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YARN Hadoop vs Yarn: What are the differences?

Introduction

YARN (Yet Another Resource Negotiator) is a component of Apache Hadoop, which is an open-source framework used for distributed processing of large data sets across clusters of computers.

  1. 1. Scalability and Resource Management: YARN Hadoop is designed to provide enhanced scalability and efficient resource management in Hadoop clusters. It allows multiple applications to run simultaneously, optimizing resource utilization by allocating resources dynamically based on application needs.

  2. 2. Application Framework Integration: YARN Hadoop provides a flexible and extensible architecture that allows various application frameworks to coexist and share the same cluster resources. It supports multiple programming models such as MapReduce, Apache Pig, Apache Hive, and Spark, enabling developers to choose the best framework for their specific processing requirements.

  3. 3. Fault Tolerance: YARN Hadoop has built-in fault tolerance mechanisms to ensure the reliability of data processing. It automatically detects and recovers from failures, redistributing work to healthy nodes in the cluster, thus minimizing data loss and disruption of service.

  4. 4. Multi-tenancy Support: YARN Hadoop supports multi-tenancy, allowing different users or organizations to securely share the same cluster while isolating their computing resources. It provides resource limits and scheduling policies to ensure fair sharing and prevent one user from monopolizing the cluster resources.

  5. 5. Fine-grained Resource Allocation: YARN Hadoop allows fine-grained resource allocation, enabling better control and utilization of cluster resources. It supports containerization technology, which provides isolation and resource monitoring at the task level, allowing for more efficient resource management and optimization.

  6. 6. Enhanced Cluster Utilization: YARN Hadoop improves cluster utilization by supporting dynamic allocation of resources based on application requirements. It enables applications to request and release resources as needed, ensuring efficient resource utilization and reducing idle resource wastage.

In summary, YARN Hadoop provides enhanced scalability, application framework integration, fault tolerance, multi-tenancy support, fine-grained resource allocation, and improved cluster utilization in Apache Hadoop clusters.

Advice on Yarn and YARN Hadoop
Needs advice
on
npmnpm
and
YarnYarn

From a StackShare Community member: “I’m a freelance web developer (I mostly use Node.js) and for future projects I’m debating between npm or Yarn as my default package manager. I’m a minimalist so I hate installing software if I don’t need to- in this case that would be Yarn. For those who made the switch from npm to Yarn, what benefits have you noticed? For those who stuck with npm, are you happy you with it?"

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Replies (14)
Julian Sanchez
Lead Developer at Chore Champion · | 11 upvotes · 253.3K views
Recommends
on
YarnYarn
at

We use Yarn because it allows us to more simply manage our node_modules. It also simplifies commands and increases speed when installing modules. Our teams module download time was cut in half after switching from NPM to Yarn. We now require all employees to use Yarn (to prevent errors with package-lock.json and yarn.lock).

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Recommends
on
npmnpm

I use npm since new version is pretty fast as well (Yarn may be still faster a bit but the difference isn't huge). No need for other dependency and mainly Yarn sometimes do not work. Sometimes when I want to install project dependencies I got error using Yarn but with npm everything is installed correctly.

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Recommends
on
YarnYarn

p.s.

I am not sure about the performance of the latest version of npm, whether it is different from my understanding of it below. Because I use npm very rarely when I had the following knowledge.

------⏬

I use Yarn because, first, yarn is the first tool to lock the version. Second, although npm also supports the lock version, when you use npm to lock the version, and then use package-lock.json on other systems, package-lock.json Will be modified. You understand what I mean, when you deploy projects based on Git...

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Mark Nelissen
Recommends
on
npmnpmnpmnpm

I use npm because I also mainly use React and TypeScript. Since several typings (from DefinitelyTyped) depend on the React typings, Yarn tends to mess up which leads to duplicate libraries present (different versions of the same type definition), which hinders the Typescript compiler. Npm always resolves to a single version per transitive dependency. At least that's my experience with both.

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Recommends
on
YarnYarn

As far as I know Yarn is a super module of NPM. But it still needs npm to run.

Yarn was developed by Facebook's guys to fix some npm issues and performance.

If you use the last version of npm most of this problem does not exist anymore.

You can choose the option which makes you more confortable. I like using yarn because I'm used to it.

In the end the packages will be the same. Just try both and choose the one you feel more confortable. :)

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Recommends
on
YarnYarn

I am a minimalist too. I once had issues with installing Nuxt.js using NPM so I had to install Yarn but I also found that the Dev experience was much better

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Digital All
Recommends
on
npmnpm

I use npm because its packaged with node installation and handles npm tokens in CI/CD tools for private packages/libraries.

