quote_ident(nsp)||'.'||quote_ident(rel)||' limit '||cnt; else return query execute 'select ctid, * from '||quote_ident(nsp)||'.'||quote_ident(rel)||' where random() <= '||(cnt/tups) * (100.0/dist)||' limit '||cnt; end if; end if; end;$$ language plpgsql strict;
因为用到了统计信息relpages和reltuples评估概率,所以表要有统计信息,通常PG会自动收集,不需要人工干预,只要打开了autovacuum即可。
测试
postgres=# create table test(id int, info text, crt_time timestamp);CREATE TABLETime: 2.522 mspostgres=# insert into test select generate_series(1,10000000), md5(random()::text), now();INSERT 0 10000000Time: 46274.872 ms
在全表范围随机采样10条记录
postgres=# select * from samp_rows('public', 'test', 10) as t(ctid tid, c1 int, c2 text, c3 timestamp); ctid | c1 | c2 | c3 ------------+---------+----------------------------------+---------------------------- (88846,70) | 9506592 | 83f2ed9c48f5c850a80b09219f8ef81d | 2016-09-29 23:59:20.619389 (2223,92) | 237953 | 2bd148a78ba8681150494f7beada073f | 2016-09-29 23:59:20.619389 (4675,95) | 500320 | 9588232acc62ce109ac91a28744ff75a | 2016-09-29 23:59:20.619389 (11396,86) | 1219458 | 38cb4f0b0f8e3c4d2c867c52aa9e9276 | 2016-09-29 23:59:20.619389 (12434,77) | 1330515 | d02e3b81543895f142f706b45589916c | 2016-09-29 23:59:20.619389 (20625,14) | 2206889 | 989f65dba839e3ad0d404b33b3dcbc54 | 2016-09-29 23:59:20.619389 (46954,59) | 5024137 | 71b84624b57271d224b368d141267f40 | 2016-09-29 23:59:20.619389 (50156,4) | 5366696 | fa96056fa5e8a914a999921d21f89c1d | 2016-09-29 23:59:20.619389 (50533,42) | 5407073 | 988dd648caabeb2bbdb9700ab4c39e85 | 2016-09-29 23:59:20.619389 (52526,59) | 5620341 | a02eb2e3499b985e719f61eb4f2d44f3 | 2016-09-29 23:59:20.619389(10 rows)Time: 997.933 ms
在20%的范围随机采样10条记录
postgres=# select * from samp_rows('public', 'test', 10, 20.0) as t(ctid tid, c1 int, c2 text, c3 timestamp); ctid | c1 | c2 | c3 ------------+---------+----------------------------------+---------------------------- (53248,74) | 5697610 | c833355249d72dd7c7679d1e857106ec | 2016-09-29 23:59:20.619389 (56404,63) | 6035291 | 0b43555f5e06684a546c61e04bf31ead | 2016-09-29 23:59:20.619389 (56643,61) | 6060862 | 205d8cead5fd828f4b7898c9533f057c | 2016-09-29 23:59:20.619389 (57482,15) | 6150589 | 88a6ea385f972745611fcc9a7ac63620 | 2016-09-29 23:59:20.619389 (63422,49) | 6786203 | f7615ebbecafa6e7f2590980e97dc21e | 2016-09-29 23:59:20.619389 (65723,98) | 7032459 | 1c7fc819d2990470608f24cfcf06f841 | 2016-09-29 23:59:20.619389 (73309,84) | 7844147 | 840dac30c69394c8faf1ce280cc26657 | 2016-09-29 23:59:20.619389 (73606,48) | 7875890 | 0115573ad12642d1a39a1e28a0c138a8 | 2016-09-29 23:59:20.619389 (75288,94) | 8055910 | f4cb320309a5abc29d5413c631643304 | 2016-09-29 23:59:20.619389 (76649,65) | 8201508 | 422364b88440b9ed38e4327080998f8b | 2016-09-29 23:59:20.619389(10 rows)Time: 383.163 ms
在1%的范围随机采样10条记录
postgres=# select * from samp_rows('public', 'test', 10, 1.0) as t(ctid tid, c1 int, c2 text, c3 timestamp); ctid | c1 | c2 | c3 ------------+---------+----------------------------------+---------------------------- (76660,85) | 8202705 | ecbbaeb19c9e223b18de807e3a891704 | 2016-09-29 23:59:20.619389 (76684,16) | 8205204 | a1a7c251d0751d0d40005a82af330357 | 2016-09-29 23:59:20.619389 (76703,42) | 8207263 | be9701285b99d2c76efe3362c27b7b4c | 2016-09-29 23:59:20.619389 (77124,49) | 8252317 | b9ddff0fb85b02e6b1eebfce7938a791 | 2016-09-29 23:59:20.619389 (77301,49) | 8271256 | 2b32b83b118fb8560d41d8841b7707ec | 2016-09-29 23:59:20.619389 (77321,44) | 8273391 | 844555ec12e0ff82581abd37302b851c | 2016-09-29 23:59:20.619389 (77390,99) | 8280829 | 4d84ac5f7b957e66f1d9a5c05411b064 | 2016-09-29 23:59:20.619389 (77464,97) | 8288745 | 66080fa16f99f27aa5392615371b8c10 | 2016-09-29 23:59:20.619389 (77534,88) | 8296226 | cfed15f4f05b1af7a4d92ddc759202b0 | 2016-09-29 23:59:20.619389 (77671,95) | 8310892 | 0070304cbe99722705a1b0c471c98132 | 2016-09-29 23:59:20.619389(10 rows)Time: 17.056 ms
