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Distributed Systems Classics (2017)

nvartolomei.com

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Re: Distributed Systems Classics (2017)

#22

I am a Lamport admirer. I gradually realized that Lamport is more of the godfather of distributed system than Hinton is to deep learning. Lamport is less prominent than Shannon is to information theory. Shannon is the closest to any title of "gold-like" figure to a scientific discipline of universal relevance in modern society. Lamport specifically revealed a philosophical connections between computer systems and phy…

> the relations between events happening in a distributed system, is more fundamental than their absolute ordering

The important thing in most distributed systems is having an order. Having a single observer serialize events as it receives them is so much more tractable than trying to use absolute order. Using absolute order requires very precise time synchronization which is hard; using absolute order requires knowing when you have received all the reports of events that already happened which is hard. Determining a designated observer isn't typically easy, but having it determine the order it observes events is easy. If two events happen at a similar time it's typically not a big deal which one is considered first as long as all nodes will agree on the result --- let the designated observer just pick the first one it sees works pretty well. If your report takes an unexpectedly long time to make it to the designated observer, then it won't be first and you'll deal.

Much better than trying to figure out unknowable questions of relativity. :P

Re: Distributed Systems Classics (2017)

#23
Some other classics (applied dist systems):

- DDB: https://www.allthingsdistributed.com/files/amazon-dynamo-sos...

- MapReduce: https://www.cs.princeton.edu/courses/archive/fall13/cos518/p...

- Spark/RDDs: https://www.usenix.org/system/files/conference/nsdi12/nsdi12...

- BigTable: https://static.googleusercontent.com/media/research.google.c...

Re: Distributed Systems Classics (2017)

#24

I am a Lamport admirer. I gradually realized that Lamport is more of the godfather of distributed system than Hinton is to deep learning. Lamport is less prominent than Shannon is to information theory. Shannon is the closest to any title of "gold-like" figure to a scientific discipline of universal relevance in modern society. Lamport specifically revealed a philosophical connections between computer systems and phy…

Hot take of the day:

Computer scientists are in denial about it, but CS is a branch of theoretical physics, not mathematics. You can point to this or that model of computation, such as lambda calculus or mu-recursive functions and try to claim its abstracted well beyond the particular laws of physics for some specific universe, but they all have some kind of rate limit built into them... and where does the motivation for this idea, that it takes something (time, space, work) to compute something ultimately come from? That's right - from underlying physics itself[1] - from the Bekenstein bound or Bremermann's limit or the like.

Even apparently non-physically-realizable models of computation like non-deterministic Turing machines are ultimately informed by and motivated by concepts in physics... otherwise they would just be examples of chmess[2] and of no interest to anyone. Computer science is of course somewhat abstracted from the details, but no more so than, say, thermodynamics, where concepts like entropy or Gibbs free energy can be studied in the abstract without reference to whether we are talking about a gas of non-interacting molecules or the spins of a bunch of electrons trapped in a lattice.

So, it's of no surprise whatsoever that the fundamental problems of distributed computing are ultimately the same as those found in the relativity of simultaneity[3]. You've all been studying the same things all along, just with different tools and at different levels of abstraction.

[1]: https://en.wikipedia.org/wiki/Limits_of_computation

[2]: https://link.springer.com/article/10.1007/s11245-006-0005-2

[3]: https://en.wikipedia.org/wiki/Relativity_of_simultaneity

Re: Distributed Systems Classics (2017)

#25
post #13

This is not a bad list for sure. Here are some deeper cuts for those looking for something a bit less mainstream: "The Maintenance of Duplicate Databases" https://datatracker.ietf.org/doc/html/rfc677 (AFAIK the genesis of the use of logical clocks in distributed systems). "Chain Replication for Supporting High Throughput and Availability" https://www.usenix.org/legacy/event/osdi04/tech/full_papers/... (Chain replicat…

Lamport lists his collected works on his site[0] along with some commentary for each one, and directly mentions, The Maintenance of Duplicate Databases, as the origin for logical clock paper. Many of the notes have interesting commentary.

> Many computer scientists claim to have read it. But I have rarely encountered anyone who was aware that the paper said anything about state machines. People seem to think that it is about either the causality relation on events in a distributed system, or the distributed mutual exclusion problem. People have insisted that there is nothing about state machines in the paper. I've even had to go back and reread it to convince myself that I really did remember what I had written.[1]

0: https://lamport.azurewebsites.net 1: https://lamport.azurewebsites.net/pubs/pubs.html#time-clocks

Re: Distributed Systems Classics (2017)

#28
post #24

I am a Lamport admirer. I gradually realized that Lamport is more of the godfather of distributed system than Hinton is to deep learning. Lamport is less prominent than Shannon is to information theory. Shannon is the closest to any title of "gold-like" figure to a scientific discipline of universal relevance in modern society. Lamport specifically revealed a philosophical connections between computer systems and phy…

Hot take of the day: Computer scientists are in denial about it, but CS is a branch of theoretical physics, not mathematics. You can point to this or that model of computation, such as lambda calculus or mu-recursive functions and try to claim its abstracted well beyond the particular laws of physics for some specific universe, but they all have some kind of rate limit built into them... and where does the motivation…

I suspect this is old news for you, but just in case you haven't heard of it, check out Feynman's Lectures on Computation. A surprising amount of the book is still relevant, and it's fun how much he always brings everything back to the physics.

Re: Distributed Systems Classics (2017)

#30
post #24

I am a Lamport admirer. I gradually realized that Lamport is more of the godfather of distributed system than Hinton is to deep learning. Lamport is less prominent than Shannon is to information theory. Shannon is the closest to any title of "gold-like" figure to a scientific discipline of universal relevance in modern society. Lamport specifically revealed a philosophical connections between computer systems and phy…

Hot take of the day: Computer scientists are in denial about it, but CS is a branch of theoretical physics, not mathematics. You can point to this or that model of computation, such as lambda calculus or mu-recursive functions and try to claim its abstracted well beyond the particular laws of physics for some specific universe, but they all have some kind of rate limit built into them... and where does the motivation…

Related hot take

Maybe thats why one of the not-so-bad ideas how to go about distributed systems came from a guy who was trained as a physicist and used to complain to his fellow programmers that “a lot of systems actually break the laws of physics”[1]?

> In distributed systems there is no real shared state (imagine one machine in the USA another in Sweden) where is the shared state? In the middle of the Atlantic? - shared state breaks laws of physics. State changes are propagated at the speed of light - we always know how things were at a remote site not how they are now. What we know is what they last told us. If you make a software abstraction that ignores this fact you’ll be in trouble.[2]

[1]: “The Mess We’re In”, 2014 https://www.youtube.com/watch?v=lKXe3HUG2l4 [2]: https://news.ycombinator.com/item?id=19708900

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