# yahoo/CaffeOnSpark

Distributed deep learning on Hadoop and Spark clusters.

Repository: https://github.com/yahoo/CaffeOnSpark
Canonical: https://ross.abutalabs.com/products/caffeonspark
Language: Jupyter Notebook
License: Apache-2.0
License Family: permissive
Archived: true
Last push: 2019-11-15T21:44:39+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3887, "days_push": 2483, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, archived
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1261, forks 352 (observed 2026-08-28T04:04:10.049290+00:00)

## What it is
CaffeOnSpark is a Spark package that brings the Caffe deep learning framework to Hadoop and Spark clusters, enabling distributed neural network training, testing, and feature extraction on GPU/CPU servers. It lets Caffe users train models directly on HDFS datasets using existing LMDB files and minimally adjusted network configs.

## Use cases
- train deep learning models on a Hadoop cluster
- distributed neural network training with Spark
- run Caffe on HDFS data without conversion
- extract features from large image datasets on Spark
- scale deep learning across GPU servers with InfiniBand
- integrate deep learning into Scala Spark pipelines

## When to avoid
- you are starting a new project - the repo is archived and unsupported
- you prefer modern frameworks like TensorFlow, PyTorch, or Spark's own deep learning integrations
- you need active community support or recent updates

## Facets
- artifact type: library
- maturity: abandoned
- function: deep-learning, machine-learning, etl
- domain: deep-learning, big-data, machine-learning, microservices
- platform: jvm, cloud
- tags: spark, hadoop, caffe, distributed-training, hdfs, archived, linux, gpu

## Member repositories
- yahoo/CaffeOnSpark (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:10.049290+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T05:04:20.873568+00:00, confidence not recorded.
  - readme: https://github.com/yahoo/CaffeOnSpark (fetched 2026-08-28T04:04:10.049290+00:00, sha 262698c764c3)
- Data as of 2026-08-30T08:39:29.467469+00:00.