Mohlo by se vám také líbit

Více informací o knize Vaex Mastery

• Parametry knihy
• Anotace
• Oblíbené z jiného soudku

Nákupem získáte 86 bodů

Anotace knihy

"Vaex Mastery: Efficient and Scalable Data Processing with Python" offers a comprehensive journey into overcoming the challenges of big data processing within the Python ecosystem. The book begins by examining the constraints of traditional Python data science tools and introduces foundational concepts such as parallelism, distributed computing, and out-of-core computation. It then presents Vaex as a powerful, high-performance alternative, providing a thorough comparative analysis against libraries like pandas, Dask, and Spark, alongside compelling industry use cases that showcase Vaex's distinctive strengths.

Delving deep into Vaex's innovative architecture, the book highlights its lazy evaluation paradigm, memory-mapping strategies, and optimized computational graph execution, empowering readers to handle data at scale with exceptional efficiency. It offers detailed guidance on scalable data ingestion, cloud-native deployment, distributed transformation, and resilient error handling. From advanced feature engineering and statistical analysis to seamless machine learning integration, every chapter equips readers with practical tools to work effortlessly with terabyte-scale datasets.

The final sections fuse practical expertise with cutting-edge insights through real-world case studies spanning astronomy, geospatial analytics, financial markets, and e-commerce. Comprehensive advice on debugging, profiling, and optimization ensures production-grade reliability and seamless ecosystem interoperability. With a strong focus on data security, governance, and emerging trends, this definitive resource enables Python professionals to build robust, scalable, and future-ready data pipelines using Vaex.

Parametry knihy

• Plný název: Vaex Mastery
• Podnázev: Efficient and Scalable Data Processing with Python
• Autor: William M. Jackson
• Jazyk: Angličtina
• Vazba: Brožovaná
• Počet stran: 228
• EAN: 9798259020184
• ID: 52229672
• Nakladatelství: Independently published
• Hmotnost: 312 g
• Rozměry: 229 × 152 × 12 mm
• Datum vydání: 26. April 2026

---

---

---