High Performance Spark. Best Practices for Scaling and Optimizing Apache Spark. 2nd Edition Holden Karau, Adi Polak, Rachel Warren
- Autorzy:
- Holden Karau, Adi Polak, Rachel Warren
- Wydawnictwo:
- O'Reilly Media
- Ocena:
- Stron:
- 412
- Dostępne formaty:
-
ePubMobi
Opis
książki
:
High Performance Spark. Best Practices for Scaling and Optimizing Apache Spark. 2nd Edition
Apache Spark is amazing when everything clicks. But if you haven't seen the performance improvements you expected or still don't feel confident enough to use Spark in production, this practical book is for you. Authors Holden Karau, Adi Polak, and Rachel Warren walk you through the secrets of the Spark code base and demonstrate performance optimizations that will help your data pipelines run faster, scale to larger datasets, and avoid costly antipatterns.
Ideal for data engineers, software engineers, data scientists, and system administrators, the second edition of High Performance Spark presents new use cases, code examples, and best practices for Spark 4.x and beyond. This book gives you a fresh perspective on this continually evolving framework and shows you how to work around bumps on your Spark and PySpark journey.
With this book, you'll learn how to:
- Accelerate your ML workflows with integrations including PyTorch
- Handle key skew and take advantage of Spark's new dynamic partitioning
- Make your code reliable with scalable testing and validation techniques
- Make Spark high performance
- Deploy Spark on Kubernetes and similar environments
- Take advantage of GPU acceleration with RAPIDS and resource profiles
- Get your Spark jobs to run faster
- Use Spark to productionize exploratory data science projects
- Handle even larger datasets with Spark
- Gain faster insights by reducing pipeline running times
Holden Karau, Adi Polak, Rachel Warren - pozostałe książki
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Dzięki tej książce nauczysz się holistycznego podejścia, które zdecydowanie usprawni współpracę między zespołami. Najpierw zapoznasz się z podstawowymi informacjami o przepływach pracy związanych z uczeniem maszynowym przy użyciu Apache Spark i pakietu PySpark. Nauczysz się też zarządzać cyklem życia eksperymentów dla potrzeb uczenia maszynowego za pomocą biblioteki MLflow. Z kolejnych rozdziałów dowiesz się, jak od strony technicznej wygląda korzystanie z platformy uczenia maszynowego. W książce znajdziesz również opis wzorców wdrażania, wnioskowania i monitorowania modeli w środowisku produkcyjnym.-
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Machine learning engineering is an in-demand skill set, and it can be difficult to find a helpful guide on the topic. This fully updated second edition will help you solve business problems by addressing the pain points in creating standardized pipelines for taking proof-of-concept ML models to production and producing trustworthy results.-
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Learn how to build end-to-end scalable machine learning solutions with Apache Spark. With this practical guide, author Adi Polak introduces data and ML practitioners to creative solutions that supersede today's traditional methods. You'll learn a more holistic approach that takes you beyond specific requirements and organizational goals--allowing d-
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Apache Spark is amazing when everything clicks. But if you haven’t seen the performance improvements you expected, or still don’t feel confident enough to use Spark in production, this practical book is for you. Authors Holden Karau and Rachel Warren demonstrate performance optimizations to help your Spark queries run faster and handle larger data-
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When people want a way to process big data at speed, Spark is invariably the solution. With its ease of development (in comparison to the relative complexity of Hadoop), it’s unsurprising that it’s becoming popular with data analysts and engineers everywhere. Beginning with the fundamentals, we’ll show you how to get set up with Spark with minimum-
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Szczegóły książki
- ISBN Ebooka:
- 978-10-981-4581-1, 9781098145811
- Data wydania ebooka :
-
2026-05-29
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- Język publikacji:
- angielski
- Rozmiar pliku ePub:
- 6MB
- Rozmiar pliku Mobi:
- 6MB
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