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SQL Server Query Tuning and Optimization

You're reading from   SQL Server Query Tuning and Optimization Optimize Microsoft SQL Server 2022 queries and applications

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Product type Paperback
Published in Aug 2022
Publisher Packt
ISBN-13 9781803242620
Length 446 pages
Edition 1st Edition
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Author (1):
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Benjamin Nevarez Benjamin Nevarez
Author Profile Icon Benjamin Nevarez
Benjamin Nevarez
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Table of Contents (14) Chapters Close

Preface 1. Chapter 1: An Introduction to Query Tuning and Optimization 2. Chapter 2: Troubleshooting Queries FREE CHAPTER 3. Chapter 3: The Query Optimizer 4. Chapter 4: The Execution Engine 5. Chapter 5: Working with Indexes 6. Chapter 6: Understanding Statistics 7. Chapter 7: In-Memory OLTP 8. Chapter 8: Understanding Plan Caching 9. Chapter 9: The Query Store 10. Chapter 10: Intelligent Query Processing 11. Chapter 11: An Introduction to Data Warehouses 12. Chapter 12: Understanding Query Hints 13. Other Books You May Enjoy

Aggregations

Just like join algorithms, aggregation algorithms can also be forced by using the GROUP hints. Specifically, the ORDER GROUP hint requests that the query optimizer use a Stream Aggregate algorithm, while the HASH GROUP hint requests a Hash Aggregate algorithm. These hints can only be specified at the query level, so they will impact all the aggregation operations in the query. To see the effects of this, take a look at the following unhinted query, which uses a Stream Aggregate operator:

SELECT SalesOrderID, COUNT(*)
FROM Sales.SalesOrderDetail
GROUP BY SalesOrderID

This produces the following plan:

Figure 12.8 – A query using Stream Aggregate

Figure 12.8 – A query using Stream Aggregate

Because the SalesOrderDetail table has a clustered index on the SalesOrderID column, and therefore the data is already sorted on the GROUP BY column, using a Stream Aggregate operator is the obvious choice. However, if we add a HASH GROUP hint to the previous query, as shown here,...

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