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Apache Oozie vs Yarn: What are the differences?

Introduction:

Apache Oozie and Apache Yarn are two popular technologies used in the Apache Hadoop ecosystem. While Apache Oozie is a workflow scheduling system for managing Apache Hadoop jobs, Apache Yarn is a resource management framework that allows multiple data processing engines to run on Hadoop clusters. Understanding the key differences between these two technologies is crucial for making informed decisions when working with big data processing.

  1. Integration with Hadoop Components: One of the key differences between Apache Oozie and Yarn is their integration with other components in the Hadoop ecosystem. Oozie acts as a workflow scheduler for managing jobs in Hadoop, while Yarn provides a resource management framework that allows multiple data processing engines such as MapReduce, Spark, and Tez to run on Hadoop clusters.

  2. Functionality: Another major difference lies in their functionality. Oozie primarily focuses on coordinating and scheduling workflows, providing advanced scheduling capabilities and supporting complex job dependencies. On the other hand, Yarn focuses on the resource management aspects of a Hadoop cluster, providing a fine-grained control of resources and facilitating efficient utilization of cluster resources among different data processing frameworks.

  3. High-Level vs. Low-Level: Oozie is a high-level workflow coordination system that abstracts the underlying details of the data processing frameworks, providing a simplified approach to managing job orchestration. Yarn, on the other hand, is a low-level resource management framework that allows fine-grained control over resources, giving more flexibility but requiring users to explicitly manage resource allocation and scheduling.

  4. Granularity of Management: Oozie manages workflows at a higher level, focusing on overall job coordination and dependencies, while Yarn manages resources at a more granular level, allowing fine-grained control over resource allocation and usage.

  5. Dependency and Job Scheduling: Oozie provides advanced features for managing dependencies between jobs and scheduling complex workflows, allowing users to define job dependencies and specify conditions for job execution. Yarn, on the other hand, focuses on resource management and doesn't provide built-in features for managing job dependencies and scheduling workflows.

  6. User Community and Adoption: Oozie has been widely adopted and has a strong user community, with extensive documentation and tutorials available. Yarn, as a core component of the Hadoop ecosystem, is widely used in many big data processing frameworks and has a large user community as well.

In summary, Apache Oozie is a workflow scheduling system for managing Hadoop jobs and provides advanced features for job coordination and scheduling, while Apache Yarn is a resource management framework that focuses on efficient resource allocation and utilization in a Hadoop cluster.

Advice on Apache Oozie and Yarn
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 · 252.9K views
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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 · 238.2K 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
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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 · 138.4K 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
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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
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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 Apache Oozie and Yarn
Oleksandr Fedotov
Senior Software Engineer at joyn · | 3 upvotes · 280K 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 · 293.9K 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 Apache Oozie
Pros of Yarn
    Be the first to leave a pro
    • 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

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    Cons of Apache Oozie
    Cons of Yarn
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      • 16
        Facebook
      • 7
        Sends data to facebook
      • 4
        Should be installed separately
      • 3
        Cannot publish to registry other than npm

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      - No public GitHub repository available -

      What is Apache Oozie?

      It is a server-based workflow scheduling system to manage Hadoop jobs. Workflows in it are defined as a collection of control flow and action nodes in a directed acyclic graph. Control flow nodes define the beginning and the end of a workflow as well as a mechanism to control the workflow execution path.

      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.

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        What are some alternatives to Apache Oozie and Yarn?
        Apache Spark
        Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
        Airflow
        Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed.
        Apache NiFi
        An easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.
        Zookeeper
        A centralized service for maintaining configuration information, naming, providing distributed synchronization, and providing group services. All of these kinds of services are used in some form or another by distributed applications.
        Apache Beam
        It implements batch and streaming data processing jobs that run on any execution engine. It executes pipelines on multiple execution environments.
        See all alternatives