Paxos and Raft : Consensus Algorithms

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Future Is Already Here

Eksplain

32 episodes

1 week ago

“The future is already here — it's just not very evenly distributed,” said science fiction writer William Gibson. We agree. Our mission is to help change that. This podcast breaks down advanced technologies and innovations in simple, easy-to-understand ways, making cutting-edge ideas more accessible to everyone. Please note: Some of our content may be AI-generated, including voices, text, images, and videos.

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Paxos and Raft : Consensus Algorithms - A Deep Dive

Future Is Already Here

24 minutes 4 seconds

9 months ago

Paxos and Raft : Consensus Algorithms - A Deep Dive

In this episode, we'll explore two fundamental consensus algorithms used in distributed systems: Raft and Paxos. These algorithms allow a collection of machines to work as a coherent group, even when some members fail. Understanding these algorithms is crucial for anyone building or working with distributed systems.

We'll begin by examining Paxos, a protocol that has become almost synonymous with consensus. We will discuss how Paxos ensures both safety and liveness, and supports changes in cluster membership. However, it is also known for its complexity and difficulty to understand. As Lamport put it, the original presentation was "Greek to many readers". We'll delve into the core concepts of Paxos, highlighting its two-phase protocol for reaching agreement on a single decision and how it combines multiple instances of this protocol for a series of decisions. We will also cover its peer-to-peer approach, and the fact that a weak form of leadership can be implemented as a performance optimization4

Next, we will focus on Raft, an algorithm designed with understandability as a primary goal. Raft simplifies the consensus problem by decomposing it into three relatively independent subproblems: leader election, log replication, and safety. We'll explore how Raft uses a strong leader model where the leader manages the replicated log, accepting entries from clients, replicating them to other servers, and telling servers when it's safe to apply them. We will also cover its randomized timers for leader election, and a new joint consensus approach for membership changes. We will also discuss the log replication mechanism in Raft that maintains a high level of coherency between the logs on different servers, and the leader append-only property, and its commitment rules. A user study demonstrated that Raft was significantly easier for students to understand than Paxos.

References:

This episode draws upon the following sources: Ongaro, Diego, and John Ousterhout. "In Search of an Understandable Consensus Algorithm." (Raft.pdf) Yadav, Ritwik, and Anirban Rahut. "FlexiRaft: Flexible Quorums with Raft." (Flexiraft.pdf) Lamport, Leslie. "Paxos Made Simple." (paxos made simple.pdf)

Disclaimer:

Please note that parts or all this episode was generated by AI. While the content is intended to be accurate and informative, it is recommended that you consult the original research papers for a comprehensive understanding.