Ini mungkin tidak sepenuhnya pada topik, namun ini adalah hari yang lambat di sini.

Apakah ada metode yang lebih efisien untuk mendapatkan daftar angka dari 1 hingga 49 dengan kolom yang berisi kata-kata FIZZketika angka dapat dibagi secara merata dengan 3, BUZZketika angka dapat dibagi secara merata dengan 5, dan FIZZBUZZketika jumlahnya dapat dibagi secara merata oleh kedua 3 dan 5?

Upaya saya adalah (HATI-HATI, ini akan mengosongkan cache prosedur Anda, jadi JANGAN LARI PADA KOTAK PRODUKSI):

DBCC FREEPROCCACHE
GO
/*VARIANT1*/
;WITH t AS (
    SELECT RowNum = ROW_NUMBER() OVER (ORDER BY o.object_id)
    FROM sys.objects o
)
SELECT t.RowNum
    , CASE WHEN ((t.RowNum % 3) + (t.RowNum % 5)) = 0  THEN 'FIZZBUZZ' 
    ELSE 
        CASE WHEN t.RowNum % 3 = 0 THEN 'FIZZ' 
        ELSE 
            CASE WHEN t.RowNum % 5 = 0 THEN 'BUZZ' 
            ELSE '' 
            END 
        END 
    END
FROM t
WHERE t.RowNum < 50;
GO 100

/*VARIANT2*/
DECLARE @t TABLE
(
    Num INT NOT NULL PRIMARY KEY CLUSTERED
);
INSERT INTO @t (Num)
SELECT ROW_NUMBER() OVER (ORDER BY o.object_id)
FROM sys.objects o;

SELECT t.Num
    , CASE WHEN ((t.Num % 3) + (t.Num % 5)) = 0  THEN 'FIZZBUZZ' 
    ELSE 
        CASE WHEN t.Num % 3 = 0 THEN 'FIZZ' 
        ELSE 
            CASE WHEN t.Num % 5 = 0 THEN 'BUZZ' 
            ELSE '' 
            END 
        END 
    END
FROM @t t
WHERE t.Num < 50;
GO 100

SELECT CASE WHEN dest.text LIKE '%/*VARIANT1*/%' THEN 'VARIANT1' ELSE 'VARIANT2' END
    , MAX(deqs.execution_count)
    , SUM(deqs.total_worker_time)
    , AvgWorkerTime = SUM(deqs.total_worker_time) / MAX(deqs.execution_count)
FROM sys.dm_exec_query_stats deqs
CROSS APPLY sys.dm_exec_sql_text(deqs.sql_handle) dest
WHERE (dest.text LIKE '%/*VARIANT1*/%'
    OR dest.text LIKE '%/*VARIANT2*/%')
    AND dest.text NOT LIKE '%/*NOT_ME!*/%'
GROUP BY CASE WHEN dest.text LIKE '%/*VARIANT1*/%' THEN 'VARIANT1' ELSE 'VARIANT2' END
ORDER BY CASE WHEN dest.text LIKE '%/*VARIANT1*/%' THEN 'VARIANT1' ELSE 'VARIANT2' END
/*NOT_ME!*/;

Seperti yang disarankan oleh @AaronBertrand, saya telah memodifikasi upaya saya untuk menjalankan setiap set pernyataan masing-masing 100 kali, kemudian menunjukkan waktu yang direkam oleh SQL Server melalui sys.dm_exec_query_stats.

Hasil:

            Runs    total_time      average time
VARIANT1    100     42533           425
VARIANT2    100     138677          1386

Di bawah ini adalah solusi T-SQL yang menulis juta angka pertama ke tabel temp. Dibutuhkan sekitar 84 ms pada mesin saya. Kemacetan utama sedang menunggu pada kait NESTING_TRANSACTION_FULL dan CXPACKET, keduanya saya tidak tahu bagaimana cara mengatasi selain mengubah MAXDOP. Saya menginginkan rencana permintaan yang dapat memanfaatkan loop bersarang paralel dan paralelisme berbasis permintaan, yang berhasil saya dapatkan:

Kode ini agak panjang. Singkatnya, saya bergabung bersama dua tabel turunan dari 246 baris dan 271 baris dengan total 66666 baris. Baris-baris tersebut digabungkan ke tabel turunan 15 baris yang mengambil keuntungan dari fakta bahwa pola FIZZBUZZ diulang untuk setiap 15 baris. Sepuluh baris terakhir ditambahkan dengan a UNION ALL.

