apache spark 2019


Apache Spark is an open source parallel processing framework for running large-scale data analytics applications across clustered computers Apache Spark is an open-source distributed general-purpose cluster-computing framework. Originally developed at the University of California, Berkeley’s AMPLab,

Processing Large Raster and Vector Data in Apache Spark
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Spatial data processing frameworks in many cases are limited to vector data only. However, an important type of spatial data is raster data which is produced by sensors on satellites but also by high resolution cameras taking pictures of nano structures, such as chips on wafers

Geospatial Data Management in Apache Spark : A Tutorial
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The volume of spatial data increases at a staggering rate. This tutorial comprehensively studies how existing works extend Apache Spark to uphold massive-scale spatial data. During this 1.5 hour tutorial, we first provide a background introduction of the characteristics

ARFF data source library for distributed single/multiple instance, single/multiple output learning on Apache Spark
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Apache Spark has become a popular framework for distributed machine learning and data mining. However, it lacks support for operating with Attribute-Relation File Format (ARFF) files in a native, convenient, transparent, efficient, and distributed way. Moreover, Spark





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