FP大串燒：SQL，LINQ，F#以及STL（2）

最後更新：2018-12-05 來源：互聯網

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文章目錄

Aggregate(Count)
彙總（計數）
Aggregate(Sum)
彙總（求和）
Aggregate(Min)
彙總（求最小值）
Aggregate(Max)
彙總（求最大值）
Aggregate(Average)
彙總（求平均值）
Aggregate(Simple)
簡單彙總
Aggregate(Seed)
帶種子的彙總

Aggregate(Count)彙總（計數）

計數操作用於統計原創組合中符合某種條件的成員的個數，結果值為整數。
計數操作在各語言中的實現方式如下表所示：

	Count
SQL(SELECT)	COUNT函數
C#(LINQ)	Count擴充方法
F#(List)	由List.filter和List.Length函數聯合實現
C++(STL)	count, count_if等演算法函數
Haskell(Prelude)	由filter和length函數聯合實現

以下範例程式碼功能為：統計整形集合numbers中奇數成員的個數。

SQL(SELECT)

TABLE(INPUT): NUMBERS FIELD DATA NUM 5, 4, 1, 3, 9, 8, 6, 7, 2, 0SELECT COUNT(*) AS ODDNUMBERS INTO RESULT FROM NUMBERS WHERE NUM MOD 2 = 1TABLE(OUTPUT): RESULT FIELD DATA ODDNUMBERS 5

C#(LINQ)int[] numbers = {5, 4, 1, 3, 9, 8, 6, 7, 2, 0}; int oddNumbers = numbers.Count(n => n % 2 == 1); // oddNumbers = 5
F#(List)

let numbers = [5; 4; 1; 3; 9; 8; 6; 7; 2; 0] let oddNumbers = numbers |> List.filter (fun num -> num % 2 = 1) |> List.length // oddNumbers = 5

STL(C++)

int numbers[] = {5, 4, 1, 3, 9, 8, 6, 7, 2, 0}; int oddNumbers = count_if(numbers, numbers + 10, [](int num){return num % 2 == 1;}); // oddNumbers = 5

Haskell(Prelude)

Prelude> let numbers = [5, 4, 1, 3, 9, 8, 6, 7, 2, 0] Prelude> let count f = length . filter f Prelude> let oddNumbers = count (/n -> n `mod` 2 == 1) numbers Prelude> oddNumbers 5

Aggregate(Sum)彙總（求和）

求和操作用於計算原創組合中各成員的總和，結果類型與原創組合成員類型相同。
求和操作在各語言中的實現方式如下表所示：

	Sum
SQL(SELECT)	SUM函數
C#(LINQ)	Sum擴充方法
F#(List)	List.sum, List.sumBy等函數
C++(STL)	accumulate演算法函數
Haskell(Prelude)	sum函數

以下範例程式碼功能為：計算整形集合numbers中各成員的總和。

SQL(SELECT)

TABLE(INPUT): NUMBERS FIELD DATA NUM 5, 4, 1, 3, 9, 8, 6, 7, 2, 0SELECT SUM(NUM) AS NUMSUM INTO RESULT FROM NUMBERSTABLE(OUTPUT): RESULT FIELD DATA NUMSUM 45

C#(LINQ)int[] numbers = {5, 4, 1, 3, 9, 8, 6, 7, 2, 0}; double numSum = numbers.Sum(); // numSum = 45
F#(List)

let numbers = [5; 4; 1; 3; 9; 8; 6; 7; 2; 0] let numSum = List.sum numbers // numSum = 45

STL(C++)

int numbers[] = {5, 4, 1, 3, 9, 8, 6, 7, 2, 0}; int numSum = accumulate(numbers, numbers + 10, 0, [](int acc, int num){return acc + num;}); // numSum = 45

Haskell(Prelude)

Prelude> let numbers = [5, 4, 1, 3, 9, 8, 6, 7, 2, 0] Prelude> let numSum = sum numbers Prelude> numSum 45

Aggregate(Min)彙總（求最小值）

求最小值操作用於找出原創組合中最小的成員，結果類型與原創組合成員類型相同。
求最小值操作在各語言中的實現方式如下表所示：

	Min
SQL(SELECT)	MIN函數
C#(LINQ)	Min擴充方法
F#(List)	List.min, List.minBy等函數
C++(STL)	min_element演算法函數
Haskell(Prelude)	minimum, minimumBy等函數