DROP TABLE IF EXISTS #t;

SELECT res.fizzbuzz INTO #t
FROM
(
VALUES
(0),
(15),
(30),
(45),
(60),
(75),
(90),
(105),
(120),
(135),
(150),
(165),
(180),
(195),
(210),
(225),
(240),
(255),
(270),
(285),
(300),
(315),
(330),
(345),
(360),
(375),
(390),
(405),
(420),
(435),
(450),
(465),
(480),
(495),
(510),
(525),
(540),
(555),
(570),
(585),
(600),
(615),
(630),
(645),
(660),
(675),
(690),
(705),
(720),
(735),
(750),
(765),
(780),
(795),
(810),
(825),
(840),
(855),
(870),
(885),
(900),
(915),
(930),
(945),
(960),
(975),
(990),
(1005),
(1020),
(1035),
(1050),
(1065),
(1080),
(1095),
(1110),
(1125),
(1140),
(1155),
(1170),
(1185),
(1200),
(1215),
(1230),
(1245),
(1260),
(1275),
(1290),
(1305),
(1320),
(1335),
(1350),
(1365),
(1380),
(1395),
(1410),
(1425),
(1440),
(1455),
(1470),
(1485),
(1500),
(1515),
(1530),
(1545),
(1560),
(1575),
(1590),
(1605),
(1620),
(1635),
(1650),
(1665),
(1680),
(1695),
(1710),
(1725),
(1740),
(1755),
(1770),
(1785),
(1800),
(1815),
(1830),
(1845),
(1860),
(1875),
(1890),
(1905),
(1920),
(1935),
(1950),
(1965),
(1980),
(1995),
(2010),
(2025),
(2040),
(2055),
(2070),
(2085),
(2100),
(2115),
(2130),
(2145),
(2160),
(2175),
(2190),
(2205),
(2220),
(2235),
(2250),
(2265),
(2280),
(2295),
(2310),
(2325),
(2340),
(2355),
(2370),
(2385),
(2400),
(2415),
(2430),
(2445),
(2460),
(2475),
(2490),
(2505),
(2520),
(2535),
(2550),
(2565),
(2580),
(2595),
(2610),
(2625),
(2640),
(2655),
(2670),
(2685),
(2700),
(2715),
(2730),
(2745),
(2760),
(2775),
(2790),
(2805),
(2820),
(2835),
(2850),
(2865),
(2880),
(2895),
(2910),
(2925),
(2940),
(2955),
(2970),
(2985),
(3000),
(3015),
(3030),
(3045),
(3060),
(3075),
(3090),
(3105),
(3120),
(3135),
(3150),
(3165),
(3180),
(3195),
(3210),
(3225),
(3240),
(3255),
(3270),
(3285),
(3300),
(3315),
(3330),
(3345),
(3360),
(3375),
(3390),
(3405),
(3420),
(3435),
(3450),
(3465),
(3480),
(3495),
(3510),
(3525),
(3540),
(3555),
(3570),
(3585),
(3600),
(3615),
(3630),
(3645),
(3660),
(3675)
) v246 (n)
CROSS JOIN 
(
VALUES
(0),
(15),
(30),
(45),
(60),
(75),
(90),
(105),
(120),
(135),
(150),
(165),
(180),
(195),
(210),
(225),
(240),
(255),
(270),
(285),
(300),
(315),
(330),
(345),
(360),
(375),
(390),
(405),
(420),
(435),
(450),
(465),
(480),
(495),
(510),
(525),
(540),
(555),
(570),
(585),
(600),
(615),
(630),
(645),
(660),
(675),
(690),
(705),
(720),
(735),
(750),
(765),
(780),
(795),
(810),
(825),
(840),
(855),
(870),
(885),
(900),
(915),
(930),
(945),
(960),
(975),
(990),
(1005),
(1020),
(1035),
(1050),
(1065),
(1080),
(1095),
(1110),
(1125),
(1140),
(1155),
(1170),
(1185),
(1200),
(1215),
(1230),
(1245),
(1260),
(1275),
(1290),
(1305),
(1320),
(1335),
(1350),
(1365),
(1380),
(1395),
(1410),
(1425),
(1440),
(1455),
(1470),
(1485),
(1500),
(1515),
(1530),
(1545),
(1560),
(1575),
(1590),
(1605),
(1620),
(1635),
(1650),
(1665),
(1680),
(1695),
(1710),
(1725),
(1740),
(1755),
(1770),
(1785),
(1800),
(1815),
(1830),
(1845),
(1860),
(1875),
(1890),
(1905),
(1920),
(1935),
(1950),
(1965),
(1980),
(1995),
(2010),
(2025),
(2040),
(2055),
(2070),
(2085),
(2100),
(2115),
(2130),
(2145),
(2160),
(2175),
(2190),
(2205),
(2220),
(2235),
(2250),
(2265),
(2280),
(2295),
(2310),
(2325),
(2340),
(2355),
(2370),
(2385),
(2400),
(2415),
(2430),
(2445),
(2460),
(2475),
(2490),
(2505),
(2520),
(2535),
(2550),
(2565),
(2580),
(2595),
(2610),
(2625),
(2640),
(2655),
(2670),
(2685),
(2700),
(2715),
(2730),
(2745),
(2760),
(2775),
(2790),
(2805),
(2820),
(2835),
(2850),
(2865),
(2880),
(2895),
(2910),
(2925),
(2940),
(2955),
(2970),
(2985),
(3000),
(3015),
(3030),
(3045),
(3060),
(3075),
(3090),
(3105),
(3120),
(3135),
(3150),
(3165),
(3180),
(3195),
(3210),
(3225),
(3240),
(3255),
(3270),
(3285),
(3300),
(3315),
(3330),
(3345),
(3360),
(3375),
(3390),
(3405),
(3420),
(3435),
(3450),
(3465),
(3480),
(3495),
(3510),
(3525),
(3540),
(3555),
(3570),
(3585),
(3600),
(3615),
(3630),
(3645),
(3660),
(3675),
(3690),
(3705),
(3720),
(3735),
(3750),
(3765),
(3780),
(3795),
(3810),
(3825),
(3840),
(3855),
(3870),
(3885),
(3900),
(3915),
(3930),
(3945),
(3960),
(3975),
(3990),
(4005),
(4020),
(4035),
(4050)
) v271 (n)
CROSS APPLY
(
VALUES
(CAST(v246.n * 271 + v271.n + 1 AS CHAR(8))),
(CAST(v246.n * 271 + v271.n + 2 AS CHAR(8))),
(CAST('FIZZ' AS CHAR(8))),
(CAST(v246.n * 271 + v271.n + 4 AS CHAR(8))),
(CAST('BUZZ' AS CHAR(8))),
(CAST('FIZZ' AS CHAR(8))),
(CAST(v246.n * 271 + v271.n + 7 AS CHAR(8))),
(CAST(v246.n * 271 + v271.n + 8 AS CHAR(8))),
(CAST('FIZZ' AS CHAR(8))),
(CAST('BUZZ' AS CHAR(8))),
(CAST(v246.n * 271 + v271.n + 11 AS CHAR(8))),
(CAST('FIZZ' AS CHAR(8))),
(CAST(v246.n * 271 + v271.n + 13 AS CHAR(8))),
(CAST(v246.n * 271 + v271.n + 14 AS CHAR(8))),
(CAST('FIZZBUZZ' AS CHAR(8)))
) res (fizzbuzz)

