Spark is an open-source cluster-computing framework that is built around speed, and streaming analytics. Used to process basically any kind of data (text files, parquet, HDFS, databases, s3, Avro ). Python is a general-purpose high-level programming language. It provides a wide range of libraries and is majority used for Data Science and Machine Learning.
” It is a python API for spark majority used for data analysis .”
“Using PySpark , you can work with Spark RDDs in python .”
“PySpark is used for analysis of big data “
“Java , Python and Scala can be used as the programming language. “
Advantage Spark With Python
- Python itself is very simple and easy but very effective. Spark with Python is very easy and simple to use.
- It makes API comprehensive and simple.
- Easy Readability and Maintenance.
- Python provides very options for Visualization. Other language is not provided as compared to python.
- Python has a wide range of libraries. Many libraries help with data analysis. ‘
- Active community.
- PySparks helps data scientist interface with RDDs in apache spark and Python through its library py4j.
Difference between PySpark and other Framework
- Real-Time: Real-time computation and in-memory computation.
- Deployment: Spark has its own cluster manager and is deployed through
