faust
beam
faust | beam | |
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11 | 30 | |
1,454 | 7,519 | |
2.1% | 0.9% | |
7.9 | 10.0 | |
about 1 month ago | 8 days ago | |
Python | Java | |
GNU General Public License v3.0 or later | 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.
faust
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faust VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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New release of FastKafka supporting Redpanda
We have many similar ideas and paradigms, as one would expect from modern frameworks tackling the same problem. However, Faust has been deprecated and no longer managed or supported (there is a fork being maintained by the community at https://github.com/faust-streaming/faust). I guess Robinhood at some point decided not to spend any more resources on it, an often destiny of such side projects by large corporations. On the other hand, we hope to stay around for a long time and build to a framework and a community that loves it. This initial version was built using many libraries in order to have a working system and to gather feedback from the large community. We plan to replace eventually all, or at least most of dependancies, and replace then with Rust lib with Python bindings.
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Kafka ETL tool, is there any?
Just wanted to add that there is an actively maintained fork called faust-streaming, you can find it here: https://github.com/faust-streaming/faust
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Apache Kafka Beyond the Basics: Windowing
That's the basics yes. You have a pletora of things coming next. One is "Windowing" mentioned in the article, it's well explained and maybe it looks simple, but when you start with it, takes some time to wrap your mind around it.
The other things in kafka world are stateful transformations, which you would normally do using Java's Flink. The closest in python is Faust (the fork) [0]. What are stateful aggregations? something like doing SQL on top of a topic: group_by, count, reduce, and joins. So similar to SQL that you have kSQL [1].
Consumer groups IMO falls under basic usage, if you need to scale, take a look at it, and what are partitions and replicas, with that in mind, you'll be ok.
[0]: https://github.com/faust-streaming/faust
[1]: https://www.confluent.io/blog/ksql-streaming-sql-for-apache-...
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How to join using Faust Streaming (Python implementation of Kafka Streams API)?
The forked one, https://github.com/faust-streaming/faust, has been updated but still doesn’t seem to support joins.
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Real Time Data Infra Stack
Faust: Python framework
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Kafka to HTTP POST requests
I’d like to use Python for this so I came across Faust but I’m not sure if it’s possible to create HTTP requests through Faust or if there are better alternatives.
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Using Kafka with Python... is Confluent the only option?
There is a community fork which was stale for a while but got a new commit a couple days ago, this one might be usable, but is still quite risky (70 open issues etc.): https://github.com/faust-streaming/faust
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Why did Robinhood abandon Faust?
There is a community which forked and actively develops faust, here’s the https://github.com/faust-streaming/faust
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Project with Faust and Django
Hi, thanks for the answer, I'm actually using virtualenv with the requirements of the file associated with the example. However I wanted to tell you that due to covid the project is suspended but only temporarily, but there is an active fork https://github.com/faust-streaming/faust. But the example in the fork doesn't work either.
beam
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Ask HN: Does (or why does) anyone use MapReduce anymore?
The "streaming systems" book answers your question and more: https://www.oreilly.com/library/view/streaming-systems/97814.... It gives you a history of how batch processing started with MapReduce, and how attempts at scaling by moving towards streaming systems gave us all the subsequent frameworks (Spark, Beam, etc.).
As for the framework called MapReduce, it isn't used much, but its descendant https://beam.apache.org very much is. Nowadays people often use "map reduce" as a shorthand for whatever batch processing system they're building on top of.
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beam VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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How do Streaming Aggregation Pipelines work?
Apache Beam is one of many tools that you can use
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Releasing Temporian, a Python library for processing temporal data, built together with Google
Flexible runtime ☁️: Temporian programs can run seamlessly in-process in Python, on large datasets using Apache Beam.
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Kafka cluster loses or duplicates messages
To perform the tests I'm using a Kafka cluster on Kubernetes from the Beam repo (here).
- Apache Beam
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Real Time Data Infra Stack
Apache Beam: Streaming framework which can be run on several runner such as Apache Flink and GCP Dataflow
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Google Cloud Reference
Apache Beam: Batch/streaming data processing 🔗Link
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Composer out of resources - "INFO Task exited with return code Negsignal.SIGKILL"
What you are looking for is Dataflow. It can be a bit tricky to wrap your head around at first, but I highly suggest leaning into this technology for most of your data engineering needs. It's based on the open source Apache Beam framework that originated at Google. We use an internal version of this system at Google for virtually all of our pipeline tasks, from a few GB, to Exabyte scale systems -- it can do it all.
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Pub/Sub parallel processing best practices
That being said, there is a learning curve in understanding how Apache Beam works. Take a look at the beam website for more information.
What are some alternatives?
Memgraph - Open-source graph database, tuned for dynamic analytics environments. Easy to adopt, scale and own.
Apache Arrow - Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing
redis-om-python - Object mapping, and more, for Redis and Python
Apache Hadoop - Apache Hadoop
aioredis - asyncio (PEP 3156) Redis support
Scio - A Scala API for Apache Beam and Google Cloud Dataflow.
arq - Fast job queuing and RPC in python with asyncio and redis.
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
Faust - Python Stream Processing
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
debezium - Change data capture for a variety of databases. Please log issues at https://issues.redhat.com/browse/DBZ.
Apache Hive - Apache Hive