UNION ALL

SELECT v.fizzbuzz
FROM (
VALUES 
('999991'),
('999992'),
('FIZZ'),
('999994'),
('BUZZ'),
('FIZZ'),
('999997'),
('999998'),
('FIZZ'),
('BUZZ')
) v (fizzbuzz)

OPTION (MAXDOP 6, NO_PERFORMANCE_SPOOL);

Menggunakan tabel SQL Server 2014 yang dioptimalkan memori dan prosedur yang disusun secara asli:

-- Setup
CREATE DATABASE InMem;
GO
ALTER DATABASE InMem
ADD FILEGROUP FG1
CONTAINS MEMORY_OPTIMIZED_DATA;
GO
ALTER DATABASE InMem
ADD FILE 
(
    NAME = 'FN1', 
    -- Change to suit your system
    FILENAME = 'C:\Program Files\Microsoft SQL Server\MSSQL12.SQL2014\MSSQL\DATA\FN1.mod'
)
TO FILEGROUP FG1;
GO
USE InMem;
GO
CREATE TYPE dbo.FizzBuzzTableType AS TABLE 
(
    n integer NOT NULL INDEX i,
    FizzBuzz varchar(8) NOT NULL
) WITH (MEMORY_OPTIMIZED = ON);
GO

Prosedur asli:

CREATE PROCEDURE dbo.FizzBuzz
WITH 
    NATIVE_COMPILATION, 
    SCHEMABINDING, 
    EXECUTE AS OWNER
AS
BEGIN ATOMIC 
WITH 
(
    TRANSACTION ISOLATION LEVEL = SNAPSHOT, 
    LANGUAGE = N'english'
)   
    DECLARE @n AS dbo.FizzBuzzTableType;

    DECLARE @i integer = 1;
    WHILE @i < 50
    BEGIN
        IF @i % 15 = 0
        BEGIN
            INSERT @n (n, FizzBuzz) 
            VALUES (@i, 'FizzBuzz')
        END
        ELSE 
        BEGIN
            IF @i % 3 = 0
            BEGIN
                INSERT @n (n, FizzBuzz)
                VALUES (@i, 'Fizz')
            END
            ELSE 
            BEGIN
                IF @i % 5 = 0
                BEGIN
                    INSERT @n (n, FizzBuzz) 
                    VALUES (@i, 'Buzz')
                END
                ELSE
                BEGIN
                    INSERT @n (n, FizzBuzz) 
                    VALUES (@i, CONVERT(varchar(8), @i));
                END;
            END;
        END;

        SET @i += 1;
    END;

    SELECT
        N.n, 
        N.FizzBuzz
    FROM @n AS N
    ORDER BY
        N.n;
END;

Uji:

SET NOCOUNT ON;
PRINT SYSUTCDATETIME();
GO
DECLARE @T AS dbo.FizzBuzzTableType;

INSERT @T (n, FizzBuzz)
EXECUTE dbo.FizzBuzz;
GO 100

PRINT SYSUTCDATETIME();

Hasil khas:

-- 95ms for 100 iterations, < 1ms each
2014-12-31 10:07:13.7993355
Beginning execution loop
Batch execution completed 100 times.
2014-12-31 10:07:13.8943409

Ini menulis output prosedur ke variabel tabel dalam memori, karena jika tidak, kami hanya menguji kecepatan menampilkan hasil dalam SSMS.

Satu juta baris

Prosedur asli di atas membutuhkan waktu sekitar 12 detik untuk beroperasi pada 1.000.000 angka. Ada segala macam cara yang lebih cepat untuk melakukan hal yang sama di T-SQL. Yang saya tulis sebelumnya mengikuti. Ini berjalan di sekitar 500 ms di laptop saya pada satu juta baris ketika rencana paralel yang dimaksud tercapai:

IF  OBJECT_ID(N'tempdb..#Result', N'U') IS NOT NULL
    DROP TABLE #Result;

IF  OBJECT_ID(N'tempdb..#Thousand', N'U') IS NOT NULL
    DROP TABLE #Thousand;

SET NOCOUNT ON;
DECLARE @start datetime2(7) = SYSUTCDATETIME();

CREATE TABLE #Thousand 
(
    n integer NOT NULL,

    CONSTRAINT PK_#Thousand
    PRIMARY KEY CLUSTERED (n)
);

-- Add 1,000 rows numbered 0-999 to #Thousand
WITH 
    L1 (n) AS
(
    SELECT  V.n
    FROM    
    (
        VALUES  (0), (1), (2), (3), (4),
                (5), (6), (7), (8), (9)
    ) AS V (n)
),
    Thousand AS
(
    SELECT  n = 
        CONVERT
        (
            integer,
            ROW_NUMBER() OVER (
            ORDER BY (SELECT NULL))
            - 1
        )
    FROM L1
    CROSS JOIN L1 AS L2
    CROSS JOIN L1 AS L3
)
INSERT #Thousand (n)
SELECT n
FROM Thousand;

-- To hold the Fizz Buzz output
CREATE TABLE #Result 
(
    n integer NOT NULL, 
    result varchar(8) NOT NULL
);

