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

Parsian, Mahmoud

 
9781492082385: Data Algorithms with Spark: Recipes and Design Patterns for Scaling Up using PySpark
Tapa blanda
ISBN 10: 1492082384 ISBN 13: 9781492082385
Editorial: O'Reilly Media, 2022

Sinopsis

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

"Sinopsis" puede pertenecer a otra edición de este libro.

Acerca del autor

Mahmoud Parsian, Ph.D. in Computer Science, is a practicing software professional with 30 years of experience as a developer, designer, architect, and author. For the past 15 years, he has been involved in Java server-side, databases, MapReduce, Spark, PySpark, and distributed computing. Dr. Parsian currently leads Illumina's Big Data team, which is focused on large-scale genome analytics and distributed computing by using Spark and PySpark. He leads and develops scalable regression algorithms; DNA sequencing pipelines using Java, MapReduce, PySpark, Spark, and open source tools. He is the author of the following books: Data Algorithms (O'Reilly, 2015), PySpark Algorithms (Amazon.com, 2019), JDBC Recipes (Apress, 2005), JDBC Metadata Recipes (Apress, 2006). Also, Dr. Parsian is an Adjunct Professor at Santa Clara University, teaching Big Data Modeling and Analytics and Machine Learning to MSIS program utilizing Spark, PySpark, Python, and scikit-learn.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
O'Reilly Media
Año de publicación
2022
Idioma
Inglés
ISBN 10 
1492082384
ISBN 13 
9781492082385
Encuadernación
Tapa blanda
Número de edición
1
Número de páginas
435
Contacto del fabricante
no disponible
Persona responsable
no disponible