lithops
pyspark-on-aws-emr
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| lithops | pyspark-on-aws-emr | |
|---|---|---|
| 2 | 1 | |
| 306 | 24 | |
| 3.6% | - | |
| 9.5 | 3.6 | |
| 3 days ago | almost 2 years ago | |
| Python | Python | |
| 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.
lithops
- Lithops: A multi-cloud framework for embarrassingly parallel jobs
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[D] For those of you who don't own a GPU, how do you run your experiments or train your models?
At work for non-ML/non-GPU stuff I've been using Lithops for running code on dynamically-provisioned cloud resources (serverless or VM). It pickles your code & runtime variables, sends them to cloud storage, runs the code & downloads the results, all relatively transparently. You're just calling Python functions with Python objects on your local computer and not having to worry about deploying your code, packaging your data, etc. Better still, you can scale up for things like hyperparameter sweeps by just dispatching more calls in parallel, and it will provision more resources.
pyspark-on-aws-emr
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Data Engineering Projects for Beginners
Building Big Data Pipelines in the Cloud with AWS EMR
What are some alternatives?
secrets-env - Extension to the crystal lang ENV module to support reading secrets
docker-livy - Dockerizing and Consuming an Apache Livy environment
treequeues - High performance queues for pytree objects.
TypedPyspark - Type-annotate your spark dataframes and validate them
demo-code - Bits of code I use during live demos
Traffic-Data-Analysis-with-Apache-Spark-Based-on-Mobile-Robot-Data - Mobile robot data were analyzed with Apache-Spark to extract five different statistical result such as travel time, waiting time, average speed, occupancy and density were produced.
livyc - Apache Spark as a Service with Apache Livy Client
IDEA - Text Data Visualizer with Django
pyspark-starter - Starter pyspark code with a working combination of all versions
Dropout-Students-Prediction - The goal of this project is to identify students at risk of dropping out the school
recommendation-system - Build a Content-Based Movie Recommender System (TF-IDF, BM25, BERT)
data-engineering-challenge-th - Dockerizing a Python Script for Web Scraping and consume the scraped data using FastApi (www.metroscubicos.com)