UPDATE CattleProds
SET SheepTherapy=(ROUND((RAND()* 10000),0))
WHERE SheepTherapy IS NULL
Answers:
代替rand()，使用newid()，对结果中的每一行都重新计算。通常的方法是使用校验和的模。请注意，这checksum(newid())可能产生-2,147,483,648并导致上的整数溢出abs()，因此我们需要在对校验和返回值进行模运算之前将其转换为绝对值。
UPDATE CattleProds
SET SheepTherapy = abs(checksum(NewId()) % 10000)
WHERE SheepTherapy IS NULL
这将生成一个介于0和9999之间的随机数。
如果您使用的是SQL Server 2008，也可以使用
CRYPT_GEN_RANDOM(2) % 10000
这似乎更简单（它也按行计算一次，newid如下所示）
DECLARE @foo TABLE (col1 FLOAT)
INSERT INTO @foo SELECT 1 UNION SELECT 2
UPDATE @foo
SET col1 = CRYPT_GEN_RANDOM(2) % 10000
SELECT * FROM @foo
返回值（2个随机的可能不同的数字）
col1
----------------------
9693
8573
考虑无法解释的下降投票，我能想到的唯一合理原因是，因为生成的随机数在0-65535之间，不能被10,000整除，所以有些数字会略有超出。一种解决方法是将其包装在标量UDF中，该标量UDF会丢弃超过60,000的任何数字，然后递归调用自身以获取替换数字。
CREATE FUNCTION dbo.RandomNumber()
RETURNS INT
AS
BEGIN
DECLARE @Result INT
SET @Result = CRYPT_GEN_RANDOM(2)
RETURN CASE
WHEN @Result < 60000
OR @@NESTLEVEL = 32 THEN @Result % 10000
ELSE dbo.RandomNumber()
END
END
虽然我确实喜欢使用CHECKSUM，但我觉得使用它是一种更好的方法NEWID()，因为您不必经过复杂的数学运算即可生成简单的数字。
ROUND( 1000 *RAND(convert(varbinary, newid())), 0)
您可以将1000您要设置为限制的数字替换为，并且始终可以使用加号来创建范围，例如，您想要在100和之间的随机数200，可以执行以下操作：
100 + ROUND( 100 *RAND(convert(varbinary, newid())), 0)
将其放到您的查询中：
UPDATE CattleProds
SET SheepTherapy= ROUND( 1000 *RAND(convert(varbinary, newid())), 0)
WHERE SheepTherapy IS NULL
我针对RAND（）测试了2种基于集合的随机方法，每个方法都产生了100,000,000行。为了平整该字段，输出是一个介于0-1之间的浮点，以模拟RAND（）。大多数代码正在测试基础结构，因此我在这里总结算法：
-- Try #1 used
(CAST(CRYPT_GEN_RANDOM(8) AS BIGINT)%500000000000000000+500000000000000000.0)/1000000000000000000 AS Val
-- Try #2 used
RAND(Checksum(NewId()))
-- and to have a baseline to compare output with I used
RAND() -- this required executing 100000000 separate insert statements
显然，使用CRYPT_GEN_RANDOM是最随机的，因为从一组10 ^ 18的数字中抽出10 ^ 8的数字时，甚至只有.000000001％的机会看到甚至1个重复项。哎呀，我们不应该看到任何重复的，而且没有！在我的笔记本电脑上生成此设置花了44秒钟。
Cnt Pct
----- ----
1 100.000000 --No duplicates
SQL Server执行时间：CPU时间= 134795毫秒，经过的时间= 39274毫秒。
IF OBJECT_ID('tempdb..#T0') IS NOT NULL DROP TABLE #T0;
GO
WITH L0 AS (SELECT c FROM (VALUES (1),(1),(1),(1),(1),(1),(1),(1),(1),(1),(1),(1),(1),(1),(1),(1)) AS D(c)) -- 2^4
,L1 AS (SELECT 1 AS c FROM L0 AS A CROSS JOIN L0 AS B) -- 2^8
,L2 AS (SELECT 1 AS c FROM L1 AS A CROSS JOIN L1 AS B) -- 2^16
,L3 AS (SELECT 1 AS c FROM L2 AS A CROSS JOIN L2 AS B) -- 2^32
SELECT TOP 100000000 (CAST(CRYPT_GEN_RANDOM(8) AS BIGINT)%500000000000000000+500000000000000000.0)/1000000000000000000 AS Val
INTO #T0
FROM L3;
WITH x AS (
SELECT Val,COUNT(*) Cnt
FROM #T0
GROUP BY Val
)
SELECT x.Cnt,COUNT(*)/(SELECT COUNT(*)/100 FROM #T0) Pct
FROM X
GROUP BY x.Cnt;
这种方法的随机性降低了近15个数量级，其速度并不快两倍，仅需23秒即可生成1亿个数字。
Cnt Pct
---- ----
1 95.450254 -- only 95% unique is absolutely horrible
2 02.222167 -- If this line were the only problem I'd say DON'T USE THIS!
