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GitHub Actions

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Luigi vs Github Actions: What are the differences?

Luigi: ETL and data flow management library *. It is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in; *Github Actions:** Automate your workflow from idea to production. It makes it easy to automate all your software workflows, now with world-class CI/CD. Build, test, and deploy your code right from GitHub. Make code reviews, branch management, and issue triaging work the way you want.

Luigi and Github Actions can be categorized as "Workflow Manager" tools.

Some of the features offered by Luigi are:

  • dependency resolution
  • workflow management
  • visualization

On the other hand, Github Actions provides the following key features:

  • Multiple workflow files support
  • Free and open source
  • Workflow run interface

Luigi is an open source tool with 13.4K GitHub stars and 2.13K GitHub forks. Here's a link to Luigi's open source repository on GitHub.

According to the StackShare community, Github Actions has a broader approval, being mentioned in 31 company stacks & 30 developers stacks; compared to Luigi, which is listed in 9 company stacks and 34 developer stacks.

Advice on GitHub Actions and Luigi
Needs advice
on
AirflowAirflowLuigiLuigi
and
Apache SparkApache Spark

I am so confused. I need a tool that will allow me to go to about 10 different URLs to get a list of objects. Those object lists will be hundreds or thousands in length. I then need to get detailed data lists about each object. Those detailed data lists can have hundreds of elements that could be map/reduced somehow. My batch process dies sometimes halfway through which means hours of processing gone, i.e. time wasted. I need something like a directed graph that will keep results of successful data collection and allow me either pragmatically or manually to retry the failed ones some way (0 - forever) times. I want it to then process all the ones that have succeeded or been effectively ignored and load the data store with the aggregation of some couple thousand data-points. I know hitting this many endpoints is not a good practice but I can't put collectors on all the endpoints or anything like that. It is pretty much the only way to get the data.

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Replies (1)
Gilroy Gordon
Solution Architect at IGonics Limited · | 2 upvotes · 282.4K views
Recommends
on
CassandraCassandra

For a non-streaming approach:

You could consider using more checkpoints throughout your spark jobs. Furthermore, you could consider separating your workload into multiple jobs with an intermittent data store (suggesting cassandra or you may choose based on your choice and availability) to store results , perform aggregations and store results of those.

Spark Job 1 - Fetch Data From 10 URLs and store data and metadata in a data store (cassandra) Spark Job 2..n - Check data store for unprocessed items and continue the aggregation

Alternatively for a streaming approach: Treating your data as stream might be useful also. Spark Streaming allows you to utilize a checkpoint interval - https://spark.apache.org/docs/latest/streaming-programming-guide.html#checkpointing

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Pros of GitHub Actions
Pros of Luigi
  • 8
    Integration with GitHub
  • 5
    Free
  • 3
    Easy to duplicate a workflow
  • 3
    Ready actions in Marketplace
  • 2
    Configs stored in .github
  • 2
    Docker Support
  • 2
    Read actions in Marketplace
  • 1
    Active Development Roadmap
  • 1
    Fast
  • 5
    Hadoop Support
  • 3
    Python
  • 1
    Open soure

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Cons of GitHub Actions
Cons of Luigi
  • 5
    Lacking [skip ci]
  • 4
    Lacking allow failure
  • 3
    Lacking job specific badges
  • 2
    No ssh login to servers
  • 1
    No Deployment Projects
  • 1
    No manual launch
    Be the first to leave a con

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    - No public GitHub repository available -

    What is GitHub Actions?

    It makes it easy to automate all your software workflows, now with world-class CI/CD. Build, test, and deploy your code right from GitHub. Make code reviews, branch management, and issue triaging work the way you want.

    What is Luigi?

    It is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.

    Need advice about which tool to choose?Ask the StackShare community!

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    What are some alternatives to GitHub Actions and Luigi?
    CircleCI
    Continuous integration and delivery platform helps software teams rapidly release code with confidence by automating the build, test, and deploy process. Offers a modern software development platform that lets teams ramp.
    Jenkins
    In a nutshell Jenkins CI is the leading open-source continuous integration server. Built with Java, it provides over 300 plugins to support building and testing virtually any project.
    Azure Pipelines
    Fast builds with parallel jobs and test execution. Use container jobs to create consistent and reliable builds with the exact tools you need. Create new containers with ease and push them to any registry.
    GitLab CI
    GitLab offers a continuous integration service. If you add a .gitlab-ci.yml file to the root directory of your repository, and configure your GitLab project to use a Runner, then each merge request or push triggers your CI pipeline.
    GitLab
    GitLab offers git repository management, code reviews, issue tracking, activity feeds and wikis. Enterprises install GitLab on-premise and connect it with LDAP and Active Directory servers for secure authentication and authorization. A single GitLab server can handle more than 25,000 users but it is also possible to create a high availability setup with multiple active servers.
    See all alternatives