John Snow Labs Spark-NLP is a natural language processing library built on top of Apache Spark ML. It provides simple, performant & accurate NLP annotations for machine learning pipelines, that scale easily in a distributed environment.

take a look at our official spark-nlp page: http://nlp.johnsnowlabs.com/ for user documentation and examples

This library has been uploaded to the spark-packages repository https://spark-packages.org/package/JohnSnowLabs/spark-nlp .

To use the most recent version just add the --packages JohnSnowLabs:spark-nlp:1.0.0 to you spark command

spark-shell --packages JohnSnowLabs:spark-nlp:1.2.1

pyspark --packages JohnSnowLabs:spark-nlp:1.2.1

spark-submit --packages JohnSnowLabs:spark-nlp:1.2.1

Check the package for the published versions if you want to use and old version.

If you have a scala project which has a dependency on spark-nlp you can resolve it using our bintray repository

Using sbt 0.13.6+

resolvers += Resolver.bintrayRepo("johnsnowlabs", "johnsnowlabs")

For sbt versions before 0.13.6, you need to include the sbt-bintray plugin in your project: https://github.com/sbt/sbt-bintray.

After you can add the resolver as before

resolvers += Resolver.bintrayRepo("johnsnowlabs", "johnsnowlabs")

If for some reason you need to use the jar, you can download the jar from the project's website: http://nlp.johnsnowlabs.com/

From there you can use it in your project setting the --classpath

To add jars to spark programs use the --jars option

spark-shell --jars spark-nlp.jar

The preferred way to use the library when running spark programs is using the --packages option as specified in the spark-packages section.

We appreciate any sort of contributions:

• ideas
• feedback
• documentation
• bug reports
• nlp training and testing corpora
• development and testing

Clone the repo and submit your pull-requests! Or directly create issues in this repo.

[email protected]

http://johnsnowlabs.com/