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内存中列表的完全外部联接

haskell algorithm

-2

shayan · 技术社区 · 5 年前

如何在具有以下签名的列表上编写类似SQL的完全连接操作?

fullJoin :: [a] -> [b] -> (a -> b -> Bool) -> [(Maybe a, Maybe b)]
fullJoin xs [] _ = map (\x -> (Just x, Nothing)) xs
fullJoin [] ys _ = map (\y -> (Nothing, Just y)) ys
fullJoin xs@(xh:xt) ys@(yh:yt) on = 
  if on xh yh
    then (Just xh, Just yh) : fullJoin xt yt
    else ???

书面条件由 a -> b -> Bool (\n i -> length n == i) ,表示来自 names 它们的长度和 nums

例子:

names = ["Foo","Bar", "John" , "Emily", "Connor"]
nums = [1,2,3,4,5]

fullJoin names nums (\n i -> length n == i)
  == [ (Just "Foo", Just 3)
     , (Just "Bar", Just 3)
     , (Just "John", Just 4)
     , (Just "Emily", Just 5)
     , (Just "Connor", Nothing)
     , (Nothing, Just 1)
     , (Nothing, Just 2)
     ]

为了澄清上述函数的SQL等价物,下面是如何在PostgreSQL中编写它的:

create table names as
select * from (values 
               ('Foo'),
               ('Bar'),
               ('John'),
               ('Emily'),
               ('Connor')
              ) 
              as z(name);

create table nums as
select * from (values 
               (1),
               (2),
               (3),
               (4),
               (5)
              ) 
              as z(num);

select * from names
full join nums
on char_length(name) = num

name    num
(null)  1
(null)  2
Foo     3
Bar     3
John    4
Emily   5
Connor  (null)

小提琴链接: sqlfiddle

0 回复 | 直到 5 年前

1

2

Will Ness Derri Leahy 5 年前

只是无聊地实现你想要它做的事情。超低效率:

fullJoin :: [a] -> [b] -> (a -> b -> Bool) 
         -> [(Maybe a, Maybe b)]
fullJoin xs ys p = concatMap (map (Just *** Just) . snd) a
                    ++ [(Just x, Nothing) | (x, []) <- a]
                    ++ [(Nothing, Just y) | (y, []) <- b]
  where
    a = [(x, [(x, y) | y <- ys, p x y]) | x <- xs]
    b = [(y, [(x, y) | x <- xs, p x y]) | y <- ys]

如果我们被允许添加 Eq a 和 b 类型,我们可以用 Data.List.\\ 找到不匹配的元素而不是进行第二次扫描。

测试:

> mapM_ print $ fullJoin names nums (\n i -> length n == i)
(Just "Foo",Just 3)
(Just "Bar",Just 3)
(Just "John",Just 4)
(Just "Emily",Just 5)
(Just "Connor",Nothing)
(Nothing,Just 1)
(Nothing,Just 2)

2

Fried Brice 5 年前

表之间的完全外部联接 X Y 有条件的 rel(x, y) 可以认为是三个部分(不相交)的结合:

(x, y) 哪里 rel(x,y)
一对 (x0, null) y in Y , not (rel(x0, y))
一对 (null, y0) x in X , not (rel(x, y0))

我们可以用类似的方式构造Haskell程序:

fullJoin :: [a] -> [b] -> (a -> b -> Bool) -> [(Maybe a, Maybe b)]
fullJoin xs ys rel = concat $
  [[(Just x, Just y) | y <- ys, x `rel` y] | x <- xs] -- for each x, find all the related ys
  <> [[(Just x, Nothing)] | x <- xs, all (\y -> not (x `rel` y)) ys] -- find all xs that have no related ys
  <> [[(Nothing, Just y)] | y <- ys, all (\x -> not (x `rel` y)) xs] -- find all ys that have no related xs

问题的提出,你不可能比 O(n^2) . 也就是说,我的解决方案 O(n^2) xs 两次。你可以想一想你必须做些什么,这样你才能一次。这与找到一种方法来跟踪 xs型

3

1

btilly 5 年前

这是一个简单的Python实现。它是 O(n^2)

#! /usr/bin/env python

def full_join_cond (list1, list2, condition_fn):
    answer = []
    for x in list1:
        matches = []
        for y in list2:
            if condition_fn(x, y):
                matches.append(y)
        if len(matches):
            answer.extend([[x, y] for y in matches])
        else:
            answer.append([x, None])

    for y in list2:
        matched = False
        for x in list1:
            if condition_fn(x, y):
                matched = True
                break
        if not matched:
            answer.append([None, y])

    return answer


names = ["Foo","Bar", "John" , "Emily", "Connor"]
nums = [1,2,3,4,5]
cond = lambda x, y: len(x) == y

print(full_join_cond(names, nums, cond))

这里有一个实现,它更接近于数据库执行这个连接的方式。它是 O(size_of_output) 通常是 O(n)

def list_map_to_dict (l, m):
    d = {}
    for x in l:
        mx = m(x)
        if mx in d:
            d[mx].append(x)
        else:
            d[mx] = [x]
    return d

def full_join_map (list1, map1, list2, map2):
    dict1 = list_map_to_dict(list1, map1)
    dict2 = list_map_to_dict(list2, map2)

    answer = []
    for mx, xs in dict1.iteritems():
        if mx in dict2:
            for y in dict2[mx]:
                answer.extend([[x, y] for x in xs])
            dict2.pop(mx)
        else:
            answer.extend([[x, None] for x in xs])

    for my, ys in dict2.iteritems():
        answer.extend([[None, y] for y in ys])
    return answer

print(full_join_map(names, lambda x: len(x), nums, lambda y: y))

对于咯咯笑和咧嘴笑,两者可以组合成一个既通用又能快速运行的函数。(我并没有试图使函数签名合理化——只是试图展示这个想法。)

def full_join (list1, map1, list2, map2, cond=None):
    if map1 is None:
        map1 = lambda x: None

    if map2 is None:
        map2 = lambda y: None

    if cond is None:
        cond = lambda x, y: True

    dict1 = list_map_to_dict(list1, map1)
    dict2 = list_map_to_dict(list2, map2)

    answer = []
    for mx, xs in dict1.iteritems():
        if mx in dict2:
            answer.extend(full_join_cond(xs, dict2[mx], cond))
            dict2.pop(mx)
        else:
            answer.extend([[x, None] for x in xs])

    for my, ys in dict2.iteritems():
        answer.extend([[None, y] for y in ys])
    return answer