Analyzing your data

GeoSpock provides you with a number of tools for analyzing the data you have ingested into the GeoSpock stack.


For an introduction, see Getting started with illumin8 .

illumin8 provides you with a set of tools that enable you to analyze your data, whilst dynamically updating the points on the map, the time trend chart and the statistics. It shows you the results of a multi-dimensional filter that, depending on your filter, can include:

  • a geographical bounding box
  • a time range
  • a time-of-day range
  • a selection of values from each of the properties in the dataset
  • a selection of geographical regions (choropleths)
  • geofences around Points of Interest (POI)


For an introduction, see Getting started with extrapol8 .

extrapol8 is available as both a Scala library and Python library that enables you to use Apache Spark for general analytics on a GeoSpock dataset.

The primary abstraction is a Spark dataset, with a schema that contains columns for:

  • latitude
  • longitude
  • time
  • (optionally) additional dataset-specific columns

extrapol8 gives you programmatic access to GeoSpock datasets to create bespoke data queries and extract source input data, using a library built on top of Apache Spark. You can load data from any geo-temporal region into an Apache Spark dataset in parallel and then explore your data using standard Spark constructs, including SQL.

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