Hacker News
It's a good example of statistic and analytic problems. Here we are trying to grab a ton of data from Google Cloud and calculate some stats values. Stairs will make calculations in parallel way.
The idea to grab some data from Google Cloud about Hacker News post
and calculate different values based on threads topics. You will find
some tips about batch_producer, pipelines configs and general information
about Stairs components.
Kaggle to Github
This project is about parsing and how stairs could help you
extract data from any source.
The main goal is to parse kaggle competitions and link them to github repositories (which were mentioned inside)
In this example you can see all power of Flow components and data pipelines itself.
Note: we are considering to make some pipelines compatible with python async, which will improve experience with such tasks/projects.
Bag of words
Is basic example of ML algorithms for solving text/nlp problems. You can find a very good example of this task on kaggle pages:
https://www.kaggle.com/c/word2vec-nlp-tutorial
There is a well build dataset and get started guide on solving this problem.
Here we have an example of how stairs could help on solving ML related tasks. The amount of data is not very big here and it's not very related to "streaming" idealogy, but it's a good example how ML playground could instantly became a production ready enviroment, it's always easy to tune and change the logic and it's always ready for big amount of data.