- Author: John T. Wolohan | ISBN-10: 1617296236 | Year: 2020 | Pages: 350 | Language: English | File size: 19.3 MB
- Book Description:
- Modern data science solutions need to be clean, easy to read, and scalable. In Mastering Large Datasets with Python, author J.T. Wolohan teaches you how to take a small project and scale it up using a functionally influenced approach to Python coding. You’ll explore methods and built-in Python tools that lend themselves to clarity and scalability, like the high-performing parallelism method, as well as distributed technologies that allow for high data throughput. The abundant hands-on exercises in this practical tutorial will lock in these essential skills for any large-scale data science project.
What You’ll Learn
- Chunk large problems into small pieces
- Use the map and reduce functiosn
- Run programs in parallel on your personal computer
- Run programs in parallel in distributed cloud environments
Who This Book Is For:
Developer or data scientist who knows enough to have gotten themselves into a situation where they’re facing a problem caused by having to much data.
![Hands-On Big Data Analytics with PySpark [2019]](https://sachit.net/wp-content/uploads/2019/05/bigdata.png "Hands-On Big Data Analytics with PySpark [2019]")
