TensorFlowOnSpark and tensorflow_scala

These are complements: TensorFlowOnSpark provides distributed training infrastructure on Spark clusters while tensorflow_scala provides the language bindings to write TensorFlow code in Scala, and they can be used together to build Scala-based distributed ML pipelines.

TensorFlowOnSpark
69
Established
tensorflow_scala
38
Emerging
Maintenance 0/25
Adoption 19/25
Maturity 25/25
Community 25/25
Maintenance 0/25
Adoption 10/25
Maturity 9/25
Community 19/25
Stars: 3,859
Forks: 941
Downloads: 11,238
Commits (30d): 0
Language: Python
License: Apache-2.0
Stars: 941
Forks: 94
Downloads: —
Commits (30d): 0
Language: Scala
License: Apache-2.0
Stale 6m No Dependents
Stale 6m No Package No Dependents

About TensorFlowOnSpark

yahoo/TensorFlowOnSpark

TensorFlowOnSpark brings TensorFlow programs to Apache Spark clusters.

Enables distributed TensorFlow training and inference across Spark/Hadoop clusters by launching TensorFlow workers on executors with support for both HDFS-native data reads and Spark RDD pushdown via `TFNode.DataFeed`. Supports synchronous/asynchronous training, model/data parallelism, and server-to-server direct communication, requiring minimal code changes to existing TensorFlow programs while integrating seamlessly into Spark data pipelines.

About tensorflow_scala

eaplatanios/tensorflow_scala

TensorFlow API for the Scala Programming Language

Related comparisons

TensorFlowOnSpark and stensorflow

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