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Verlag: Apress (edition First Edition), 2005
ISBN 10: 1590595203 ISBN 13: 9781590595206
Sprache: Englisch
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Verlag: O'Reilly Media (edition 1), 2022
ISBN 10: 1492082384 ISBN 13: 9781492082385
Sprache: Englisch
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In den WarenkorbZustand: New. pp. 506.
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In den WarenkorbZustand: New. pp. 506 68:B&W 7 x 10 in or 254 x 178 mm Case Laminate on White w/Gloss Lam.
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In den WarenkorbZustand: New. pp. 664 Illus.
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In den WarenkorbPaperback or Softback. Zustand: New. Data Algorithms with Spark: Recipes and Design Patterns for Scaling Up Using Pyspark 1.55. Book.
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In den WarenkorbPaperback. Zustand: New. 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 solutionsExplore powerful transformations and reductions including reduceByKey(), combineByKey(), and mapPartitions()Understand data partitioning for optimized queriesBuild and apply a model using PySpark design patternsApply motif-finding algorithms to graph dataAnalyze graph data by using the GraphFrames APIApply PySpark algorithms to clinical and genomics dataLearn how to use and apply feature engineering in ML algorithmsUnderstand and use practical and pragmatic data design patterns.
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In den WarenkorbZustand: New. In.
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In den WarenkorbPaperback. Zustand: New. 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 solutionsExplore powerful transformations and reductions including reduceByKey(), combineByKey(), and mapPartitions()Understand data partitioning for optimized queriesBuild and apply a model using PySpark design patternsApply motif-finding algorithms to graph dataAnalyze graph data by using the GraphFrames APIApply PySpark algorithms to clinical and genomics dataLearn how to use and apply feature engineering in ML algorithmsUnderstand and use practical and pragmatic data design patterns.
EUR 64,08
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In den WarenkorbZustand: New. First book to market on metadata specific recipes related to JDBC and its use with MySQL and Oracle, databases standard to JavaCompliant with the new Java EE 5Provides cut and paste code templates that can be immediately customized and appl.
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In den WarenkorbTaschenbuch. Zustand: Neu. Neuware -JDBC Metadata, MySQL, and Oracle Recipes is the only book that focuses on metadata or annotation-based code recipes for JDBC API for use with Oracle and MySQL. It continues where the authors other book, JDBC Recipes: A Problem-Solution Approach, leaves off.This edition is also a Java EE 5-compliant book, perfect for lightweight Java database development. And it provides cut-and-paste code templates that can be immediately customized and applied in each developer's application development.APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 508 pp. Englisch.
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In den WarenkorbZustand: New.
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In den WarenkorbZustand: New.