Data Warehouse Hardware - DW硬件需求计算
1. Disk I/O, 硬盘IO速度
硬盘的IO速度一直都是数据库的瓶颈,所以有条件的情况下尽可能的使用高IO的磁盘。
可以使用微软的工具SQLIO测试磁盘的IOPS
2. CPU的主频,
DW和传统的OLTP数据库在使用场景上不一样。
传统的OLTP数据库具有[事务小][并发多]的特点;而DW的数据库相比较具有[事务大][并发少]的特点。
所以对比起来,传统的OLTP数据库可以使用[低主频][多核]的硬件架构,而DW建议使用[高主频][少核]方案。
上述都是相对情况,对于不差钱的土豪,高主频,多核当然是更好的选择。
我们可以计算的是要满足具体的业务需求,需要多少CPU(Core),多少内存。
MCR,Maximum Consumption Rate,这是一个Core的吞吐量指标
3. 计算MCR
可以使用下面的脚本计算出当前计算机的MCR
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 BEGIN SET @i = @i + 1 INSERT 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 BEGIN INSERT INTO heap_table SELECT col2, col3 FROM clust_table; INSERT INTO clust_table SELECT col2, col3 FROM clust_table; END;
USE BenchmarkDB GO SELECT 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 core To estimate the no. of cores required, use the following formula: (Amount of data scanned in an average query / MCR) * Concurrent Sessions / Target response time For example: (18000 MB/200 MBs) * 10 users / 60s response time = 15 cores (round up to 16) */
4. Memory内存需求
最少1核对应4G内存,或者对每组CPU给64-128G内存