Artículo: AMZ-1492082384

Data Algorithms with Spark: Recipes and Design Patterns for Scaling Up using PySpark

Format:

Paperback

Kindle

Paperback

Detalles del producto
Disponibilidad
En stock
Peso con empaque
1.12 kg
Devolución
Condición
Nuevo
Producto de
Amazon
Viaja desde
USA

Sobre este producto
  • Apache Spark's speed, ease of use, sophisticated analytics, and multilanguage support makes practical knowledge of this cluster-computing framework a required skill for data engineers and data scientists. With this hands-on guide, anyone looking for an introduction to Spark will learn practical algorithms and examples using PySpark. In each chapter, author Mahmoud Parsian shows you how to solve a data problem with a set of Spark transformations and algorithms. You'll learn how to tackle problems involving ETL, design patterns, machine learning algorithms, data partitioning, and genomics analysis. Each detailed recipe includes PySpark algorithms using the PySpark driver and shell script. With this book, you will: Learn how to select Spark transformations for optimized solutions Explore powerful transformations and reductions including reduceByKey(), combineByKey(), and mapPartitions() Understand data partitioning for optimized queries Build and apply a model using PySpark design patterns Apply motif-finding algorithms to graph data Analyze graph data by using the GraphFrames API Apply PySpark algorithms to clinical and genomics data Learn how to use and apply feature engineering in ML algorithms Understand and use practical and pragmatic data design patterns
$114,34
44% OFF
$63,52

IMPORT EASILY

By purchasing this product you can deduct VAT with your RUT number

$114,34
44% OFF
$63,52

3 meses de gracia en diferidos y hasta 6 meses sin intereses con Pacificard

Envío gratis
Llega en 5 a 12 días hábiles
Con envío
Tienes garantia de entrega
Este producto viaja de USA a tus manos en