Mahmoud Parsian

Data Algorithms with Spark

Recipes and Design Patterns for Scaling Up Using Pyspark

• Broschiertes Buch

Produktbeschreibung

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.

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Produktdetails

• Verlag: O'Reilly Media
• Seitenzahl: 435
• Erscheinungstermin: 17. Mai 2022
• Englisch
• Abmessung: 231mm x 180mm x 25mm
• Gewicht: 760g
• ISBN-13: 9781492082385
• ISBN-10: 1492082384
• Artikelnr.: 62064268

Autorenporträt

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.