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  • Book Overview & Buying SQL Server Query Tuning and Optimization
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SQL Server Query Tuning and Optimization

SQL Server Query Tuning and Optimization

By : Benjamin Nevarez
4.9 (13)
Buy this Book
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SQL Server Query Tuning and Optimization

SQL Server Query Tuning and Optimization

4.9 (13)
By: Benjamin Nevarez
Buy this Book

Overview of this book

SQL Server is a relational database management system developed by Microsoft. As a database server, it is a software product with the primary function of storing and retrieving data as requested by other software applications. This book starts by describing the inner workings of the query optimizer, and will enable you to use this knowledge to write better queries and provide the query engine with all the information it needs to produce efficient execution plans. As you progress, you’ll get practical query optimization tips for troubleshooting underperforming queries. The book will also guide you through intelligent query processing and what is new in SQL Server 2022. Query performance topics such as the Query Store, In-Memory OLTP and columnstore indexes are covered as well. By the end of this book, you’ll be able to get the best possible performance for your queries and applications.
Table of Contents (14 chapters)
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Preface
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Preface
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Who this book is for
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What this book covers
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Download the example code files
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Download the color images
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Conventions used
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Get in touch
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Share Your Thoughts
1
Chapter 1: An Introduction to Query Tuning and Optimization
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Chapter 1: An Introduction to Query Tuning and Optimization
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Query Processor Architecture
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Analyzing execution plans
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Getting plans from a trace or the plan cache
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SET STATISTICS TIME and IO statements
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Summary
Lock Free Chapter
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Chapter 2: Troubleshooting Queries
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Chapter 2: Troubleshooting Queries
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DMVs and DMFs
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SQL Trace
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Extended events
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The Data Collector
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Summary
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Chapter 3: The Query Optimizer
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Chapter 3: The Query Optimizer
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Query optimization research
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Introduction to query processing
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The sys.dm_exec_query_optimizer_info DMV
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Parsing and binding
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Simplification
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Trivial plan optimization
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Joins
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Transformation rules
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The Memo
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Statistics
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Full optimization
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Summary
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Chapter 4: The Execution Engine
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Chapter 4: The Execution Engine
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Data access operators
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Aggregations
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Joins
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Parallelism
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Updates
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Summary
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Chapter 5: Working with Indexes
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Chapter 5: Working with Indexes
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Introduction to indexes
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Creating indexes
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Understanding index operations
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The Database Engine Tuning Advisor
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Missing indexes
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Index fragmentation
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Unused indexes
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Summary
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Chapter 6: Understanding Statistics
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Chapter 6: Understanding Statistics
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Exploring statistics
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Histograms
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A new cardinality estimator
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Cardinality estimation errors
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Incremental statistics
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Statistics on computed columns
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Filtered statistics
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Statistics on ascending keys
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UPDATE STATISTICS with ROWCOUNT and PAGECOUNT
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Statistics maintenance
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Cost estimation
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Summary
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Chapter 7: In-Memory OLTP
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Chapter 7: In-Memory OLTP
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In-memory OLTP architecture
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Tables and indexes
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Natively compiled stored procedures
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Limitations and later enhancements
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Summary
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Chapter 8: Understanding Plan Caching
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Chapter 8: Understanding Plan Caching
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Batch compilation and recompilation
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Exploring the plan cache
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Understanding parameterization
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Parameter sniffing
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Parameter-sensitive plan optimization
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Summary
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Chapter 9: The Query Store
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Chapter 9: The Query Store
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Using the Query Store
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Querying the Query Store
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Summary
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Chapter 10: Intelligent Query Processing
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Chapter 10: Intelligent Query Processing
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Overview of intelligent query processing
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Memory grant feedback
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Cardinality estimation feedback
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Degree of parallelism feedback
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Interleaved execution
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Table variable deferred compilation
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Adaptive joins
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Summary
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Chapter 11: An Introduction to Data Warehouses
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Chapter 11: An Introduction to Data Warehouses
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Data warehouses
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Star join query optimization
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Columnstore indexes
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Summary
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Chapter 12: Understanding Query Hints
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Chapter 12: Understanding Query Hints
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Breaking down complex queries
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Hints
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Joins
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Aggregations
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FORCE ORDER
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The INDEX, FORCESCAN, and FORCESEEK hints
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FAST N
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The NOEXPAND and EXPAND VIEWS hints
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Plan guides
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USE PLAN
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Summary
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Why subscribe?
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Other Books You May Enjoy
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Other Books You May Enjoy
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Packt is searching for authors like you
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Parallelism

SQL Server can use parallelism to help execute some expensive queries faster by using several processors simultaneously. However, even when a query might get better performance by using parallel plans, it could still use more resources than a similar serial plan.

For the query optimizer to consider parallel plans, the SQL Server installation must have access to at least two processors or cores or a hyper-threaded configuration. In addition, both the affinity mask and the maximum degree of parallelism advanced configuration options must allow the use of at least two processors, which they do by default. Finally, as explained later in this section, SQL Server will only consider parallelism for serial queries whose cost exceeds the configured cost threshold for parallelism, where the default value is 5.

The affinity mask configuration option specifies which processors are eligible to run SQL Server threads, and the default value of 0 means that all the processors can...

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