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Izzur Zuhri
Recommends
on
npmnpm

I use npm because it has a lot of community support and the performance difference with alternative tool is not so significant for me.

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tataata
Frontend designer and developer · | 3 upvotes · 238.5K views
Recommends
on
YarnYarn

Yarn made it painless for the team to sync on versions of packages that we use on the project <3

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Shuuji TAKAHASHI
Recommends
on
YarnYarn

I use Yarn because it outputs nice progress messages with cute emoji and installs packages quickly if the package is cached. Also, Yarn creates yarn.lock file which makes the developer use the consistent environment.

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Tor Hagemann
Principal Software Engineer at Socotra · | 3 upvotes · 138.7K views
Recommends
on
npmnpmYarnYarn

You should use whichever had the best DX (developer experience) for your team. If you are doing a massive front-end project, consider yarn if not only because it makes it a snap to go from zero to ready. What some people say about npm being more stable or easier for smaller projects is highly true as well. (not to mention, you sometimes have to install yarn) But, note that official NodeJS Docker images ship with both npm and yarn. If you want to use yarn, put package-lock=false and optionally save-exact=true in your project's .npmrc file. Compare whether you prefer the ergonomics of yarn global add over npm install -g or see fewer meaningless warnings for the specific set of dependencies you leverage.

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Recommends
on
npmnpm

I use npm because its the official package manager for Node. It's reliability, security and speed has increased over time so the battle is over!

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Francois Leurent
Recommends
on
npmnpm
at

We tend to stick to npm, yarn is only a fancy alternative, not 10x better. Using a self -hosted private repository (via sinopia/npm-mirror) make package locking (mostly) pointless.

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Denys Slipetskyy
Recommends
on
YarnYarn
at

I use Yarn because it process my dependencies way faster, predictable deps resolution order, upgrade-interactive is very handy + some Yarn specific features (workspaces, Plug’n’Play alternative installation strategy) ...

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Decisions about Yarn and YARN Hadoop
Oleksandr Fedotov
Senior Software Engineer at joyn · | 3 upvotes · 280.4K views

As we have to build the application for many different TV platforms we want to split the application logic from the device/platform specific code. Previously we had different repositories and it was very hard to keep the development process when changes were done in multiple repositories, as we had to synchronize code reviews as well as merging and then updating the dependencies of projects. This issues would be even more critical when building the project from scratch what we did at Joyn. Therefor to keep all code in one place, at the same time keeping in separated in different modules we decided to give a try to monorepo. First we tried out lerna which was fine at the beginning, but later along the way we had issues with adding new dependencies which came out of the blue and were not easy to fix. Next round of evolution was yarn workspaces, we are still using it and are pretty happy with dev experience it provides. And one more advantage we got when switched to yarn workspaces that we also switched from npm to yarn what improved the state of the lock file a lot, because with npm package-lock file was updated every time you run npm install, frequent updates of package-lock file were causing very often merge conflicts. So right now we not just having faster dependencies installation time but also no conflicts coming from lock file.

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Petr Bambušek
Head of Frontend at Mews · | 2 upvotes · 294.4K views
Chose
YarnYarn
over
npmnpm
at
()

This was no real choice - we switched the moment Yarn was available, and never looked back. Yarn is the only reasonable frontend package manager that's actually being developed. They even aim to heal the node_modules madness with v2! Npm is just copying its ideas on top of introducing massive bugs with every change.

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Pros of Yarn
Pros of YARN Hadoop
  • 85
    Incredibly fast
  • 22
    Easy to use
  • 13
    Open Source
  • 11
    Can install any npm package
  • 8
    Works where npm fails
  • 7
    Workspaces
  • 3
    Incomplete to run tasks
  • 2
    Fast
  • 1
    Batch processing with commodity machine

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Cons of Yarn
Cons of YARN Hadoop
  • 16
    Facebook
  • 7
    Sends data to facebook
  • 4
    Should be installed separately
  • 3
    Cannot publish to registry other than npm
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    What is Yarn?

    Yarn caches every package it downloads so it never needs to again. It also parallelizes operations to maximize resource utilization so install times are faster than ever.

    What is YARN Hadoop?

    Its fundamental idea is to split up the functionalities of resource management and job scheduling/monitoring into separate daemons. The idea is to have a global ResourceManager (RM) and per-application ApplicationMaster (AM).

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    Mar 24 2021 at 12:57PM

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