Was watching a series from Big Data Analysis with Scala and Spark and the video about latency led me down a rabbit hole. I had first seen this break down from System Design Interview by Alex Xu. These values estimated/adjusted from Colin's Scott's Interactive Latency:
L1 cache reference ~0.5-1 ns
Branch mispredict ~3 ns
L2 cache reference 4 ns 14x L1 cache
Mutex lock/unlock 17 ns
Main memory reference 100 ns 20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy 3,000 ns 3 us
Send 1K bytes over 1 Gbps network 10,000 ns 10 us
Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD
Read 1 MB sequentially from memory 250,000 ns 250 us
Round trip within same datacenter 500,000 ns 500 us
Read 1 MB sequentially from SSD* 1,000,000 ns 1,000 us 1 ms ~1GB/sec SSD, 4X memory
Disk seek 10,000,000 ns 10,000 us 10 ms 20x datacenter roundtrip
Read 1 MB sequentially from disk 20,000,000 ns 20,000 us 20 ms 80x memory, 20X SSD
Send packet CA->Netherlands->CA 150,000,000 ns 150,000 us 150 ms
The scale can be conceptualized in terms of time with this gist from hellerbarde.
I wanted to adapt this data so that it can be groked visually with scale.
TODO: Better visuals with dynamic calculations. Currently adapted from Odds of Dying and Winning Mega Millions Lottery
Credit
- Originally by Peter Norvig: norvig.com/21-days.html#answers
- Jeff Dean: research.google.com/people/jeff