In this project we'll apply data modeling with Apache Cassandra and complete an ETL pipeline using Python. we will model Sparkify event data by creating in Apache Cassandra. The ETL pipeline that transfers data from a set of CSV files to create a streamline CSV file to model and insert data into Apache Cassandra tables.
- event_data/*.csv - csv files of user event sessions in the sparkify music app data which partitioned by day.
- data_modeling_with_cassandra.ipynb -
- ETL pipeline for pre-processing the files
- Apache Cassandra coding portion
- Give me the artist, song title and song's length in the music app history that was heard > during sessionId = 338, and itemInSession = 4
- Give me only the following: name of artist, song (sorted by itemInSession) and user (first and last name) for userid = 10, sessionid = 182
- Give me every user name (first and last) in my music app history who listened to the song 'All Hands Against His Own'
- pandas
- cassandra
- re
- os
- glob
- numpy
- json
- csv