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Practical oracle SQL : mastering the full power of oracle database / Kim Berg Hansen

By: Material type: TextTextPublication details: New Jersey Apress 2022Description: 460pISBN:
  • 9781484276075
Subject(s): DDC classification:
  • 005.7565 HAN-K
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Holdings
Item type Current library Collection Shelving location Call number Status Date due Barcode Item holds
Books Books BITS Pilani Hyderabad 003-007 General Stack (For lending) 005.7565 HAN-K (Browse shelf(Opens below)) Available 45732
Total holds: 0


Write powerful queries using as much of the feature-rich Oracle SQL language as possible, progressing beyond the simple questions of basic SQL as standardized in SQL-92. Both standard SQL and Oracles' extensions to the language have moved far over the decades in terms of how much you can work with your data in a single, albeit sometimes complex, SQL statement. Suppose you already know the basics of SQL. In that case, this book provides many examples of how to write even more advanced SQL to massive benefit in your applications, such as Pivoting rows to columns and columns to rows, Recursion in SQL with MODEL and WITH clauses Answering Top-N questions Forecasting with linear regressions Row pattern matching to group or distribute rows Using MATCH_RECOGNIZE as a row processing engine The process of starting from more straightforward statements in SQL, and gradually working those statements stepwise into more complex ideas that deliver powerful results, is covered in each example. By trying out the recipes and standards for yourself, you will put together the building blocks into powerful SQL statements that will make your application run circles around your competitors. You will: Take full advantage of advanced and modern features in Oracle SQL, Recognize when modern SQL constructs can help create better applications, Improve SQL query building skills through stepwise refinement, Apply set-based thinking to process more data in fewer queries, Make cross-row calculations with analytic functions Search for patterns across multiple rows using row pattern matching Break complex calculations into smaller steps with subquery factoring.

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