INSERT #Result
SELECT 
    Million.n, 
    Million.result
FROM
(
    -- Modulo operation to encourage few outer rows parallelism
    SELECT  n
    FROM    #Thousand
    WHERE   n % 1 = 0
) AS T1
-- Outer Apply to keep the Compute Scalar parallel
OUTER APPLY
(
    SELECT
        F2.n, 
        F2.result
    FROM #Thousand AS T2
    CROSS APPLY
    (
        -- Row numbers 1 to 1,000,000
        SELECT  (T1.n * 1000) + T2.n + 1
    ) AS F1 (n)
    CROSS APPLY
    (
        -- The Fizz Buzz bit
        SELECT
            F1.n,
            result =
                CASE 
                    WHEN F1.n % 15 = 0 THEN 'FizzBuzz'
                    WHEN F1.n % 3 = 0 THEN 'Buzz'
                    WHEN F1.n % 5 = 0 THEN 'Fizz'
                    ELSE CONVERT(varchar(8), F1.n)
                END
    ) AS F2
) AS Million
OPTION  (MAXDOP 4, QUERYTRACEON 9481);

PRINT DATEDIFF(MILLISECOND, @start, SYSUTCDATETIME());

Yang ini berjalan sama di komputer saya dengan yang pertama Anda (0ms). Saya tidak yakin apakah itu akan skala lebih cepat atau tidak.

;WITH t AS (
    SELECT RowNum = ROW_NUMBER() OVER (ORDER BY o.object_id)
    FROM sys.objects o
)
SELECT t.RowNum
    , Cxa.Fizz + CxB.Buzz
FROM t
CROSS APPLY (SELECT CASE WHEN t.RowNum % 3 = 0 THEN 'FIZZ' ELSE '' END) CxA(Fizz)
CROSS APPLY (SELECT CASE WHEN t.RowNum % 5 = 0 THEN 'BUZZ' ELSE '' END) CxB(Buzz)
WHERE t.RowNum < 50;

Versi terbaik yang saya buat berjalan dalam 30 ms di komputer saya:

WITH t AS (
    SELECT 1 As RowNum
    Union ALL
    Select RowNum + 1
    From t
    Where RowNum < 49
)
SELECT t.RowNum
, SubString('FIZZ', (t.RowNum % 3)*10, 5) + SubString('BUZZ', (t.RowNum % 5)*10, 5)
FROM t;

Menurut sqlfiddle.com ini membutuhkan waktu 7 ms:

select coalesce(fizz + buzz, fizz, buzz, cast(n as varchar)) as FizzBuzz
  from (
    select n0 + 3 * n3 + 9 * n9 + 27 * n27 + 81 * n81 as n
        from
            (select 0 as n0  union all select 1 union all select 2 as n0)  as n0,
            (select 0 as n3  union all select 1 union all select 2 as n3)  as n3,
            (select 0 as n9  union all select 1 union all select 2 as n9)  as n9,
            (select 0 as n27 union all select 1 union all select 2 as n27) as n27,
            (select 0 as n81 union all select 1                    as n81) as n81
  ) as stupidalias1
  left outer join
    (select 3 as fizzstep, 'Fizz' as fizz) as stupidalias2 on n % fizzstep = 0
  left outer join
    (select 5 as buzzstep, 'Buzz' as buzz) as stupidalias3 on n % buzzstep = 0
  where n between 1 and 100
  order by n;

Tidak menggunakan tabel, procs tersimpan, atau CTE apa pun.

Saya mendapatkan versi yang masuk akal dari proc tersimpan yang dikompilasi secara asli dan bekerja untuk 1 juta baris dalam ~ 500-800ms. Ini adalah konversi T-SQL yang saya lakukan pada algoritma bitwise dari sini dengan sedikit bantuan dari blog Adam Machanic tentang operasi bitwise di sini .

Saya (mudah-mudahan) mengikuti aturan yang sama dengan proc 500ms / 1 juta baris @ PaulWhite, yaitu menghasilkan hasil tetapi tidak menampilkannya / tidak meneruskannya sebagai bagian dari pengaturan waktu. Itu harus menjadi indeks hash pada tabel di dalam memori untuk kecepatan dan ukuran bucket 4.194.304 atau 8.388.608 tampaknya menjadi titik manis bagi saya, meskipun jelas yang memberikan jumlah ember kosong yang tinggi.