以下範例程式碼功能為：找出整形集合numbers中最小的成員。

SQL(SELECT)

TABLE(INPUT): NUMBERS FIELD DATA NUM 5, 4, 1, 3, 9, 8, 6, 7, 2, 0SELECT MIN(NUM) AS MINNUM INTO RESULT FROM NUMBERSTABLE(OUTPUT): RESULT FIELD DATA MINNUM 0

C#(LINQ)int[] numbers = {5, 4, 1, 3, 9, 8, 6, 7, 2, 0}; int minNum = numbers.Min(); // minNum = 0
F#(List)

let numbers = [5; 4; 1; 3; 9; 8; 6; 7; 2; 0] let minNum = List.min numbers // minNum = 0

STL(C++)

int numbers[] = {5, 4, 1, 3, 9, 8, 6, 7, 2, 0}; int minNum = *min_element(numbers, numbers + 10); // minNum = 0

Haskell(Prelude)

Prelude> let numbers = [5, 4, 1, 3, 9, 8, 6, 7, 2, 0] Prelude> let minNum = minimum numbers Prelude> minNum 0

Aggregate(Max)彙總（求最大值）

求最大值操作用於找出原創組合中最大的成員，結果類型與原創組合成員類型相同。
求最大值操作在各語言中的實現方式如下表所示：

	Max
SQL(SELECT)	MAX函數
C#(LINQ)	Max擴充方法
F#(List)	List.max, List.maxBy等函數
C++(STL)	max_element演算法函數
Haskell(Prelude)	maximum, maximumBy等函數

以下範例程式碼功能為：找出整形集合numbers中最大的成員。

SQL(SELECT)

TABLE(INPUT): NUMBERS FIELD DATA NUM 5, 4, 1, 3, 9, 8, 6, 7, 2, 0SELECT MAX(NUM) AS MAXNUM INTO RESULT FROM NUMBERSTABLE(OUTPUT): RESULT FIELD DATA MAXNUM 9

C#(LINQ)int[] numbers = {5, 4, 1, 3, 9, 8, 6, 7, 2, 0}; int maxNum = numbers.Max(); // maxNum = 9
F#(List)

let numbers = [5; 4; 1; 3; 9; 8; 6; 7; 2; 0] let maxNum = List.max numbers // maxNum = 9

STL(C++)

int numbers[] = {5, 4, 1, 3, 9, 8, 6, 7, 2, 0}; int maxNum = *max_element(numbers, numbers + 10); // maxNum = 9

Haskell(Prelude)

Prelude> let numbers = [5, 4, 1, 3, 9, 8, 6, 7, 2, 0] Prelude> let maxNum = maximum numbers Prelude> maxNum 9

Aggregate(Average)彙總（求平均值）

求平均值操作用於計算原創組合中各成員的平均值，結果類型與原創組合成員類型相同。
求平均值操作在各語言中的實現方式如下表所示：

	Average
SQL(SELECT)	AVG函數
C#(LINQ)	Average擴充方法
F#(List)	List.average, List.averageBy等函數
C++(STL)	無對應演算法函數，由accumulate演算法函數間接實現
Haskell(Prelude)	由sum和length函數聯合實現

以下範例程式碼功能為：計算整形集合numbers中各成員的平均值。

SQL(SELECT)

TABLE(INPUT): NUMBERS FIELD DATA NUM 5, 4, 1, 3, 9, 8, 6, 7, 2, 0SELECT AVG(NUM) AS AVERAGENUM INTO RESULT FROM NUMBERSTABLE(OUTPUT): RESULT FIELD DATA AVERAGENUM 4.5

C#(LINQ)int[] numbers = {5, 4, 1, 3, 9, 8, 6, 7, 2, 0}; double averageNum = numbers.Average(); // averageNum = 4.5
F#(List)

let numbers = [5.; 4.; 1.; 3.; 9.; 8.; 6.; 7.; 2.; 0.] let averageNum = List.average numbers // averageNum = 4.5

