USE master;-- Create a database for benchmark queries
IF EXISTS (SELECT * FROM sys.sysdatabases WHERE name = 'BenchmarkDB')
DROP DATABASE BenchMarkDB;
GO
CREATE DATABASE BenchMarkDB;
GO
USE BenchMarkDB;-- Include a heap and a table with a clustered index
CREATE TABLE heap_table
(col1 integer identity,col2 integer,col3 varchar(50));CREATE TABLE clust_table
(col1 integer identity PRIMARY KEY CLUSTERED,col2 integer,col3 varchar(50));-- Insert 100 rows to start with
DECLARE @i integer = 0;
WHILE @i < 101
BEGINSET @i = @i + 1INSERT INTO heap_table VALUES (@i, CAST(@i%5 AS varchar))INSERT INTO clust_table VALUES (@i, CAST(@i%5 AS varchar))
END;-- Now keep reinserting exponentially until the tables each contain 2 million rows
WHILE (SELECT COUNT(*) FROM clust_table) < 2000000
BEGININSERT INTO heap_tableSELECT col2, col3 FROM clust_table;INSERT INTO clust_tableSELECT col2, col3 FROM clust_table;
END;

USE BenchmarkDB
GOSELECT SUM(Col2) FROM heap_table WHERE col1 % 3 = 1
GROUP BY col3;SELECT SUM(Col2) FROM clust_table WHERE col1 % 3 = 1
GROUP BY col3;SET STATISTICS IO ON;
SET STATISTICS TIME ON;-- run these muliple times and take an average of the logical reads and CPU time
SELECT SUM(Col2) FROM heap_table WHERE col1 % 3 = 1
GROUP BY col3
OPTION (MAXDOP 1);SELECT SUM(Col2) FROM clust_table WHERE col1 % 3 = 1
GROUP BY col3
OPTION (MAXDOP 1);/* Max Consumption Rate (MCR) is the average of (logical reads / CPU time in seconds) * 8 / 1024(or put another way, the size of the table in MB / CPU time in seconds)This gives us the throughput of a coreTo estimate the no. of cores required, use the following formula:(Amount of data scanned in an average query / MCR) * Concurrent Sessions / Target response timeFor example:(18000 MB/200 MBs) * 10 users / 60s response time = 15 cores (round up to 16)   */