Apache Spark is an open source framework for efficient cluster computing with a strong interface for data parallelism and fault tolerance. The PySpark Cookbook presents effective and time-saving recipes for leveraging the power of Python and putting it to use in the Spark ecosystem.
You’ll start by learning the Apache Spark architecture and how to set up a Python environment for Spark. You’ll then get familiar with the modules available in PySpark and start using them effortlessly. In addition to this, you’ll discover how to abstract data with RDDs and DataFrames, and understand the streaming capabilities of PySpark. You’ll then move on to using ML and MLlib in order to solve any problems related to the machine learning capabilities of PySpark and use GraphFrames to solve graph-processing problems. Finally, you will explore how to deploy your applications to the cloud using the spark-submit command.
By the end of this book, you will be able to use the Python API for Apache Spark to solve any problems associated with building data-intensive applications.
Betal nemt med kort, Klarna, Apple Pay eller Google Pay. Ikke tilfreds? Du har altid 14 dages fortrydelsesret. Læs mere i vores vilkår. Har du spørgsmål, så send os en mail på hello@memmo.org.
Memmo gør det nemmere at studere – uanset hvor du er i verden. Hos os samler du dine kursusbøger og smarte studieværktøjer ét sted: resuméer, quizzer, podcasts og flashcards. Og så er der Ted, din studieven, der svarer på alt, du undrer dig over. Over 50 000 studerende studerer allerede her – bygget til at hjælpe dig med at lære hurtigere og stresse mindre.