| Mastering Large Datasets with Python (Manning) |
| Friday, 31 January 2020 | |||
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In this book, subtitled "Parallelize and Distribute Your Python Code", author J.T. Wolohan shows how to take a small project and scale it up using a functionally influenced approach to Python coding. The book explores 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 book explores tools like Hadoop and PySpark to efficiently process massive distributed datasets, speeding up decision-making with machine learning, and simplifying data storage with AWS S3 <ASIN:1617296236> . Author: J.T. Wolohan
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