{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/3"},{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/7"},{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/4"},{"label":"Build Tools","url":"https://skillfed.io/packages/category/software-development-build-tools/2"},{"label":"Information Analysis","url":"https://skillfed.io/packages/category/scientific-engineering-information-analysis"},{"label":"Linguistic","url":"https://skillfed.io/packages/category/text-processing-linguistic"},{"label":"Internationalization","url":"https://skillfed.io/packages/category/software-development-internationalization"},{"label":"Localization","url":"https://skillfed.io/packages/category/software-development-localization"}],"enrichment":{"capability":"Spark NLP provides distributed natural language processing on Apache Spark, offering pretrained pipelines and models for tokenization, named entity recognition, sentiment analysis, machine translation, and embeddings across multiple languages.","skillfed_tags":["distributed-nlp","spark-ml","transformers"],"use_cases":["Build production NLP pipelines that scale across Spark clusters for large-scale text processing","Extract named entities, perform sentiment analysis, or classify documents using pretrained models","Translate text between languages or generate summaries and answers from documents","Integrate transformer models into Spark ML workflows for feature engineering","Process multilingual text data in a single distributed pipeline"],"what_it_does":"Spark NLP is a natural language processing library built on top of Apache Spark that brings NLP and machine learning to distributed environments. It provides access to pretrained pipelines and models across multiple languages, supporting tasks like tokenization, part-of-speech tagging, named entity recognition, sentiment analysis, machine translation, question answering, and text generation. The library integrates state-of-the-art transformer models and can import models from TensorFlow, ONNX, and OpenVINO frameworks.\n\nThe package is designed for production use and scales across distributed Spark clusters. It supports multiple programming languages through the JVM ecosystem and offers specialized variants for GPU acceleration, Apple Silicon, and AArch64 architectures. The library requires Java 8 or 11 and Apache Spark 3.0 or later.","worth_installing":"Yes, if you need production-grade NLP at scale on Spark. The library is actively maintained with no security vulnerabilities and offers a comprehensive suite of pretrained models and tasks. Install only if you already have Apache Spark 3.0+ and Java 8 or 11 in your environment; it is not suitable for lightweight single-machine NLP work."},"id":"spark-nlp","links":{"html":"https://skillfed.io/packages/spark-nlp","md":"https://skillfed.io/packages/spark-nlp.md","pypi":"https://pypi.org/project/spark-nlp/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-06-24","license_spdx":null,"license_treatment":"permissive","name":"spark-nlp","python_support":"unspecified","summary":"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."},"popularity":{"monthly_downloads":1180010,"position":4260,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"6.4.2"}