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Let's Understand Quorum Properly in Distributed Systems: Explained with Real-World Examples
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In this video, I'll explain the concept of quorum in distributed systems. Quorum represents the majority agreement among servers when making decisions. When dealing with multiple machines, decisions are based on the agreement of more than half of the servers.
In a distributed system, nodes sync with each other, and when a client like Alice requests data, it goes through a coordinator node, which determines the location of the data and fetches the response.
There are three main consistency levels: "all" for strong consistency, "one" for faster writes, and "quorum" for a balance between speed and consistency.
Tuneable consistency allows customising levels for read and write operations, making it valuable in systems like Apache Cassandra.
Join me to grasp a better understanding of quorum's role in achieving reliable data storage in distributed systems
Chapters:
00:00 Intro
00:56 Data flow
04:21 Replication factor
07:09 Consistency Level
11:06 tun-able consistency
13:51 Summary
In a distributed system, nodes sync with each other, and when a client like Alice requests data, it goes through a coordinator node, which determines the location of the data and fetches the response.
There are three main consistency levels: "all" for strong consistency, "one" for faster writes, and "quorum" for a balance between speed and consistency.
Tuneable consistency allows customising levels for read and write operations, making it valuable in systems like Apache Cassandra.
Join me to grasp a better understanding of quorum's role in achieving reliable data storage in distributed systems
Chapters:
00:00 Intro
00:56 Data flow
04:21 Replication factor
07:09 Consistency Level
11:06 tun-able consistency
13:51 Summary
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