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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware -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 graphframes and see how to optimize your PySpark SQL code.APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 348 pp. Englisch.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 graphframes and see how to optimize your PySpark SQL code.PySpark SQL Recipes starts with recipes on creating dataframes from different types of data source, data aggregation and summarization, and exploratory data analysis using PySpark SQL. You'll also discover how to solve problems in graph analysis using graphframes.On completing this book, you'll have ready-made code for all your PySpark SQL tasks, including creating dataframes using data from different file formats as well as from SQL or NoSQL databases.What You Will LearnUnderstand PySpark SQL and its advanced featuresUse SQL and HiveQL with PySpark SQLWork with structured streamingOptimize PySpark SQLMaster graphframes and graph processingWho This Book Is ForData scientists, Python programmers, and SQL programmers. 348 pp. Englisch.
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Explains PySpark SQL and Dataframe in detailInclude IO operation using  PySpark SQL from  most frequently used SQL and NoSQL databasesDetail discussion on  Data Preprocessing  usin.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. PySpark SQL Recipes | With HiveQL, Dataframe and Graphframes | Sundar Rajan Raman (u. a.) | Taschenbuch | xxiv | Englisch | 2019 | Apress | EAN 9781484243343 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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 graphframes and see how to optimize your PySpark SQL code.PySpark SQL Recipes starts with recipes on creating dataframes from different types of data source, data aggregation and summarization, and exploratory data analysis using PySpark SQL. You'll also discover how to solve problems in graph analysis using graphframes.On completing this book, you'll have ready-made code for all your PySpark SQL tasks, including creating dataframes using data from different file formats as well as from SQL or NoSQL databases.What You Will LearnUnderstand PySpark SQL and its advanced featuresUse SQL and HiveQL with PySpark SQLWork with structured streamingOptimize PySpark SQLMaster graphframes and graph processingWho This Book Is ForData scientists, Python programmers, and SQL programmers.