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    PySpark Cookbook. Over 60 recipes for implementing big data processing and analytics using Apache Spark and Python

    (ebook) (audiobook) (audiobook) Język publikacji: angielski
    PySpark Cookbook. Over 60 recipes for implementing big data processing and analytics using Apache Spark and Python Denny Lee, Tomasz Drabas - okładka ebooka

    PySpark Cookbook. Over 60 recipes for implementing big data processing and analytics using Apache Spark and Python Denny Lee, Tomasz Drabas - okładka ebooka

    PySpark Cookbook. Over 60 recipes for implementing big data processing and analytics using Apache Spark and Python Denny Lee, Tomasz Drabas - okładka audiobooka MP3

    PySpark Cookbook. Over 60 recipes for implementing big data processing and analytics using Apache Spark and Python Denny Lee, Tomasz Drabas - okładka audiobooks CD

    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Stron:
    330
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    119,00 zł

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    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.

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    O autorach ebooka

    Denny Lee - zajmuje się systemami rozproszonymi i inżynierią danych, zwłaszcza dla branży ochrony zdrowia.

    Tomasz Drabas is a Data Scientist working for Microsoft and currently residing in the Seattle area. He has over 12 years' international experience in data analytics and data science in numerous fields: advanced technology, airlines, telecommunications, finance, and consulting. Tomasz started his career in 2003 with LOT Polish Airlines in Warsaw, Poland while finishing his Master's degree in strategy management. In 2007, he moved to Sydney to pursue a doctoral degree in operations research at the University of New South Wales, School of Aviation; his research crossed boundaries between discrete choice modeling and airline operations research. During his time in Sydney, he worked as a Data Analyst for Beyond Analysis Australia and as a Senior Data Analyst/Data Scientist for Vodafone Hutchison Australia among others. He has also published scientific papers, attended international conferences, and served as a reviewer for scientific journals. In 2015 he relocated to Seattle to begin his work for Microsoft. While there, he has worked on numerous projects involving solving problems in high-dimensional feature space.

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