Select n random rows from SQL Server table

select top 10 percent * from [yourtable] order by newid()

In response to the "pure trash" comment concerning large tables: you could do it like this to improve performance.

select  * from [yourtable] where [yourPk] in 
(select top 10 percent [yourPk] from [yourtable] order by newid())

The cost of this will be the key scan of values plus the join cost, which on a large table with a small percentage selection should be reasonable.

Depending on your needs, TABLESAMPLE will get you nearly as random and better performance. this is available on MS SQL server 2005 and later.

TABLESAMPLE will return data from random pages instead of random rows and therefore deos not even retrieve data that it will not return.

On a very large table I tested

select top 1 percent * from [tablename] order by newid()

took more than 20 minutes.

select * from [tablename] tablesample(1 percent)

took 2 minutes.

Performance will also improve on smaller samples in TABLESAMPLE whereas it will not with newid().

Please keep in mind that this is not as random as the newid() method but will give you a decent sampling.

See the MSDN page.

newid()/order by will work, but will be very expensive for large result sets because it has to generate an id for every row, and then sort them.

TABLESAMPLE() is good from a performance standpoint, but you will get clumping of results (all rows on a page will be returned).

For a better performing true random sample, the best way is to filter out rows randomly. I found the following code sample in the SQL Server Books Online article Limiting Results Sets by Using TABLESAMPLE:

If you really want a random sample of individual rows, modify your query to filter out rows randomly, instead of using TABLESAMPLE. For example, the following query uses the NEWID function to return approximately one percent of the rows of the Sales.SalesOrderDetail table:

SELECT * FROM Sales.SalesOrderDetail
WHERE 0.01 >= CAST(CHECKSUM(NEWID(),SalesOrderID) & 0x7fffffff AS float)
              / CAST (0x7fffffff AS int)

The SalesOrderID column is included in the CHECKSUM expression so that NEWID() evaluates once per row to achieve sampling on a per-row basis. The expression CAST(CHECKSUM(NEWID(), SalesOrderID) & 0x7fffffff AS float / CAST (0x7fffffff AS int) evaluates to a random float value between 0 and 1.

When run against a table with 1,000,000 rows, here are my results:

SET STATISTICS TIME ON
SET STATISTICS IO ON

/* newid()
   rows returned: 10000
   logical reads: 3359
   CPU time: 3312 ms
   elapsed time = 3359 ms
*/
SELECT TOP 1 PERCENT Number
FROM Numbers
ORDER BY newid()

/* TABLESAMPLE
   rows returned: 9269 (varies)
   logical reads: 32
   CPU time: 0 ms
   elapsed time: 5 ms
*/
SELECT Number
FROM Numbers
TABLESAMPLE (1 PERCENT)

/* Filter
   rows returned: 9994 (varies)
   logical reads: 3359
   CPU time: 641 ms
   elapsed time: 627 ms
*/    
SELECT Number
FROM Numbers
WHERE 0.01 >= CAST(CHECKSUM(NEWID(), Number) & 0x7fffffff AS float) 
              / CAST (0x7fffffff AS int)

SET STATISTICS IO OFF
SET STATISTICS TIME OFF

If you can get away with using TABLESAMPLE, it will give you the best performance. Otherwise use the newid()/filter method. newid()/order by should be last resort if you have a large result set.

Selecting Rows Randomly from a Large Table on MSDN has a simple, well-articulated solution that addresses the large-scale performance concerns.

  SELECT * FROM Table1
  WHERE (ABS(CAST(
  (BINARY_CHECKSUM(*) *
  RAND()) as int)) % 100) < 10