Big data python spark par carter thompson (5 résultats)

PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000.

PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000.

Etat : New. Print on Demand.

Paperback. Etat : new. Paperback. Handle Big Data Like a Pro-With Python and Apache SparkToday's data is massive. Terabytes. Petabytes. If you want to work at scale, you need tools that move fast and scale even faster.Big Data with Python & Spark gives you everything you need to analyze, transform, and process massive datasets using two of the most powerful tools in data engineering.This book blends Python's flexibility with Spark's power, helping you go from raw logs to clean insights-fast. Whether you're a data analyst, engineer, or developer, this hands-on guide equips you with the knowledge to tackle real-world big data projects with confidence.What You'll Learn: How to set up Spark and PySpark environments for big data projectsThe fundamentals of resilient distributed datasets (RDDs) and DataFramesData cleaning, ETL pipelines, and batch processing at scaleWriting fast, efficient Spark jobs with PythonWorking with structured and semi-structured data: JSON, CSV, ParquetReal-world use cases in finance, retail, IoT, and web analyticsPerformance tuning, lazy evaluation, and memory management in SparkRunning Spark on local machines, clusters, or in the cloudVisualizing massive data outputs and building summariesWhether you're processing a few gigabytes or a hundred terabytes, this book will help you write scalable, maintainable, and powerful big data pipelines.Code smarter. Analyze faster. Scale bigger. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …

Paperback. Etat : new. Paperback. Handle Big Data Like a Pro-With Python and Apache SparkToday's data is massive. Terabytes. Petabytes. If you want to work at scale, you need tools that move fast and scale even faster.Big Data with Python & Spark gives you everything you need to analyze, transform, and process massive datasets using two of the most powerful tools in data engineering.This book blends Python's flexibility with Spark's power, helping you go from raw logs to clean insights-fast. Whether you're a data analyst, engineer, or developer, this hands-on guide equips you with the knowledge to tackle real-world big data projects with confidence.What You'll Learn: How to set up Spark and PySpark environments for big data projectsThe fundamentals of resilient distributed datasets (RDDs) and DataFramesData cleaning, ETL pipelines, and batch processing at scaleWriting fast, efficient Spark jobs with PythonWorking with structured and semi-structured data: JSON, CSV, ParquetReal-world use cases in finance, retail, IoT, and web analyticsPerformance tuning, lazy evaluation, and memory management in SparkRunning Spark on local machines, clusters, or in the cloudVisualizing massive data outputs and building summariesWhether you're processing a few gigabytes or a hundred terabytes, this book will help you write scalable, maintainable, and powerful big data pipelines.Code smarter. Analyze faster. Scale bigger. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. …