Apache Spark's speed, ease of use, sophisticated analytics, and multilanguage support makes practical knowledge of this cluster-computing framework a required …
Get started with distributed computing using PySpark, a single unified framework to solve end-to-end data analytics at scaleKey FeaturesDiscover how …
Build data-intensive applications locally and deploy at scale using the combined powers of Python and Spark 2.0About This BookLearn why …
Build machine learning models, natural language processing applications, and recommender systems with PySpark to solve various business challenges. This book …
Written by the core Optimus team, this comprehensive guide will help you to understand how Optimus improves the whole data …
Migrate from pandas and scikit-learn to PySpark to handle vast amounts of data and achieve faster data processing time. This …
Think big about your data! PySpark brings the powerful Spark big data processing engine to the Python ecosystem, letting you …
Data Analysis with Python andPySpark is a carefully engineered tutorial that helps you use PySpark to deliver your data-driven applications …
The amount of data being generated today is staggering and growing. Apache Spark has emerged as the de facto tool …
Combine the power of Apache Spark and Python to build effective big data applications Key Features Perform effective data processing, …
Over 60 recipes for implementing big data processing and analytics using Apache Spark and Python
