背景

使用 PostgreSQL 9.1，所以WITH ORDINAL（9.4 特性）不可用。

问题

希望简化旋转二维数组的代码。

代码

一个说明问题的工作，过于冗长的例子是：

SELECT
  u.aspect,
  u.preference
FROM (
  SELECT
    t.aspect_preference AS aspect,
    -- Skip every second row
    seq % 2 AS seq,
    lead( aspect_preference, 1 ) OVER (ORDER BY t.seq) AS preference
  FROM (
    SELECT
      unnest( '{ {"COLOUR_SCHEME", "RASPBERRY_BLISS"}, {"FONT", "TERMES_HEROS"}, {"LIST_LAYOUT", "BULLET_SNOWFLAKE"} }'::text[] ) aspect_preference,
      -- Maintain array order after unnesting to a result set
      generate_series( 1,
       (array_ndims( '{ {"COLOUR_SCHEME", "RASPBERRY_BLISS"}, {"FONT", "TERMES_HEROS"}, {"LIST_LAYOUT", "BULLET_SNOWFLAKE"} }'::text[] ) *
        array_length( '{ …

我有一个表定义为：

create table dummy (jdata jsonb);

我插入了以下两行：

insert into dummy values ('["dog","cat","elephant","waffle"]');
insert into dummy values ('[1,2,3,4]');

我正在尝试使用 jsonb?&运算符，它可以让您提出问题“所有这些键/元素字符串都存在吗？”

使用字符串字段的示例有效：

select * from dummy where jdata ?& array['cat','dog'];
            jdata                 
--------------------------------------
["dog", "cat", "elephant", "waffle"]
(1 row)

但是，尝试使用包含数字的数组来执行此操作是行不通的：

select * from dummy where jdata ?& array['1','2'];
  jdata 
  -------
(0 rows)

select * from dummy where jdata ?& array['1','2'];
 jdata 
 -------
 (0 rows)

select * from dummy where jdata ?& array[1,2];
ERROR:  operator does not exist: jsonb ?& integer[]
LINE …

是否可以通过索引删除 Postgres 数组元素？（使用 Postgres 9.3。）

我在文档（http://www.postgresql.org/docs/9.3/static/functions-array.html）中没有看到任何相关内容，但也许我还缺少其他功能？

使用 Postgres 9.4，我有兴趣拥有一个整数数组，例如user_ids_who_like并提供一个用户数组（例如user_ids_i_am_following）来对该交集进行排序。

就像是：

select * 
from items 
where [there is an intersection between 
       user_ids_who_like with user_ids_i_am_following] 
order by intersection(user_ids_who_like).count

是否可以通过数组交集进行分组和排序？

示例数据：

items
name          | user_ids_who_like
'birds'       | '{1,3,5,8}'
'planes'      | '{2,3,4,11}'
'spaceships'  | '{3,4,6}'

对于给定的user_ids_who_i_follow = [3,4,11]，我可以执行以下操作：

select * from items
where <user_ids_who_like intersects with user_ids_who_i_follow>
order by <count of that intersection>

想要的结果：

name          | user_ids_who_like  | count
'planes'      |  '{2,3,4,11}'      | 3
'spaceships'  |  '{3,4,6}'         | 2
'birds'       |  '{1,3,5,8}'       | 1 …

我正在处理启用了intarray扩展的 Postgres 9.4项目。我们有一个看起来像这样的表：

items
-------------------------------------
id    name                  tag_ids  
--------------------------------------
1     a car                 {1,4}
2     a room to rent        {1}
3     a boat                {1,2,4,11}
4     a wine                {2}
5     emily                 {3}

如果可能，我想对标签 ID 进行分组。就像获取具有tag_id“{1,2,4,11}”的所有元素的计数

tag_id  count
1       3
2       2
4       2
11      1

这可能吗？我会认为这样的交叉点：

select * from items where tag_ids && '{1,2,4,11}'

但我需要按交集结果内的数组元素进行分组。如果我按 tag_ids 分组，它只是唯一值。

我该怎么做？

Postgres 似乎对数组值进行了某种压缩。我有一个包含 210 万行的表，每个表都有 2 列 smallint 数组，全部填充了 1440 个值。大多数这些值是-32768。我很惊讶地看到整个表，大约 60 亿个 smallint，在磁盘上只有 540MB。我做了一个实验，看起来 Postgres 正在做某种压缩。

对于从 1 到 1000 的 1000 个 smallint，pg_column_size 返回 2048。1000 个 smallint 的数组，全部为 -32768，pg_column_size 返回 74。1000 个 smallint 的数组，交替 1 和 0，pg_column_size 返回 73。

这在任何地方都有记录吗？

CREATE TABLE testing (
  values smallint[]
);

SELECT pg_table_size('testing');

