Data Algorithms: Recipes for Scaling Up with Hadoop and Spark
Book information
Description
If you are ready to dive into the MapReduce framework for processing large datasets, this practical book takes you step by step through the algorithms and tools you need to build distributed MapReduce applications with Apache Hadoop or Apache Spark. Each chapter provides a recipe for solving a massive computational problem, such as building a recommendation system. You'll learn how to implement the appropriate MapReduce solution with code that you can use in your projects. Dr. Mahmoud Parsian covers basic design patterns, optimization techniques, and data mining and machine learning solutions for problems in bioinformatics, genomics, statistics, and social network analysis. This book also includes an overview of MapReduce, Hadoop, and Spark.
Similar books
JDBC Recipes: A Problem-Solution Approach
2005 · PDF
Data Algorithms with Spark: Recipes and Design Patterns for Scaling Up using PySpark
2022 · PDF
Data Algorithms with Spark: Recipes and Design Patterns for Scaling Up using PySpark
2022 · EPUB
Data Algorithms: Recipes for Scaling Up with Hadoop and Spark
2015 · PDF
Data Algorithms: Recipes for Scaling Up with Hadoop and Spark
2015 · MOBI
Data Algorithms: Recipes for Scaling Up with Hadoop and Spark
2015 · EPUB
JDBC Metadata, MySQL, and Oracle Recipes: A Problem-Solution Approach
2006 · DJVU
JDBC Metadata, MySQL, and Oracle Recipes: A Problem-Solution Approach
2006 · DJVU