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Including my content originally published on 𝕏, SQLperformance.com, and SQLblog.com
Showing posts with label Query Optimizer. Show all posts
Showing posts with label Query Optimizer. Show all posts

Sunday 29 April 2012

Query Optimizer Deep Dive – Part 3

Query Optimizer Deep Dive – Part 3

This is the third in a series of posts based on the content of the Query Optimizer Deep Dive presentations I have given over the last month or so at the Auckland SQL Users’ Group, and SQL Saturday events in Wellington, New Zealand and Adelaide, Australia.

Links to other parts of this series: Part 1 Part 2 Part 4

Storage of Alternative Plans

We saw in part 2 how optimizer rules are used to explore logical alternatives for parts of the query tree, and how implementation rules are used to find physical operations to perform each logical steps.

To keep track of all these options, the cost-based part of the SQL Server query optimizer uses a structure called the Memo. This structure is part of the Cascades general optimization framework developed by Goetz Graefe.

Saturday 28 April 2012

Query Optimizer Deep Dive – Part 2

Query Optimizer Deep Dive – Part 2

This is the second in a series of posts based on the content of the Query Optimizer Deep Dive presentations I have given over the last month or so at the Auckland SQL Users’ Group, and SQL Saturday events in Wellington, New Zealand and Adelaide, Australia.

Links to other parts of this series: Part 1 Part 3 Part 4

Cost-Based Optimization Overview

The input to cost-based optimization is a tree of logical operations produced by the previous optimization stages discussed in part one.

Cost-based optimization takes this logical tree, explores logical alternatives (different logical tree shapes that will always produce the same results), generates physical implementations, assigns an estimated cost to each, and finally chooses the cheapest physical option overall.

The goal of cost-based optimization is not to find the best possible physical execution plan by exploring every possible alternative. Rather, the goal is to find a good plan quickly.

Query Optimizer Deep Dive - Part 1

Query Optimizer Deep Dive - Part 1

This is the first in a series of posts based on the content of the Query Optimizer Deep Dive presentations I have given over the last month or so at the Auckland SQL Users’ Group, and SQL Saturday events in Wellington, New Zealand and Adelaide, Australia.

Links to other parts of this series: Part 2 Part 3 Part 4

Introduction

The motivation behind writing these sessions is finding that relatively few people have a good intuition for the way the optimizer works. This is partly because the official documentation is rather sparse, and partly because what information is available is dispersed across many books and blog posts.

The content presented here is very much geared to my preferred way of learning. It shows the concepts in what seems to me to be a reasonably logical sequence, and then provides tools to enable the interested reader to explore further, if desired.

Monday 12 March 2012

Fun with Scalar and Vector Aggregates

Fun with Scalar and Vector Aggregates

There are interesting things to be learned from even the simplest queries.

For example, imagine you are asked to write a query that lists AdventureWorks product names, where the product has at least one entry in the transaction history table, but fewer than ten.

Wednesday 18 January 2012

Dynamic Seeks and Hidden Implicit Conversions

Dynamic Seeks and Hidden Implicit Conversions

A LIKE predicate with only a trailing wildcard can usually use an index seek, as the following AdventureWorks sample database query shows:

SELECT 
    P.[Name]
FROM Production.Product AS P
WHERE 
    P.[Name] LIKE N'D%';

Friday 23 December 2011

Forcing a Parallel Query Execution Plan

Forcing a Parallel Query Execution Plan

This article is for SQL Server developers who have experienced the special kind of frustration that only comes from spending hours trying to convince the query optimizer to generate a parallel execution plan.

This situation often occurs when making an apparently innocuous change to the text of a moderately complex query — a change which somehow manages to turn a parallel plan that executes in ten seconds, into a five-minute serially-executing monster.

Wednesday 21 September 2011

Finding the Statistics Used to Compile an Execution Plan

Finding the Statistics Used to Compile an Execution Plan

In this post, I show you how to determine the statistics objects used by the query optimizer in producing an execution plan.

Note: This technique only applies to queries compiled using the original (70) cardinality estimation model.

Wednesday 23 February 2011

Advanced TSQL Tuning: Why Internals Knowledge Matters

Advanced T-SQL Tuning: Why Internals Knowledge Matters

There is much more to query tuning than reducing logical reads and adding covering nonclustered indexes. Query tuning is not complete as soon as the query returns results quickly in the development or test environments.

In production, your query will compete for memory, CPU, locks, I/O, and other resources on the server. Today’s post looks at some tuning considerations that are often overlooked, and shows how deep internals knowledge can help you write better T-SQL.

Friday 10 December 2010

Heaps of Trouble?

Heaps of Trouble?

Brad Schulz recently wrote about optimizing a query run against tables with no indexes at all. The problem was, predictably, that performance was not very good. The catch was that we are not allowed to create any indexes (or even new statistics) as part of our optimization efforts.

In this post, I’m going to look at the problem from a different angle, and present an alternative solution to the one Brad found.

Thursday 23 September 2010

A Tale of Two Index Hints

A Tale of Two Index Hints

If you look up Table Hints in the official documentation, you’ll find the following statements:

If a clustered index exists, INDEX(0) forces a clustered index scan and INDEX(1) forces a clustered index scan or seek.

If no clustered index exists, INDEX(0) forces a table scan and INDEX(1) is interpreted as an error.

The interesting thing there is that both hints can result in a scan. If that is the case, you might wonder if there is any effective difference between the two.

This blog entry explores that question, and highlights an optimizer quirk that can result in a much less efficient query plan when using INDEX(0). I’ll also cover some stuff about ordering guarantees.

Wednesday 1 September 2010

Inside the Optimizer: Plan Costing

Inside the Optimizer: Plan Costing

A detailed look at costing, and more undocumented optimizer fun.

The SQL Server query optimizer generates a number of physical plan alternatives from a logical requirement expressed in T-SQL. If full cost-based optimization is required, a cost is assigned to each iterator in each alternative plan, and the plan with the lowest overall cost is ultimately selected for execution.

Saturday 31 July 2010

Inside the Optimizer: Constructing a Plan – Part 4

Inside the Optimizer: Constructing a Plan – Part 4

More undocumented ways to explore how the query optimizer works.

Inside the Optimizer: Constructing a Plan – Part 3

Inside the Optimizer: Constructing a Plan – Part 3

Presenting an undocumented Dynamic Management View we can use to identify the optimization rules involved in producing an executable plan.

Thursday 29 July 2010

Inside the Optimizer: Constructing a Plan - Part 2

Inside the Optimizer: Constructing a Plan - Part 2

Continuing the series of posts looking at how the optimizer matches and applies internal rules to refine a query plan.

The last post ended with this query plan:

The optimizer has pushed the predicate ProductNumber LIKE 'T%' down from a Filter to the Index Scan on the Product table, but it remains as a residual predicate.

Inside the Optimizer: Constructing a Plan - Part 1

Inside the Optimizer: Constructing a Plan - Part 1

For today’s entry, I thought we might take a look at how the optimizer builds an executable plan using rules. To illustrate the process performed by the optimizer, we will configure it to produce incrementally better plans by progressively applying the necessary rules.

Wednesday 28 July 2010

The “Segment Top” Query Optimization

The Segment Top Query Optimization

A question that often comes up on the forums is how to get the first or last row from each group of records in a table. This post describes a clever query plan optimisation that SQL Server can use for these types of query.