Big Data analytics with PySpark (Apache Spark and Python)

A course for leveraging the power of Python and putting it to use in the(Apache spark architecture) Spark ecosystem.



About Course


PySpark helps data scientists interface with Resilient Distributed Datasets in apache spark and python.Py4J is a popularly library integrated within PySpark that lets python interface dynamically with JVM objects (RDD's).  In this course you'll learn how to use Spark from Python! Spark is a tool for doing parallel computation with large datasets and it integrates well with Python. PySpark is the Python package that makes the magic happen. You'll use this package to work with some live example. You'll learn to wrangle this data and build a whole machine learning pipeline to predict results. Get ready to put some Spark in your Python code and dive into the world of high performance machine learning! 

Apache Spark is a fast cluster computing framework which is used for processing, querying and analyzing big data. Being based on in-memory computation, it has an advantage over several other big data frameworks.





Highlights

Comments