FITS Data Source for Apache Spark

An Apache Spark Implementation for Sentiment Analysis on Twitter Data

Sentiment Analysis on Twitter Data is a challenging problem due to the nature, diversity and volume of the data. In this work, we implement a system on Apache Spark, an open-source framework for programming with Big Data. The sentiment analysis tool is based on Machine Learning methodologies alongside with Natural Language Processing techniques and utilizes Apache Spark’s Machine learning libra...

Identifying the potential of Near Data Computing for Apache Spark

While cluster computing frameworks are continuously evolving to provide real-time data analysis capabilities, Apache Spark has managed to be at the forefront of big data analytics for being a unified framework for both, batch and stream data processing. There is also a renewed interest is Near Data Computing (NDC) due to technological advancement in the last decade. However, it is not known if ...

A comparison on scalability for batch big data processing on Apache Spark and Apache Flink

*Correspondence: [email protected] 1Department of Computer Science and Artificial Intelligence, CITIC-UGR (Research Center on Information and Communications Technology), University of Granada, Calle Periodista Daniel Saucedo Aranda, 18071 Granada, Spain Full list of author information is available at the end of the article Abstract The large amounts of data have created a need for new fram...

On the usability of Hadoop MapReduce, Apache Spark & Apache flink for data science

Distributed data processing platforms for cloud computing are important tools for large-scale data analytics. Apache Hadoop MapReduce has become the de facto standard in this space, though its programming interface is relatively low-level, requiring many implementation steps even for simple analysis tasks. This has led to the development of advanced dataflow oriented platforms, most prominently...

Getting Started with Apache Spark