399 views • Distributed Systems
Reaching consensus is extremely important in any distributed network. For example, we cannot have two data nodes in a cluster where one thinks that
$1000 while the other thinks it is
So, we need the nodes to talk to each other and reach a consensus and converge on the true value of
price. Reaching consensus is easy when there are no failures - no network failures, or process failures.
But, reaching a consensus becomes impossible when we cannot guarantee message delivery.
Say, there are two generals - A and B - and they want to attack the enemy from two different directions. The only way to conquer the enemy is when both generals attack simultaneously. If only one attacks, then the enemy wins.
The generals communicate via foot soldiers. These foot soldiers can be captured by the enemy and hence the message that generals wanted to send to each other can be lost. So, how would generals coordinate the attack?
If the communication channel is reliable, then the generals all send each other messages to agree to attack and everyone responds/ack to everyone else, thus coordinating the attack.
Committing to a distributed database. The commit should succeed when all the nodes of the database agree to commit. If anyone cannot commit then the commit cannot go through.
When general A sent a message to general B, what if B’s response got lost? then general A would not know if it should attack or not.
Also, since B did not receive an ack from A, then it cannot decide if it should attack or not either.
This is where we see both generals will keep on waiting for an acknowledgment of an acknowledgment, purely because the communication channel is unreliable.
This is the class Two Generals’ Problem where it is impossible to reach a consensus when the underlying communication channel is unreliable.
Generals, instead of sending just a foot soldier, can send multiple foot soldiers increasing the probability that at least one of them would go through.
This is like we are flooding an unreliable network to get our message delivered.
In the real world, hence we do not assume a completely unreliable network. Instead, we assume a certain fraction of messages will be lost - eg: 1 in 2. Hence to overcompensate we send 2 messages instead of one.
If you like what you read subscribe you can always subscribe to my newsletter and get the post delivered straight to your inbox. I write essays on various engineering topics and share it through my weekly newsletter.
618 views • 28 likes • 2022-09-16
Distributed Transactions are the heart and soul of Distributed Systems and getting all the participating nodes to agree ...
379 views • 16 likes • 2022-09-14
Byzantine Agreement is an important problem to address in a Distributed Network. It is all about being tolerant of the n...
245 views • 6 likes • 2022-09-12
Exponential Algorithms have to be the worst possible way to solve Distributed Consensus; but are they really that bad? ...
432 views • 14 likes • 2022-09-09
Reaching a consensus is extremely critical in a Distributed System as we would have situations day-in and day-out where ...
A set of courses designed to make you a better engineer and excel at your career; no-fluff, pure engineering.
Being a passionate engineer, I love to talk about a wide range of topics, but these are my personal favourites.
Arpit's Newsletter read by 17000+ engineers
🔥 Thrice a week, in your inbox, an essay about system design, distributed systems, microservices, programming languages internals, or a deep dive on some super-clever algorithm, or just a few tips on building highly scalable distributed systems.
Powered by this tech stack.