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Data aggregation pipeline for running real-time predictive models

Project description

Blurr

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Table of contents

What is Blurr?

Blurr transforms structured, streaming raw data into features for model training and prediction using a high-level expressive YAML-based language called the Blurr Transform Spec (BTS). The BTS merges the schema and computation model for data processing.

The BTS is a data transform definition for structured data. The BTS encapsulates the business logic of data transforms and Blurr orchestrates the execution of data transforms. Blurr is runner-agnostic, so BTSs can be run by event processors such as Spark, Spark Streaming or Flink.

Is Blurr for you?

Yes, if: you are well on your way on the ML 'curve of enlightenment', and are thinking about how to do online scoring

Curve

Playground

Launch playground

Tutorial and Docs

Coming up with features is difficult, time-consuming, requires expert knowledge. 'Applied machine learning' is basically feature engineering --- Andrew Ng

Read the docs

Streaming BTS Tutorial | Window BTS Tutorial

Preparing data for specific use cases using Blurr:

Contribute to Blurr

Welcome to the Blurr community! We are so glad that you share our passion for building MLOps!

Please create a new issue to begin a discussion. Alternatively, feel free to pick up an existing issue!

Please sign the Contributor License Agreement before raising a pull request.

Data Science 'Joel Test'

Inspired by the (old school) Joel Test to rate software teams, here's our version for data science teams. What's your score?

  1. Data pipelines are versioned and reproducible
  2. Pipelines (re)build in one step
  3. Deploying to production needs minimal engineering help
  4. Successful ML is a long game. You play it like it is
  5. Kaizen. Experimentation and iterations are a way of life

Roadmap

Blurr is currently in Developer Preview. Stay in touch!: Star this project or email hello@blurr.ai

  • Local transformations only
  • Support for custom functions and other python libraries in the BTS
  • Spark runner
  • S3 support for data sink
  • DynamoDB as an Intermediate Store
  • Features server

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