PySpark Recipes A Problem-Solution Approach with PySpark2

Quickly find solutions to common programming problems encountered while processing big data. Content is presented in the popular problem-solution format. Look up the programming problem that you want to solve. Read the solution. Apply the solution directly in your own code. Problem solved! PySpark R...

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Detalles Bibliográficos
Autor principal:	Mishra, Raju Kumar. author (author)
Formato:	Libro electrónico
Idioma:	Inglés
Publicado:	Berkeley, CA : Apress 2018.
Edición:	1st ed. 2018.
Materias:	Big data. Computer programming. Programming languages (Electronic computers). Data mining. Big Data. Programming Techniques. Programming Languages, Compilers, Interpreters. Data Mining and Knowledge Discovery.
Ver en Biblioteca Universitat Ramon Llull:	https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630430306719

Tabla de Contenidos:

Chapter 1: The Era of Big Data, Hadoop, and Other Big Data Processing Frameworks
Chapter 2: Installation
Chapter 3: Introduction to Python and NumPy
Chapter 4: Spark Architecture and Resilient Distributed Dataset
Chapter 5: The Power of Pairs: Paired RDD
Chapter 6: IO in PySpark
Chapter 7: Optimizing PySpark and PySpark Streaming
Chapter 8: PySparkSQL
Chapter 9: PySpark MLlib and Linear Regression.

PySpark Recipes A Problem-Solution Approach with PySpark2

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