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This article mainly explains "what's the difference between spark on yarn and on docker". Interested friends might as well take a look. The method introduced in this paper is simple, fast and practical. Now let the editor take you to learn "what's the difference between spark on yarn and on docker"?

What is the maturity of Q1:docker?

Docker is the hottest open source cloud computing project in 2013 and 2014.

Baidu is the most in-depth and largest company using Docker in China, running hundreds of thousands of Docker containers stably online. at present, it has used Docker to comprehensively upgrade its own BAE, and the upgraded BAE exceeds expectations both in performance and business performance.

What is the difference in positioning between Q2:Docker and cloud computing OpenStack?

Docker is a complete solution for lightweight virtualization

Docker is the best implementation of PaaS.

Docker is a Linux-based Process Container, which isolates and restricts resources in the outer layer through Container technology. Now, without any language level, new PaaS platforms in the industry have chosen to be implemented based on Container.

Q3: can docker access each other across physical machines now?

There's no problem at all.

Q4:spark on yarn can also improve utilization. How is it different from spark on docker?

Yarn is used for big data cluster resource management and allocation, and Docker is used for cloud computing infrastructure.

Spark on yarn is the resource management and allocation of Spark cluster by Spark with the help of Yarn

Spark on Docker is a way to deploy Spark clusters

At this point, I believe you have a deeper understanding of "what's the difference between spark on yarn and on docker". You might as well do it in practice. Here is the website, more related content can enter the relevant channels to inquire, follow us, continue to learn!

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