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data-lakes-with-spark's Introduction

Summary of the project

The goal of this project is to develop an ETL pipeline tool for Sparkify that extracts song data from S3, transforms data into a set of dimensional tables using Spark, and loads the output files on S3 for an analytics team to continue finding insights in what songs their users are listening to.

Fact and Dimension table schema

Instruction to run the tool from python console

$ python etl.py

Code explaination

dwh.cfg - this file has all of the configuration settings in it (S3 storage information)
etl.py - this script file will load aws configuration, create a spark session, process song data, and log data to extract, transform, and load the output for additional analysis
etl.ipynb - this is a python notebook used during development; has sample code that can modified to test changes

data-lakes-with-spark's People

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