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Liikennedata project for collecting Tampereen Kaupungin Liikenne bus position data.

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Liikennedata

Liikennedata project in Big Data spirit.

Liikennedata high-level architecture

Guiding Principles

  • Everything is open source, published in GitHub.
  • The data storage instance is deployed in Cybercom Cloud.
  • The data storage instance is a normal JSON/HTTP client to Siri Access.
  • The data storage instance stores the data to Hadoop.
  • Hadoop uses a managed volume in Cybercom Cloud to store the massive amount of data.
  • The frontend is scalable through Nginx load balancing.
  • The backend is scalable through Hadoop distribution and general caching.
  • There is a public read/query access to Hadoop for researchers.
  • There is a public web UI for easy use.
  • There is a public interface for REST queries to Data Views Service.
  • Data is provisioned through efficient views that provide cached, real-time, precomputed and aggregated parametrized views to the data.
  • Each view has relevant windowing limits; larger summarizations of data can only be accessed through views specialized for large history summarizations (pre-computed, pre-rasterized).
  • Redis is used as a rich cache for current data to enable real-time views and summaries.

Link to the internal wiki: https://confluence.cybercom.com/display/FIBDTF/FI+-+Liikennedata+Home

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Liikennedata project for collecting Tampereen Kaupungin Liikenne bus position data.

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