Qihoo360/hbox

Health v2 · maintenance only

Adoption not part of the score

1727 stars · 383 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Hbox (formerly XLearning) is a scheduling platform that runs machine learning and deep learning frameworks like TensorFlow, MXNet, Caffe, and PyTorch on Hadoop YARN clusters. It provides GPU resource scheduling, HDFS-based unified data management, Docker container support, and a RESTful API management interface.

Use cases

• run distributed TensorFlow training on a Hadoop YARN cluster
• schedule GPU resources for deep learning jobs alongside big data workloads
• train models using HDFS-stored data with multiple input strategies
• run PyTorch or MXNet training jobs in Docker containers on YARN
• manage deep learning training jobs via a RESTful API
• share a cluster between Spark/MapReduce and deep learning workloads

When to choose

• you already operate a Hadoop YARN cluster and want to run deep learning training on it
• you need GPU-aware scheduling mixed with big data jobs
• you want unified HDFS-based data management for training data and model outputs

When to avoid

• you run a Kubernetes-based ML platform (use Kubeflow or similar instead)
• you need a modern cloud-native scheduler without Hadoop dependencies
• your training is single-node and needs no cluster scheduling

Facets

application · maturity maintenance

scheduling machine-learning deep-learning workflow-automation gpu-computing machine-learning deep-learning big-data microservices artificial-intelligence jvm self-hosted hadoop-yarn tensorflow mxnet caffe pytorch gpu-scheduling hdfs distributed-training resource-management linux docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="Qihoo360/hbox")