Mindfork Tech

Concept       In distributed systems, it is often normal that data is replicated on other nodes to provide resiliency and high fault tolerance.  But at the same time, storing all of the data on a single node and keeping its copies across others might increase the query time and might affect query throughput. Well, While working with a large amount of data, in order to increase the query throughput, data needs to be distributed or partitioned across the nodes. This makes it easy to leverage the compute power of all the nodes involved.          A node having all the data is often known to be a "hot-spot". If the data is being queried, it will get queried from one of the nodes, depending upon the query type and type of replication i.e. leader-follower replication or leader-leader replication. If a node has all the data, then query throughput will suffer as it will have to refer all of the data unnecessarily. And that's where partitioning comes to rescue. Key-Range

Preface When it comes to Networking, I always thought it's so boring and never ever gave a thought about how cool it can be! Well, as a human, psychologically, we all tend to have some biases, towards clothes, brands, things, opinions, judgments, emotions, the language to code in :P, etc which all contribute to some stubborn prejudices in our mind and which in turn creates conjectures. Well, in my opinion, Conjectures aren't healthy(subjective), as you tend to live in your hypothetical world without giving damn about facts and proofs. And the only way out is to cross-examine every decision, opinion, and judgment you make. Well, it's not a psychology blog, let's just leave it here. :) This is my experience of getting out of my prejudice with networking.  While working for a network feature, I came across this amazing use case. Thought of writing it down after I get done with it. Now I think it's the time. Grab your chair and popcorn, here it goes! Con