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Spark and Big Data Processing with R and Python: Building Scalable Pipelines with Sparklyr, PySpark, and Databricks - Tapa blanda
Sinopsis
Reactive Publishing
Learn big data processing with Spark using R and Python.
This book offers a practical introduction to Apache Spark for large-scale data work. It focuses on building scalable data pipelines using Sparklyr, PySpark, and Databricks.
You will discover how to:
- Work with large datasets using Apache Spark
- Use Sparklyr to integrate Spark with R
- Develop with PySpark in Python
- Leverage Databricks for cloud-based Spark environments
- Construct reliable data pipelines for real-world use
The book bridges the R and Python ecosystems, helping data professionals use the right language for different Spark tasks. It covers core concepts including data transformation, distributed processing, and moving projects from development to production.
Written for data analysts, data scientists, and engineers who want to add Spark to their toolkit.
Perfect for: Professionals looking to expand their skills in big data processing with Spark across both R and Python.
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Spark and Big Data Processing with R and Python: Building Scalable Pipelines with Sparklyr, PySpark, and Databricks
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Condición: New. Print on Demand. Nº de ref. del artículo: I-9798198822771
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Spark and Big Data Processing with R and Python
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PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: L2-9798198822771
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Spark and Big Data Processing with R and Python
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
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PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: L2-9798198822771
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Spark and Big Data Processing with R and Python (Paperback)
Impresión bajo demandaLibrería: CitiRetail, Stevenage, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: new. Paperback. Reactive PublishingLearn big data processing with Spark using R and Python.This book offers a practical introduction to Apache Spark for large-scale data work. It focuses on building scalable data pipelines using Sparklyr, PySpark, and Databricks.You will discover how to: Work with large datasets using Apache SparkUse Sparklyr to integrate Spark with RDevelop with PySpark in PythonLeverage Databricks for cloud-based Spark environmentsConstruct reliable data pipelines for real-world useThe book bridges the R and Python ecosystems, helping data professionals use the right language for different Spark tasks. It covers core concepts including data transformation, distributed processing, and moving projects from development to production.Written for data analysts, data scientists, and engineers who want to add Spark to their toolkit.Perfect for: Professionals looking to expand their skills in big data processing with Spark across both R and Python. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9798198822771
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Spark and Big Data Processing with R and Python : Building Scalable Pipelines with Sparklyr, PySpark, and Databricks
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. Neuware - Reactive PublishingLearn big data processing with Spark using R and Python.This book offers a practical introduction to Apache Spark for large-scale data work. It focuses on building scalable data pipelines using Sparklyr, PySpark, and Databricks.You will discover how to: - Work with large datasets using Apache Spark- Use Sparklyr to integrate Spark with R- Develop with PySpark in Python- Leverage Databricks for cloud-based Spark environments- Construct reliable data pipelines for real-world useThe book bridges the R and Python ecosystems, helping data professionals use the right language for different Spark tasks. It covers core concepts including data transformation, distributed processing, and moving projects from development to production.Written for data analysts, data scientists, and engineers who want to add Spark to their toolkit.Perfect for: Professionals looking to expand their skills in big data processing with Spark across both R and Python. Nº de ref. del artículo: 9798198822771
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