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analysis using graphframes and see how to optimize your PySpark SQL code. PySpark SQL Recipes starts with recipes on creating dataframes from;
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, machine learning, and analytics using PySpark Overcome challenges in developing and deploying Spark solutions using Python Explore recipes for;
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-to-day conundrums with SQL. The second edition includes: Fully revised recipes that recognize the greater adoption of window functions;
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This unique cookbook contains a wealth of solutions to problems that SQL programmers face all the time. The recipes inside range from how;
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* Comprehensive T-SQL Coverage, including all SQL Server 2005 new features, from an established SQL Server expert and author. * Broad;
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SQL Server 2012 Data Integration Recipes provides focused and practical solutions to real world problems of data integration. Need to;
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Leverage machine and deep learning models to build applications on real-time data using PySpark. This book is perfect for those who want to;
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Leverage machine and deep learning models to build applications on real-time data using PySpark. This book is perfect for those who want to;
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SQL Server T-SQL Recipes is an example-based guide to the Transact-SQL language that is at the core of SQL Server. This edition has been;
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This book offers practical, task-based, and immediately usable recipes covering a wide range of MDX calculations and queries. In addition;
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A practical cookbook packed with recipes to help developers produce data cubes as quickly as possible by following step by step;
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SQL Success is about problem-solving in SQL. It bridges the gap between dry and dull database theory books, and developer books that focus;
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Use PySpark to easily crush messy data at-scale and discover proven techniques to create testable, immutable, and easily parallelizable;
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with SQL databases is assumed, but the recipes are approachable to almost anyone with basic database skills.;
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application development (RAD) techniques along with Microsoft SQL Server 2012, this book guides database administrators, SQL programmers, and report;
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This book has individual recipes and you can read it from cover to cover or dip into any recipe and get solution to a specific issue. Every;
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Build machine learning models, natural language processing applications, and recommender systems with PySpark to solve various business;
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Discover the capabilities of PySpark and its application in the realm of data science. This comprehensive guide with hand-picked examples;
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Discover the capabilities of PySpark and its application in the realm of data science. This comprehensive guide with hand-picked examples;
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book contains recipes that explore the new and advanced features added to SQL Server 2016. The first few chapters cover recipes on configuring;
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This cookbook presents solutions to problems in the form of recipes. Each recipe provides the reader with easy step-by-step descriptions;
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This cookbook presents solutions to problems in the form of recipes. Each recipe provides the reader with easy step-by-step descriptions;
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trying out the recipes and examples for yourself, you will put together the building blocks into powerful SQL statements that will make your;
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, SMO, .NET classes, or other components * It offers easy-to-follow, practical recipes to help you get the most out of SQL Server and;
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SQL Server 2012 Integration Services Design Patterns is a book of recipes for SQL Server Integration Services (SSIS). Design patterns;
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