USE hekatondb
GO

--NB: SQLCMD script, Enable via: Query menu > SQLCMD Mode
:setvar bucketCount 4194304
--:setvar bucketCount 8388608

IF OBJECT_ID('dbo.usp_hekatonFizzBuzz') IS NOT NULL
DROP PROC dbo.usp_hekatonFizzBuzz 
GO
IF OBJECT_ID('dbo.FizzBuzz') IS NOT NULL
DROP TABLE dbo.FizzBuzz
GO


IF OBJECT_ID('dbo.FizzBuzz') IS NULL
CREATE TABLE dbo.FizzBuzz (
    Number      INT NOT NULL,
    Result      VARCHAR(8) NULL,

    CONSTRAINT PK_FizzBuzz PRIMARY KEY NONCLUSTERED HASH ( Number ) WITH ( BUCKET_COUNT = $(bucketCount) )

) WITH ( MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_ONLY )
GO


CREATE PROC dbo.usp_hekatonFizzBuzz 

    @limit  INT

WITH
    NATIVE_COMPILATION, 
    SCHEMABINDING, 
    EXECUTE AS OWNER
AS
BEGIN ATOMIC
WITH
(
    TRANSACTION ISOLATION LEVEL = SNAPSHOT, 
    LANGUAGE = N'english'
)   

    DECLARE @acc INT = 810092048    -- 11 00 00 01 00 10 01 00 00 01 10 00 01 00 00
    DECLARE @i INT = 1
    DECLARE @c INT

    WHILE @i <= @limit
    BEGIN 

        SELECT
            @c = @acc & 3,
            @acc = ( @acc / 4 ) | ( @c * 268435456 )

        INSERT dbo.FizzBuzz ( Number, Result )
        SELECT @i, SUBSTRING( '       Fizz    Buzz    FizzBuzz', @c * 8, @c * 4 )

        SET @i += 1

    END

END
GO

DELETE dbo.FizzBuzz
DECLARE @startDate DATETIME2 = SYSUTCDATETIME();

EXEC dbo.usp_hekatonFizzBuzz 1000000

SELECT DATEDIFF( millisecond, @startDate, SYSUTCDATETIME() ) diff
GO 10

Saya menemukan dan bermain dengan sub pilih tunggal ini tanpa CTE. max_elapsed_time dalam statistik kueri menunjukkan 1036

 SELECT num,
        CASE    WHEN mod3 + mod5 = 0 THEN 'FizzBuzz'
                WHEN mod5 = 0 THEN 'Buzz'
                WHEN mod3 = 0 THEN 'Fizz'
                ELSE CONVERT(VARCHAR(8), num)
        END
 FROM 
 (
    SELECT  number as num,
            number % 3 AS mod3,
            number % 5 AS mod5
    FROM    master.dbo.spt_values
    WHERE   name IS NULL
            AND number BETWEEN 1 AND 101
 ) AS numbers;

Saya tidak mengambil kredit untuk kode yang ditulis, saya hanya ingin melihat berapa lama waktu yang diperlukan

SATU MILIAR BARIS!

;WITH T(N) AS (SELECT N FROM (VALUES (NULL),(NULL),(NULL),(NULL),(NULL),(NULL),(NULL),(NULL),(NULL),(NULL)) AS X(N))
    ,NUMS(N) AS (SELECT TOP(1000000000) ROW_NUMBER() OVER (ORDER BY (SELECT NULL))  AS N FROM T T1,T T2,T T3,T T4,T T5,T T6,T T7,T T8,T T9, T T10)
    SELECT  n, ca.fb
    INTO #fizzywizzy
    FROM    NUMS n
            CROSS APPLY ( SELECT    CASE WHEN n.N % 15 = 0 THEN 'FizzBuzz'
                                         WHEN n.N % 3 = 0 THEN 'Fizz'
                                         WHEN n.N % 5 = 0 THEN 'Buzz'
                                         ELSE CAST(n AS VARCHAR)
                                    END AS [fb]
                        ) ca

Jawabannya adalah: sekitar 10 menit.

SQL Server parse and compile time: 
   CPU time = 13 ms, elapsed time = 13 ms.

 SQL Server Execution Times:
   CPU time = 648625 ms,  elapsed time = 618025 ms.

PostgreSQL

PostgreSQL menyediakan generate_series, Tabel-Nilai Fungsi (Set-Returning Function) yang membuat ini lebih sederhana. Saya berasumsi Anda tidak ingin output apa pun ketika nomor tidak 3, atau 5 masuk ke dalamnya.

SELECT x, str
FROM generate_series(1,49) AS gs(x)
CROSS JOIN LATERAL (VALUES (CASE
  WHEN x % 15 =0 THEN 'Fizzbuzz'
  WHEN x % 3  =0 THEN 'Fizz'
  WHEN x % 5  =0 THEN 'Buzz'
END)) AS c(str)
WHERE str IS NOT NULL;