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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Mishra, Raju Kumar (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berkeley, CA : Apress : Imprint: Apress, 2018.
Έκδοση:1st ed. 2018.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • 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.