PySpark SQL Recipes : With HiveQL, Dataframe and Graphframes

PySpark SQL Recipes With HiveQL, Dataframe and Graphframes

Carry out data analysis with PySpark SQL, graphframes, and graph data processing using a problem-solution approach. This book provides solutions to problems related to dataframes, data manipulation summarization, and exploratory analysis. You will improve your skills in graph data analysis using gra...

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Detalles Bibliográficos
Autores principales: Mishra, Raju Kumar. author (author), Raman, Sundar Rajan. author
Formato: Libro electrónico
Idioma:Inglés
Publicado: Berkeley, CA : Apress 2019.
Edición:1st ed. 2019.
Materias:
Big data.
Open source software.
Computer programming.
Python (Computer program language).
Programming languages (Electronic computers).
Big Data.
Open Source.
Python.
Programming Languages, Compilers, Interpreters.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630659606719
Tabla de Contenidos:
  • Chapter 1: Introduction to PySparkSQL
  • Chapter 2: Some time with Installation
  • Chapter 3: IO in PySparkSQL
  • Chapter 4 : Operations on PySparkSQL DataFrames
  • Chapter 5 : Data Merging and Data Aggregation using PySparkSQL
  • Chapter 6: SQL, NoSQL and PySparkSQL
  • Chapter 7: Structured Streaming
  • Chapter 8 : Optimizing PySparkSQL
  • Chapter 9 : GraphFrames.

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