tensorframes (homepage)

Tensorflow wrapper for DataFrames on Apache Spark

@databricks / (0)

TensorFrames (TensorFlow on Spark Dataframes) lets you manipulate Spark's DataFrames with TensorFlow programs.
This package provides Python bindings, a Scala DSL and a small runtime to express and run TensorFlow computation graphs.


Tags

  • 1|tensorflow

How to

Include this package in your Spark Applications using:

spark-shell, pyspark, or spark-submit

> $SPARK_HOME/bin/spark-shell --packages databricks:tensorframes:0.2.3-s_2.10

sbt

If you use the sbt-spark-package plugin, in your sbt build file, add:

spDependencies += "databricks/tensorframes:0.2.3-s_2.10"

Otherwise,

resolvers += "Spark Packages Repo" at "http://dl.bintray.com/spark-packages/maven"

libraryDependencies += "databricks" % "tensorframes" % "0.2.3-s_2.10"

Maven

In your pom.xml, add:
<dependencies>
  <!-- list of dependencies -->
  <dependency>
    <groupId>databricks</groupId>
    <artifactId>tensorframes</artifactId>
    <version>0.2.3-s_2.10</version>
  </dependency>
</dependencies>
<repositories>
  <!-- list of other repositories -->
  <repository>
    <id>SparkPackagesRepo</id>
    <url>http://dl.bintray.com/spark-packages/maven</url>
  </repository>
</repositories>

Releases

Version: 0.2.3-s_2.10 ( 58737c | zip | jar ) / Date: 2016-07-15 / License: Apache-2.0 / Scala version: 2.10