This application consists of a simple pipeline to perform a data migration. It takes CSV files with specific schemas as input and inserts the content into hive tables in AVRO format. It uses PySpark and Airflow throughout the process.

The data will be stored using Hive-Hadoop. The 3 tables used for the migration can be created with the scripts contained in the folder create_table_scripts.

The pipeline runs on Airflow. A Spark Operator takes care of reading the data from CSV files. It performs a data types check, and after confirming the compatibility, the data is inserted into the corresponding tables.

The pipeline runs every day at 12 noon. It checks for new files in the folder input/. After reading each file, if the file data types were compatible and the data was inserted, the file is moved to the folder processed/. On the other hand, if the file data types were incorrect, the file is moved to the folder skipped.

• Pyspark
• SQL
• Hadoop
• Airflow
• CSV
• AVRO