Big Data Real-Time Clickstream Data Ingestion Paradigm for E-Commerce Analytics

Gautam Pal, Gangmin Li, Katie Atkinson

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

3 Citations (Scopus)

Abstract

E-Commerce websites track visitors browsing records to uncover their intent and preferences for effective online marketing. User clicks or clickstream is a series of page requests which generates a URL on each click event. Clickstream data is an information trail a user leaves behind while visiting websites. Click URLs can be graphically represented for clickstream reporting. In this work, we study Big Data real-Time clickstream data ingestion model in e-commerce Domain, which builds on top of standard Big Data tools like Kafka, Flume, Spark and Cassandra. In particular, we focus on high velocity, fault-tolerant streaming data acquisition pipelines in a distributed setup rather than mining and searching patterns in it.

Original languageEnglish
Title of host publication2018 4th International Conference for Convergence in Technology, I2CT 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538652329
DOIs
Publication statusPublished - Oct 2018
Event4th International Conference for Convergence in Technology, I2CT 2018 - Mangalore, India
Duration: 27 Oct 201828 Oct 2018

Publication series

Name2018 4th International Conference for Convergence in Technology, I2CT 2018

Conference

Conference4th International Conference for Convergence in Technology, I2CT 2018
Country/TerritoryIndia
CityMangalore
Period27/10/1828/10/18

Keywords

  • Clickstream
  • Flume
  • Kafka
  • Real-time data processing
  • Watermark

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