PySpark — An Effective ETL Tool?
Many of you may be curious about ETL Tools and the use of the ETL process in the world of data hubs where data plays a significant role. Today, we will examine this more closely.
What is ETL?
ETL (which stands for Extraction, Transform and Load) is the generic process of extracting data from one or more systems and loading it into a data warehouse or databases after performing some intermediate transformations.
There are many ETL tools available in the market that can carry out this process.
A standard ETL tool like PySpark, supports all basic data transformation features like sorting, mapping, joins, operations, etc. PySpark’s ability to rapidly process massive amounts of data is a key advantage.
Some tools perform a complete ETL implementation while some tools help us create a custom ETL process from scratch, and there are a few those fall somewhere in between. Before going into the detail of PySpark, let’s first understand some important features that an ETL tool should have.
