PySpark is a popular tool developed by the Apache community to combine Python with Spark for different uses. Moreover, an API of Python built for Apache Spark allows Python users to work closely with RDD.
PySpark is commonly used to build ETL pipelines and supports all the basic features of data transformation. These include sorting, joins, mapping, and many more.
PySpark is a distributed computing framework that supports large-scale data processing in real-time using a set of libraries. Also, PySpark enables us to build a tempView that doesn’t give up runtime performance.
PySpark and SQL both have some standard features. Some SQL keywords have an equivalent in PySpark utilizing the dot function.
There are many uses of PySpark as it is an API of Python. Also, Python is an easy-to-learn language that improves code readability and maintenance. Further, it is a combination of Python and Spark, which makes it more widespread.