Analysis of Community Interactions using Spark GraphX

Analysis of Community Interactions using Spark GraphX

The goal of this spark project is to analyse the level and strength of interactions across areas of coverage of a telecom provider between different areas in the city of Milan.
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What will you learn

Introduction to Graphs and why are they essential
Simple Graphs, BIpirate Graphs, Directed, Undirected graphs, Multi Graphs and Property Graphs
Understanding Apache Spark
Understanding Hadoop MapReduce framework
Introduction to Spark GraphX
Visualizations restrictions related to Spark GraphX
The use case for Graph storage and Graph processing
Building a graph structure from our dataset
Downloading the dataset and performing basic EDA
Visualizing edges and nodes of the graph by writing queries in Scala
Use of Spark GraphX graph operators
Analysis of graph using GraphX
Exploring functions and features of Spark GraphX
Performing parallel algorithmic computing like page rank on Graph using GraphX

Project Description

For all telecommunication providers, using the call details record (CDR), it is quite easy to measure the level and strength of interaction across areas of coverage. Such measurement enables the providers to make further decisions regarding sales, promotions and engineering details to improve the quality of service amongst other things.

In this spark graphx project, we will be doing an analysis of the level and strength of interactions between different areas in the city of Milan. Our dataset for this big data project include datasets from Dandelion Open big data website which contains aggregated anonymized call records based on the calls exchanged between Telecom Italia Mobile users.

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Curriculum For This Mini Project

03h 33m
01h 49m