Isso pode não estar completamente no tópico, no entanto, é um dia lento aqui.

Existe um método mais eficiente de obter uma lista de números de 1 a 49 com uma coluna contendo as palavras FIZZquando o número pode ser dividido igualmente por 3, BUZZquando o número pode ser dividido por 5 e FIZZBUZZquando o número pode ser dividido igualmente por tanto 3 e 5?

Minhas tentativas são (CUIDADO, isso esvaziará o cache do procedimento, portanto NÃO EXECUTAR EM UMA CAIXA DE PRODUÇÃO):

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!*/;

Conforme recomendado por @AaronBertrand, modifiquei minhas tentativas de executar cada conjunto de instruções 100 vezes cada e depois mostrar os horários registrados pelo SQL Server sys.dm_exec_query_stats.

Os resultados:

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

Abaixo está uma solução T-SQL que grava o primeiro milhão de números em uma tabela temporária. Demora cerca de 84 ms na minha máquina. Os principais gargalos estão aguardando a trava NESTING_TRANSACTION_FULL e CXPACKET, os quais não sei como resolver além de mudar MAXDOP. Eu queria um plano de consulta que pudesse tirar proveito de loops aninhados paralelos e paralelismo baseado em demanda, que foi o que consegui obter:

O código é um pouco longo. Em resumo, uno duas tabelas derivadas de 246 linhas e 271 linhas, para um total de 66666 linhas. Essas linhas são unidas a uma tabela derivada de 15 linhas, que aproveita o fato de o padrão FIZZBUZZ ser repetido para cada 15 linhas. As dez linhas finais são adicionadas com 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);

Usando uma tabela otimizada de memória do SQL Server 2014 e um procedimento compilado nativamente:

-- 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

Procedimento nativo:

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;

Teste:

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

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

PRINT SYSUTCDATETIME();

Resultados típicos:

-- 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

Isso grava a saída do procedimento em uma variável da tabela na memória, porque, caso contrário, estamos apenas testando a velocidade de exibição dos resultados no SSMS.

Um milhão de linhas

O procedimento nativo acima leva cerca de 12 segundos para executar em 1.000.000 de números. Existem todos os tipos de maneiras mais rápidas de fazer a mesma coisa no T-SQL. Um que eu escrevi antes segue. Ele roda em cerca de 500 ms no meu laptop em um milhão de linhas quando o plano paralelo pretendido é alcançado:

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());

Este funciona da mesma forma na minha máquina que o seu primeiro (0 ms). Não tenho certeza se escalaria mais rápido ou não.

;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;

A melhor versão que eu criei é executada em 30ms na minha máquina:

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;

De acordo com sqlfiddle.com, são necessários 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;

Não usa tabelas, procs armazenados ou CTEs.

Eu obtive uma versão razoável do proc armazenado nativamente compilado, trabalhando por 1 milhão de linhas em ~ 500-800ms. Esta é uma conversão T-SQL que fiz do algoritmo bit a bit daqui com uma pequena ajuda do blog de Adam Machanic sobre operações bit a bit aqui .

Estou (espero) seguindo as mesmas regras do processo de 500ms / 1 milhão de linhas da @ PaulWhite, ou seja, gerando os resultados, mas não exibindo-os / não transmitindo-os como parte do tempo. Tem que haver índices de hash nas tabelas na memória para tamanhos de velocidade e de balde de 4.194.304 ou 8.388.608 pareceu ser o ponto ideal para mim, embora obviamente isso ofereça contagens altas de baldes vazios.

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

Eu encontrei e joguei com este único sub-select sem CTE. max_elapsed_time nas estatísticas da consulta mostra 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;

Não aceito o código conforme escrito, só queria ver quanto tempo levaria

UM BILHÃO DE LINHAS!

;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

A resposta é: cerca de 10 minutos.

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

O PostgreSQL fornece generate_seriesuma função de valor de tabela (função de retorno de conjunto) que torna isso substancialmente mais simples. Eu estou supondo que você não quer nada de saída quando o número nem 3, nem 5 entra nele.

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;