Airflow
Apache Camel
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Airflow | Apache Camel | |
---|---|---|
151 | 18 | |
29,553 | 4,778 | |
2.2% | 1.9% | |
10.0 | 10.0 | |
6 days ago | 6 days ago | |
Python | Java | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Airflow
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.NET Modern Task Scheduler
A few years ago, I opened a GitHub issue with Microsoft telling them that I think the .NET ecosystem needs its own equivalent of Apache Airflow or Prefect. Fast forward 'til now, and I still don't think we have anything close to these frameworks.
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How do you decide when to keep a project in a single python file vs break it up into multiple files?
Check out taskinstance.py in the Airflow project, it's a well targeted file, it has only one main class TaskInstance and a few small supporting classes and functions. It is ~3000 lines long: https://github.com/apache/airflow/blob/main/airflow/models/taskinstance.py
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How do you backup running systems?
If you have the spare capacity Apache Airflow is great for this.
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Building a Data Lakehouse for Analyzing Elon Musk Tweets using MinIO, Apache Airflow, Apache Drill and Apache Superset
💡 You can read more here.
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How do you manage scheduled tasks?
Its a bit overkill but i use Airflow with local executor.
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Twitter Data Pipeline with Apache Airflow + MinIO (S3 compatible Object Storage)
To learn more about it, I built a Data Pipeline that uses Apache Airflow to pull Elon Musk tweets using the Twitter API and store the result in a CSV stored in a MinIO (OSS alternative to AWS s3) Object Storage bucket.
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Data Analytics at Potloc I: Making data integrity your priority with Elementary & Meltano
Airflow
- self hosted Alternative to easycron.com?
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Azure OAuth CSRF State Not Equal Error
I am currently having a problem with trying to enable Azure OAuth to authenticate into our airflow instance. I have posted in countless other places trying to get answers so this is my next place I am trying. Here is the link to the discussion I posted within the airflow repo: https://github.com/apache/airflow/discussions/28098 but I will also do the liberty of posting it here as well. If anybody has any knowledge or can help I would greatly appreciate it as I have been dealing with this for over a month with no answers.
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ETL tool
Airflow is really popular, started at Airbnb. Pros: huge community, super mature. Cons: generic workflow orchestration, not the best for handling only data, hard to scale and maintain.
Apache Camel
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Why messaging is much better than REST for inter-microservice communications
This reminds me more of Apache Camel[0] than other things it's being compared to.
> The process initiator puts a message on a queue, and another processor picks that up (probably on a different service, on a different host, and in different code base) - does some processing, and puts its (intermediate) result on another queue
This is almost exactly the definition of message routing (ie: Camel).
I'm a bit doubtful about the pitch because the solution is presented as enabling you to maintain synchronous style programming while achieving benefits of async processing. This just isn't true, these are fundamental tradeoffs. If you need a synchronous answer back then no amount of queuing, routing, prioritisation, etc etc will save you when the fundamental resource providing that is unavailable, and the ultimate outcome that your synchronous client now hangs indefinitely waiting for a reply message instead of erroring hard and fast is not desirable at all. If you go into this ad hoc, and build in a leaky abstraction that asynchronous things are are actually synchronous and vice versa, before you know it you are going to have unstable behaviour or even worse, deadlocks all over your system and the worst part - the true state of the system is now hidden in which messages are pending in transient message queues everywhere.
What really matters here is to fundamentally design things from the start with patterns that allow you to be very explicit about what needs to be synchronous vs async (building on principles of idempotency, immutability, coherence, to maximise the cases where async is the answer).
The notion of Apache Camel is to make all these decisions a first class elements of your framework and then to extract out the routing layer as a dedicated construct. The fact it generalises beyond message queues (treating literally anything that can provide a piece of data as a message provider) is a bonus.
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S3 to S3 transform
For a simple sequential Pipeline, my goto would be Apache Camel. As soon as you want complexity its either Apache Nifi or a micro service architecture.
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🗞️ We have just released our JBang! catalog 🛍️
🐪 Apache Camel : Camel JBang, A JBang-based Camel app for easily running Camel routes.
- 7GUIs of Java/Object Oriented Design?
- Message broker as service integrator
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Apache Airflow 2.3.0 is out !
Sounds like Camel.
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Open source Java projects
Camel
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What tools to use for small in house applications?
If you need to stick with spreadsheets I agree with the suggestion of Python--or Java, I used to automate a bunch of business processes with Apache Camel.
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Im making a FME open source clone
Or if you are looking for something light-weighter you can always use Camel camel.apache.org
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Steps to upgrade spring-boot 1.x to 2.x
apache camel dependency on spring boot, Kafka etc, also other libs dependencies Note: Kafka 1.1: https://mvnrepository.com/artifact/org.apache.camel/camel-kafka/2.22.4 kafka 2.0 : https://mvnrepository.com/artifact/org.apache.camel/camel-kafka/2.23.1 https://github.com/apache/camel/blob/master/components/camel-kafka/src/main/docs/kafka-component.adoc
What are some alternatives?
Kedro - A Python framework for creating reproducible, maintainable and modular data science code.
dagster - An orchestration platform for the development, production, and observation of data assets.
luigi - Luigi 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.
n8n - Free and source-available fair-code licensed workflow automation tool. Easily automate tasks across different services.
Dask - Parallel computing with task scheduling
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
airbyte - Data integration platform for ELT pipelines from APIs, databases & files to warehouses & lakes.
Apache Kafka - Mirror of Apache Kafka
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
argo - Workflow engine for Kubernetes
Apache Pulsar - Apache Pulsar - distributed pub-sub messaging system
Apache Arrow - Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing