×
Dodano do koszyka:
Pozycja znajduje się w koszyku, zwiększono ilość tej pozycji:
Zakupiłeś już tę pozycję:
Książkę możesz pobrać z biblioteki w panelu użytkownika
Pozycja znajduje się w koszyku
Przejdź do koszyka

Zawartość koszyka

ODBIERZ TWÓJ BONUS :: »

Essential PySpark for Scalable Data Analytics. A beginner's guide to harnessing the power and ease of PySpark 3

(ebook) (audiobook) (audiobook) Książka w języku angielskim
Essential PySpark for Scalable Data Analytics. A beginner's guide to harnessing the power and ease of PySpark 3 Sreeram Nudurupati - okladka książki

Essential PySpark for Scalable Data Analytics. A beginner's guide to harnessing the power and ease of PySpark 3 Sreeram Nudurupati - okladka książki

Essential PySpark for Scalable Data Analytics. A beginner's guide to harnessing the power and ease of PySpark 3 Sreeram Nudurupati - audiobook MP3

Essential PySpark for Scalable Data Analytics. A beginner's guide to harnessing the power and ease of PySpark 3 Sreeram Nudurupati - audiobook CD

Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
322
Dostępne formaty:
     PDF
     ePub
     Mobi
Apache Spark is a unified data analytics engine designed to process huge volumes of data quickly and efficiently. PySpark is Apache Spark's Python language API, which offers Python developers an easy-to-use scalable data analytics framework.
Essential PySpark for Scalable Data Analytics starts by exploring the distributed computing paradigm and provides a high-level overview of Apache Spark. You'll begin your analytics journey with the data engineering process, learning how to perform data ingestion, cleansing, and integration at scale. This book helps you build real-time analytics pipelines that help you gain insights faster. You'll then discover methods for building cloud-based data lakes, and explore Delta Lake, which brings reliability to data lakes. The book also covers Data Lakehouse, an emerging paradigm, which combines the structure and performance of a data warehouse with the scalability of cloud-based data lakes. Later, you'll perform scalable data science and machine learning tasks using PySpark, such as data preparation, feature engineering, and model training and productionization. Finally, you'll learn ways to scale out standard Python ML libraries along with a new pandas API on top of PySpark called Koalas.
By the end of this PySpark book, you'll be able to harness the power of PySpark to solve business problems.

Wybrane bestsellery

O autorze książki

Sreeram Nudurupati is a data analytics professional with years of experience in designing and optimizing data analytics pipelines at scale. He has a history of helping enterprises, as well as digital natives, build optimized analytics pipelines by using the knowledge of the organization, infrastructure environment, and current technologies.

Packt Publishing - inne książki

Zamknij

Przenieś na półkę

Proszę czekać...
ajax-loader

Zamknij

Wybierz metodę płatności

Zamknij Pobierz aplikację mobilną Ebookpoint