Practical Oracle SQL: Mastering the Full Power of Oracle Database

ISBN-13: 9781484256169 / Angielski / Miękka / 2020 / 460 str.

Kim Berg Hansen

Opis

IOUG Press cover treatment, Intermediate-Advanced user level

Spis treści

Part I. Core SQL

1. Correlating Inline Views

2. Pitfalls of Set Operations

3. Divide and Conquer with Subquery Factoring

4. Tree Calculations with Recursion

5. Functions Defined Within SQL

6. Iterative Calculations with Multidimensional Data

7. Unpivoting Columns to Rows

8. Pivoting Rows to Columns

9. Splitting Delimited Text

10. Creating Delimited Text

Part II. Analytic Functions

11. Analytic Partitions, Ordering and Windows

12. Answering Top-N Questions

13. Ordered Subsets with Rolling Sums

14. Analyzing Activity Logs with Lead

15. Forecasting with Linear Regression

16. Rolling Sums to Forecast Reaching Minimums

Part III. Row Pattern Matching

17. Up and  Down Patterns

18. Grouping Data Through Patterns

19. Merging Date Ranges

20. Finding Abnormal Peaks

21. Bin Fitting

22. Counting Children in Trees

O autorze

​Kim Berg Hansen is a database developer from Middelfart in Denmark. As a youngster he originally wanted to work with electronics, and he tried computer programming and discovered that the programs he wrote worked well—unlike the electronics projects he soldered that often failed. This led to a VIC-20 with 5 kilobytes RAM and many hours programming in Commodore Basic.

Having discovered his talent, Kim financed computer science studies at Odense University with a summer job as sheriff of Legoredo, while learning methodology and programming in Modula-2 and C. From there he moved into consulting as a developer making customizations to ERP software. That gave him his first introduction to Oracle SQL and PL/SQL, with which he has worked extensively since the year 2000.

His professional passion is to work with data inside the database utilizing the SQL language to the fullest to achieve the best application experience for his application users. With a background fitting programs into 5 KB RAM, Kim hates to waste computing resources unnecessarily.

Kim shares his experience and knowledge by blogging at the kibeha.dk website, presenting at various Oracle User Group conferences, and being the SQL quizmaster at the Oracle Dev Gym. His motivation comes from peers who say “now I understand” after his explanations, and from end users who “can’t live without” his application coding. He is a certified Oracle OCE in SQL, and an Oracle ACE Director. 

Outside the coding world, Kim is married, loves to cook, and is a card-carrying member of the Danish Beer Enthusiasts Association.

Blurb

Write powerful queries using as much of the feature-rich Oracle SQL language as possible, progressing beyond the simple queries of basic SQL as standardized in SQL-92.

Both standard SQL and Oracle’s own extensions to the language have progressed far over the decades in terms of how much you can work with your data in a single, albeit sometimes complex, SQL statement. If you already know the basics of SQL, this book provides many examples of how to write even more advanced SQL to huge 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 simpler statements in SQL, and gradually working those statements stepwise into more complex statements that deliver powerful results, is covered in each example. By trying out the recipes and examples 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