问题
- What is the key difference between IOPS and Throughput in large data storage?
- Does file size have an effect on IOPS? Why?
回答1:
IOPS measures the number of read and write operations per second, while throughput measures the number of bits read or written per second.
Although they measure different things, they generally follow each other as IO operations have about the same size.
If you have large files, you simply need more IO operations to read the entire file. The file size has no effect on the IOPS as it measures the number of clusters read or written, not the number of files.
If you have small files, there will be more overhead, so while the IOPS and throughput look good, you may experience a lower actual performance.
回答2:
IOPS - Number of read write operations mostly useful for OLTP transactions used in AWS for DBs like Cassandra.
Throughput - Is the number of bit transferred per sec. i.e.data transferred per sec. Mainly a unit for high data transfer applications like big data hadoop,kafka streaming
回答3:
The Disk IOPS Describes the count of input/output operations on the disk per seconds, regardless block size.
The disk throughput describes how many data may be transferred per second, so the block size play a huge role upon calculating the throughput required by app
Let's consider as the sample the 3000 IOPS and SQL database engine, the block size in terms of db engine is called the page size and for SQL Server it's equal to 8 KB. If you wish to calculate the actual throughput, if the IOPS defined, you will end up with the formula below:
throughput = [IOPS] * [block size] = 3000 * 8 = 24 000 KB/s = 24 MB/s
来源：https://stackoverflow.com/questions/15759571/iops-versus-throughput