离散达到目的,性能也达到目的。
接下来把ctid去掉即可。
create or replace function samp_rows(nsp name, rel name, cnt int8, dist float8 default 100.0) returns setof record as $$declare pages int8; tups float8;begin if dist<0 or dist>100 then raise notice 'dist must between 0 and 100'; return; end if; select relpages,reltuples into pages,tups from pg_class where oid=(quote_ident(nsp)||'.'||quote_ident(rel))::regclass; if not found then return; end if; if cnt >= tups then return query execute 'select * from '||quote_ident(nsp)||'.'||quote_ident(rel)||' t limit '||cnt; else -- 如果采样的记录数小于实际的记录数,则根据随机数的概率来返回采样结果 cnt/tups 即全离散时的采样概率 -- 离散度0-100,越大表示采样的结果越离散,可以理解为随机采样时覆盖的数据面,0表示连续采样,100则表示在所有数据中随机采样。 if dist = 100.0 then return query execute 'select * from '||quote_ident(nsp)||'.'||quote_ident(rel)||' where random() <= '||cnt/tups||' limit '||cnt; elsif (dist/100.0) <= (cnt/tups) then return query execute 'select * from '||quote_ident(nsp)||'.'||quote_ident(rel)||' limit '||cnt; else return query execute 'select * from '||quote_ident(nsp)||'.'||quote_ident(rel)||' where random() <= '||(cnt/tups) * (100.0/dist)||' limit '||cnt; end if; end if; end;$$ language plpgsql strict;
结果如下
postgres=# select * from samp_rows('public', 'test', 10, 1.0) as t(c1 int, c2 text, c3 timestamp); c1 | c2 | c3 ---------+----------------------------------+---------------------------- 8510389 | aa866b8fecfa5dc73e25df0eb8eb6e5d | 2016-09-29 23:59:20.619389 8511823 | 3f637e7b4c2dc3ca72dec979d25d8945 | 2016-09-29 23:59:20.619389 8542741 | 921dc72741ddcc5100a9204a9e1f67f2 | 2016-09-29 23:59:20.619389 8560000 | 150138e96c00557a2904293a461a6bb6 | 2016-09-29 23:59:20.619389 8571110 | 510bcdc6b4a3108cc7adc901a30932ed | 2016-09-29 23:59:20.619389 8583953 | 555afdc0ca25da10a1fe0c980d6505a5 | 2016-09-29 23:59:20.619389 8590392 | 03a3faf95d397784fa2c2aeccce296cc | 2016-09-29 23:59:20.619389 8601889 | ecab338c982818673b024f5299717c11 | 2016-09-29 23:59:20.619389 8603505 | c176f2e29c5fa0538054f2651cf9c4e3 | 2016-09-29 23:59:20.619389 8620874 | 75ca3ff98cc8040d6ca3f16b6402a5d0 | 2016-09-29 23:59:20.619389(10 rows)Time: 15.660 mspostgres=# select * from samp_rows('public', 'test', 10, 20.0) as t(c1 int, c2 text, c3 timestamp); c1 | c2 | c3 ---------+----------------------------------+---------------------------- 9217485 | dbe16993b20d736572a926bf1df05aea | 2016-09-29 23:59:20.619389 9327154 | cf6414a9a49f0fa41e0465fa2d015054 | 2016-09-29 23:59:20.619389 9664326 | 84c1f8ad26228c55b20085f80b2b3292 | 2016-09-29 23:59:20.619389 9667704 | 1da59e4572a09456408d65e7babbe8e4 | 2016-09-29 23:59:20.619389 221144 | 990aa3f26c8db1b8a9a48471a515b65f | 2016-09-29 23:59:20.619389 443124 | 974d539de407b7f4824510992cb71ef3 | 2016-09-29 23:59:20.619389 500254 | f8a70b3b0b2920618b17d63043444fbb | 2016-09-29 23:59:20.619389 952485 | bef93b6c48a2f74c7a7cde5af1153ccb | 2016-09-29 23:59:20.619389 1494854 | 7ed5e5873bcc7e4e12a6a424d39ac755 | 2016-09-29 23:59:20.619389 1557716 | 1c79f1f3d0026b47a7470d700cb0baad | 2016-09-29 23:59:20.619389(10 rows)
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