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Expert T-SQL window functions in SQL server /

Expert T-SQL Window Functions in SQL Server takes you from any level of knowledge of windowing functions and turns you into an expert who can use these powerful functions to solve many T-SQL queries. Replace slow cursors and self-joins with queries that are easy to write and fantastically better per...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Kellenberger, Kathi (Autor), Groom, Clayton (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: [Berkeley, CA] : Apress, [2015]
Colección:Expert's voice in SQL server.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Tabla de Contenidos:
  • Contents at a Glance
  • Contents
  • About the Authors
  • About the Technical Reviewer
  • Acknowledgments
  • Authorâ€?s Note
  • Chapter 1: Looking Through the Window
  • Discovering Window Functions
  • Thinking About the Window
  • Understanding the OVER Clause
  • Dividing Windows with Partitions
  • Uncovering Special Case Windows
  • Summary
  • Chapter 2: Discovering Ranking Functions
  • Using ROW_NUMBER
  • Understanding RANK and DENSE_RANK
  • Dividing Data with NTILE
  • Solving Queries with Ranking Functions
  • Deduplicating Data
  • Finding the First N Rows of Every GroupSolving the Islands Problem
  • Solving the Bonus Problem
  • Summary
  • Chapter 3: Summarizing with Window Aggregates
  • Using Window Aggregates
  • Adding Window Aggregates to Aggregate Queries
  • Using Window Aggregates to Solve Common Queries
  • The Percent of Sales Problem
  • The Partitioned Table Problem
  • Creating Custom Window Aggregate Functions
  • Summary
  • Chapter 4: Tuning for Better Performance
  • Using Execution Plans
  • Using STATISTICS IO
  • Understanding the Performance Implications of Window Aggregates
  • Indexing to Improve the Performance of Window FunctionsPerforming Time Comparisons
  • Summary
  • Chapter 5: Calculating Running and Moving Aggregates
  • Adding ORDER BY to Window Aggregates
  • Calculating Moving Totals and Averages
  • Solving Queries Using Accumulating Aggregates
  • The Last Good Value Problem
  • The Subscription Problem
  • Summary
  • Chapter 6: Adding Frames to the Window
  • Understanding Framing
  • Applying Frames to Running and Moving Aggregates
  • Measuring Performance
  • Understanding the Logical Difference Between ROWS and RANGE
  • SummaryChapter 7: Taking a Peek at Another Row
  • Understanding LAG and LEAD
  • Understanding FIRST_VALUE and LAST_ VALUE
  • Using the Offset Functions to Solve Queries
  • The Year-Over-Year Growth Calculation
  • The Gaps Problem
  • Comparing Performance
  • LAG and LEAD Performance
  • FIRST_VALUE and LAST_VALUE PERFORMANCE
  • Summary
  • Chapter 8: Understanding Statistical Functions
  • Using PERCENT_RANK and CUME_ DIST
  • Using PERCENTILE_CONT and PERCENTILE_ DISC
  • Comparing Statistical Functions to Older Methods
  • Summary
  • Chapter 9: Time Range Calculations and TrendsPutting It All Together
  • Percent of Parent
  • Period-to-Date Calculations
  • Averages, Moving Averages, and Rate-of-Change
  • Same Period Prior Year
  • Difference and Percent Difference
  • Moving Totals and Simple Moving Averages
  • Rate-of-Change Calculations
  • Summary
  • Index