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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

Fuzzy string matching

When searching for strings in the SQL Database Engine using =, the strings must match exactly for the expression to evaluate to true. If we want to match only part of the string, however, we must use a LIKE operator with wildcards. If we want to search for a pattern anywhere within a string, we need both leading and trailing wildcards. The problem with this is that it prevents us from being able to use an index or accurately estimate the cardinality. An index with a string key is sorted starting with the first character of the string, but if we are searching for a pattern that may appear in the middle of the string, the SQL Database Engine must scan every value and search for the matching pattern in each string in the column. A LIKE operator with a leading wildcard (%a value or %a value%) almost always causes a scan operation.

Consider an example from the AdventureWorks database where we want to find all the Flat Washers in the Product table. We know they all...

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Learn T-SQL Querying
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