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  • Book Overview & Buying Learn T-SQL Querying
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Learn T-SQL Querying

Learn T-SQL Querying - Second Edition

By : Pedro Lopes, Pam Lahoud
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Learn T-SQL Querying

Learn T-SQL Querying

5 (3)
By: Pedro Lopes, Pam Lahoud

Overview of this book

Data professionals seeking to excel in Transact-SQL for Microsoft SQL Server and Azure SQL Database often lack comprehensive resources. Learn T-SQL Querying second edition focuses on indexing queries and crafting elegant T-SQL code enabling data professionals gain mastery in modern SQL Server versions (2022) and Azure SQL Database. The book covers new topics like logical statement processing flow, data access using indexes, and best practices for tuning T-SQL queries. Starting with query processing fundamentals, the book lays a foundation for writing performant T-SQL queries. You’ll explore the mechanics of the Query Optimizer and Query Execution Plans, learning to analyze execution plans for insights into current performance and scalability. Using dynamic management views (DMVs) and dynamic management functions (DMFs), you’ll build diagnostic queries. The book covers indexing and delves into SQL Server’s built-in tools to expedite resolution of T-SQL query performance and scalability issues. Hands-on examples will guide you to avoid UDF pitfalls and understand features like predicate SARGability, Query Store, and Query Tuning Assistant. By the end of this book, you‘ll have developed the ability to identify query performance bottlenecks, recognize anti-patterns, and avoid pitfalls
Table of Contents (18 chapters)
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1
Part 1: Query Processing Fundamentals
4
Part 2: Dos and Don’ts of T-SQL
9
Part 3: Assembling Our Query Troubleshooting Toolbox

Complex expressions

Search predicates should not use complex expressions. Much like the deterministic function calls we discussed in the Functions in our predicate section, complex expressions can also cause unnecessary scans.

As was discussed in previous chapters, the Query Optimizer uses statistics, internal transformation rules, and heuristics at compile time to determine a good enough plan to execute a query. This includes the ability to fold expressions, which is the process of simplifying constant expressions at compile time. For example, a predicate such as WHERE Column = 320 * 200 * 32 is computed at compile time to its arithmetic result and, internally, the predicate is evaluated as WHERE Column = 2048000. But unlike constants, calculations that involve column values, parameters, non-deterministic functions, or variables are only evaluated at runtime – this is another example of how the Query Optimizer can’t accurately estimate row counts beforehand, resulting...

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