3 documents found

Proceedings
CC BY-NC-ND 4.0
2017

Advances in Database Technology - EDBT 2017 : 20th International Conference on ...

Konstanz: University of Konstanz, University Library, 2017
Article / Chapter
CC BY-NC-ND 4.0
2017

Efficient spatio-temporal event processing with STARK

For Big Data processing, Apache Spark has been widely accepted. However, when dealing with events or any other spatio-temporal data sets, Spark becomes very inefficient as it does not include any spatial or temporal data types and operators. In this paper we demonstrate our STARK project that adds the...
Konstanz: University of Konstanz, University Library, 2017
Article / Chapter
CC BY-NC-ND 4.0
2017

Big spatial data processing frameworks: feature and performance evaluation

Nowadays, a vast amount of data is generated and collected every moment and often, this data has a spatial and/or temporal aspect. To analyze the massive data sets, big data platforms like Apache Hadoop MapReduce and Apache Spark emerged and extensions that take the spatial characteristics into account...
Konstanz: University of Konstanz, University Library, 2017