STL(C++)

int numbers[] = {5, 4, 1, 3, 9, 8, 6, 7, 2, 0}; double averageNum = accumulate(numbers, numbers + 10, 0, [](int acc, int num){return acc + num;}) / 10.; // averageNum = 4.5

Haskell(Prelude)

Prelude> let numbers = [5, 4, 1, 3, 9, 8, 6, 7, 2, 0] Prelude> let averageNum = fromIntegral (sum numbers) / fromIntegral (length numbers) Prelude> averageNum 4.5

Aggregate(Simple)簡單彙總

簡單彙總操作。
簡單彙總操作在各語言中的實現方式如下表所示：

	Aggregate(Simple)
SQL(SELECT)	無對應函數
C#(LINQ)	Aggregate擴充方法
F#(List)	List.reduce, List.reduceBack等函數
C++(STL)	accumulate演算法函數
Haskell(Prelude)	foldl1, foldr1等函數

以下範例程式碼功能為：計算雙精確度浮點數集合doubles中所有成員的積。

SQL(SELECT)
C#(LINQ)double[] doubles = {1.7, 2.3, 1.9, 4.1, 2.9}; double product = doubles.Aggregate((runningProduct, nextFactor) => runningProduct * nextFactor); // product = 88.330809999999985
F#(List)

let doubles = [1.7; 2.3; 1.9; 4.1; 2.9] let product = List.reduce (fun runningProduct nextFactor -> runningProduct * nextFactor) doubles // product = 88.33081

C++(STL)

double doubles[] = {1.7, 2.3, 1.9, 4.1, 2.9}; double product = accumulate(doubles + 1, doubles + 5, doubles[0], [](double runningProduct, double nextFactor){return runningProduct * nextFactor;}); // product = 88.330809999999985

Haskell(Prelude)

Prelude> let doubles = [1.7, 2.3, 1.9, 4.1, 2.9] Prelude> let productOfDoubles = foldl1 (/runningProduct nextFactor -> runningProduct * nextFactor) doubles Prelude> productOfDoubles 88.33080999999999

Aggregate(Seed)帶種子的彙總

帶種子的彙總操作。
帶種子的彙總操作在各語言中的實現方式如下表所示：

	Aggregate(Simple)
SQL(SELECT)	無對應函數
C#(LINQ)	Aggregate擴充方法
F#(List)	List.fold, List.foldBack等函數
C++(STL)	accumulate演算法函數
Haskell(Prelude)	foldl, foldr等函數

以下範例程式碼功能為：從賬戶中扣除提款額（忽略大於存款的提款項目），計算賬戶餘額。

SQL(SELECT)

C#(LINQ)double startBalance = 100.0; int[] attemptedWithdrawals = { 20, 10, 40, 50, 10, 70, 30 }; double endBalance = attemptedWithdrawals.Aggregate(startBalance, (balance, nextWithdrawal) => ((nextWithdrawal <= balance) ? (balance - nextWithdrawal) : balance)); // endBalance = 20.0
F#(List)

let startBalance = 100.0 let attemptedWithdrawals = [20; 10; 40; 50; 10; 70; 30] let endBalance = List.fold (fun balance nextWithdrawal2 -> let nextWithdrawal = float nextWithdrawal2 if nextWithdrawal <= balance then balance - nextWithdrawal else balance) startBalance attemptedWithdrawals // endBalance = 20.0

C++(STL)

double startBalance = 100.0; int attemptedWithdrawals[] = {20, 10, 40, 50, 10, 70, 30}; double endBalance = accumulate(attemptedWithdrawals, attemptedWithdrawals + 7, startBalance, [](double balance, int nextWithdrawal){ return ((nextWithdrawal <= balance) ? (balance - nextWithdrawal) : balance);}); // endBalance = 20.000000000000000

Haskell(Prelude)

Prelude> let startBalance = 100.0 Prelude> let attemptedWithdrawals = [20, 10, 40, 50, 10, 70, 30] Prelude> let endBalance = foldl (/ balance nextWithdrawal2 -> let nextWithdrawal = fromIntegral nextWithdrawal2 in if nextWithdrawal <= balance then balance - nextWithdrawal else balance) startBalance attemptedWithdrawals Prelude> endBalance 20.0

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FP大串燒：SQL，LINQ，F#以及STL（2）

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