Essential PySpark for data analytics a beginner's guide to harnessing the power and ease of PySpark 3.0
Get started with distributed computing using PySpark, a single unified framework to solve end-to-end data analytics at scale Key Features Discover how to convert huge amounts of raw data into meaningful and actionable insights Use Spark's unified analytics engine for end-to-end analytics, from...
| Otros Autores: | |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Birmingham, England ; Mumbai :
Packt
[2021]
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| Edición: | 1st edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009635717106719 |
Tabla de Contenidos:
- Table of Contents Distributed Computing Primer Data Ingestion Data Cleansing and Integration Real-time Data Analytics Scalable Machine Learning with PySpark Feature Engineering – Extraction, Transformation, and Selection Supervised Machine Learning Unsupervised Machine Learning Machine Learning Life Cycle Management Scaling Out Single-Node Machine Learning Using PySpark Data Visualization with PySpark Spark SQL Primer Integrating External Tools with Spark SQL The Data Lakehouse.