SELECT pg_column_size(testing.*) FROM testing
-- 1,2,3,...,1000
INSERT INTO testing VALUES(
'{1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326,327,328,329,330,331,332,333,334,335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359,360,361,362,363,364,365,366,367,368,369,370,371,372,373,374,375,376,377,378,379,380,381,382,383,384,385,386,387,388,389,390,391,392,393,394,395,396,397,398,399,400,401,402,403,404,405,406,407,408,409,410,411,412,413,414,415,416,417,418,419,420,421,422,423,424,425,426,427,428,429,430,431,432,433,434,435,436,437,438,439,440,441,442,443,444,445,446,447,448,449,450,451,452,453,454,455,456,457,458,459,460,461,462,463,464,465,466,467,468,469,470,471,472,473,474,475,476,477,478,479,480,481,482,483,484,485,486,487,488,489,490,491,492,493,494,495,496,497,498,499,500,501,502,503,504,505,506,507,508,509,510,511,512,513,514,515,516,517,518,519,520,521,522,523,524,525,526,527,528,529,530,531,532,533,534,535,536,537,538,539,540,541,542,543,544,545,546,547,548,549,550,551,552,553,554,555,556,557,558,559,560,561,562,563,564,565,566,567,568,569,570,571,572,573,574,575,576,577,578,579,580,581,582,583,584,585,586,587,588,589,590,591,592,593,594,595,596,597,598,599,600,601,602,603,604,605,606,607,608,609,610,611,612,613,614,615,616,617,618,619,620,621,622,623,624,625,626,627,628,629,630,631,632,633,634,635,636,637,638,639,640,641,642,643,644,645,646,647,648,649,650,651,652,653,654,655,656,657,658,659,660,661,662,663,664,665,666,667,668,669,670,671,672,673,674,675,676,677,678,679,680,681,682,683,684,685,686,687,688,689,690,691,692,693,694,695,696,697,698,699,700,701,702,703,704,705,706,707,708,709,710,711,712,713,714,715,716,717,718,719,720,721,722,723,724,725,726,727,728,729,730,731,732,733,734,735,736,737,738,739,740,741,742,743,744,745,746,747,748,749,750,751,752,753,754,755,756,757,758,759,760,761,762,763,764,765,766,767,768,769,770,771,772,773,774,775,776,777,778,779,780,781,782,783,784,785,786,787,788,789,790,791,792,793,794,795,796,797,798,799,800,801,802,803,804,805,806,807,808,809,810,811,812,813,814,815,816,817,818,819,820,821,822,823,824,825,826,827,828,829,830,831,832,833,834,835,836,837,838,839,840,841,842,843,844,845,846,847,848,849,850,851,852,853,854,855,856,857,858,859,860,861,862,863,864,865,866,867,868,869,870,871,872,873,874,875,876,877,878,879,880,881,882,883,884,885,886,887,888,889,890,891,892,893,894,895,896,897,898,899,900,901,902,903,904,905,906,907,908,909,910,911,912,913,914,915,916,917,918,919,920,921,922,923,924,925,926,927,928,929,930,931,932,933,934,935,936,937,938,939,940,941,942,943,944,945,946,947,948,949,950,951,952,953,954,955,956,957,958,959,960,961,962,963,964,965,966,967,968,969,970,971,972,973,974,975,976,977,978,979,980,981,982,983,984,985,986,987,988,989,990,991,992,993,994,995,996,997,998,999,1000}' );

SELECT pg_column_size(testing.*) FROM testing;
TRUNCATE TABLE testing;
-- 1000 identical values
INSERT INTO testing VALUES (
'{-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768,-32768}');

SELECT …

目前我有这个查询：

select 
    sum(case when my_table.property_type = 'FLAT' then my_table.price else 0 end) as Flat_Current_Asking_Price,
    sum(case when my_table.property_type_mapped = 'SEMIDETACHED' then my_table.price else 0 end) as Semidetached_Current_Asking_Price
from 
    my_table;

所以如果my_table有以下值：

property_type | price
--------------+-------
FLAT          | 5000
SEMIDETACHED  | 9000
FLAT          | 6000

查询将返回：

Flat_Current_Asking_Price | Semidetached_Current_Asking_Price
--------------------------+-----------------------------------
11000                     | 9000

如何替换将sum值累积到数组中以获取？

Flat_Current_Asking_Price | Semidetached_Current_Asking_Price
--------------------------+-----------------------------------
{5000, 6000}              | {9000}

我有一个包含类似于此对象的 json 数组的表：

id    |   record
____________________
name1 | [{"a":0, "b":x}, {"a":1, "b":y}, {"a":2, "b":z}, ...]

我想得到一个包含仅包含“a”值的 json 数组的表：

id    |   record
____________________
name1 | [0, 1, 2, ...]

我使用的是 PostgreSQL 11，所以最新的功能是可以接受的。

我正在尝试在 PostgreSQL 表中存储word/doc 嵌入的向量，并希望能够快速将具有最高余弦相似度的 N 行提取到给定的查询向量。我正在使用的向量是numpy.array长度为100 <= L <= 1000的浮点数。

我查看了相似度搜索cube模块，但它仅限于<= 100维的向量。我使用的嵌入将产生最少100 维且通常更高的向量（取决于训练 word2vec/doc2vec 模型时的设置）。

在 Postgres 中存储大维向量（numpy 浮点数组）并根据余弦相似度（或其他向量相似度度量）执行快速查找的最有效方法是什么？

给定一个数据集（GIN索引为values）：

key | values
-------------
 1  | {4,2,1}
 1  | {2,5}
 2  | {4,1,3}

我想聚合数组：

key | values
-------------
 1  | {4,2,1,5}
 2  | {4,1,3}

我的第一个想法不起作用：

SELECT key, array_agg(DISTINCT unnest(values)) AS values FROM data GROUP BY key

[0A000] 错误：聚合函数调用不能包含返回集合的函数调用
提示：您可以将返回集合的函数移动到 LATERAL FROM 项中。

不熟悉LATERAL FROM，对我来说如何实现所需的输出并不明显。