3 00.034582
4 00.000409 -- 409 numbers appeared 4 times
5 00.000006 -- 6 numbers actually appeared 5 times
SQL Server执行时间：CPU时间= 77156 ms，经过的时间= 24613 ms。
IF OBJECT_ID('tempdb..#T1') IS NOT NULL DROP TABLE #T1;
GO
WITH L0 AS (SELECT c FROM (VALUES (1),(1),(1),(1),(1),(1),(1),(1),(1),(1),(1),(1),(1),(1),(1),(1)) AS D(c)) -- 2^4
,L1 AS (SELECT 1 AS c FROM L0 AS A CROSS JOIN L0 AS B) -- 2^8
,L2 AS (SELECT 1 AS c FROM L1 AS A CROSS JOIN L1 AS B) -- 2^16
,L3 AS (SELECT 1 AS c FROM L2 AS A CROSS JOIN L2 AS B) -- 2^32
SELECT TOP 100000000 RAND(Checksum(NewId())) AS Val
INTO #T1
FROM L3;
WITH x AS (
SELECT Val,COUNT(*) Cnt
FROM #T1
GROUP BY Val
)
SELECT x.Cnt,COUNT(*)*1.0/(SELECT COUNT(*)/100 FROM #T1) Pct
FROM X
GROUP BY x.Cnt;
RAND（）本身对于基于集合的生成毫无用处，因此生成用于比较随机性的基准要花费6个小时以上的时间，必须重新启动几次才能最终获得正确数量的输出行。看起来随机性还有很多需要改进的地方，尽管它比使用checksum（newid（））重新设定每行的种子更好。
Cnt Pct
---- ----
1 99.768020
2 00.115840
3 00.000100 -- at least there were comparitively few values returned 3 times
由于重新启动，无法捕获执行时间。
IF OBJECT_ID('tempdb..#T2') IS NOT NULL DROP TABLE #T2;
GO
CREATE TABLE #T2 (Val FLOAT);
GO
SET NOCOUNT ON;
GO
INSERT INTO #T2(Val) VALUES(RAND());
GO 100000000
WITH x AS (
SELECT Val,COUNT(*) Cnt
FROM #T2
GROUP BY Val
)
SELECT x.Cnt,COUNT(*)*1.0/(SELECT COUNT(*)/100 FROM #T2) Pct
FROM X
GROUP BY x.Cnt;
require_once('db/connect.php');
//rand(1000000 , 9999999);
$products_query = "SELECT id FROM products";
$products_result = mysqli_query($conn, $products_query);
$products_row = mysqli_fetch_array($products_result);
$ids_array = [];
do
{
array_push($ids_array, $products_row['id']);
}
while($products_row = mysqli_fetch_array($products_result));
/*
echo '<pre>';
print_r($ids_array);
echo '</pre>';
*/
$row_counter = count($ids_array);
for ($i=0; $i < $row_counter; $i++)
{
$current_row = $ids_array[$i];
$rand = rand(1000000 , 9999999);
mysqli_query($conn , "UPDATE products SET code='$rand' WHERE id='$current_row'");
}