SQL Window Functions Series: RANK() and DENSE_RANK()
Welcome to the fascinating world of SQL window functions! Today, we'll explore in detail: RANK() and DENSE_RANK().
2023-11-20 (first published: 2023-11-15)
13,762 reads
Welcome to the fascinating world of SQL window functions! Today, we'll explore in detail: RANK() and DENSE_RANK().
2023-11-20 (first published: 2023-11-15)
13,762 reads
In this Article , We will delve into the world of Query Store and explore how to use Optimized Plan Forcing to improve performance in SQL Server 2022. We will discuss what it is, how it works, and how it can impact your system's performance.
2023-09-04
5,287 reads
Learn how to conduct deep SQL Query optimization with SQL Grease with the Enterprise dashboard, historical data, troubleshooting SQL Server Wait Stats, capturing anomalies and intelligent notifications.
2022-02-02
As SQL developers, we tend to think of performance tuning in terms of crafting the best table indices, avoiding scalar and table valued functions, and analyzing query plans (among other things). But sometimes going back to the spec and applying some properties of elementary math can be the best way to begin to improve performance of SQL queries which implement mathematical formulas. This article is a case study of how I used this technique to optimize my SQL implementation of the Inverse Simpson Index.
2021-05-07 (first published: 2019-09-12)
5,393 reads
2016-01-14
1,814 reads
In his continuing quest to bring a deeper understanding of Query Optimizer to the world at large, Fabiano Amorim takes a moment to point out a potential pitfall you may encounter. A light read, but one worth persuing.
2010-01-01
3,379 reads
In SQL Server 2005, a feature was introduced that was hardly noticed, but which might make a great difference to anyone doing queries involving temporal data. For anyone doing Data Warehousing, timetabling, or time-based pricing, this could speed up your queries considerably. Who better to introduce this than Query Optimizer expert, Fabiano Amorim?
2009-10-26
3,485 reads
Microsoft SQL Server 2008 collects statistical information about indexes and column data stored in the database. These statistics are used by the SQL Server query optimizer to choose the most efficient plan for retrieving or updating data. This paper describes what data is collected, where it is stored, and which commands create, update, and delete statistics. By default, SQL Server 2008 also creates and updates statistics automatically, when such an operation is considered to be useful. This paper also outlines how these defaults can be changed on different levels (column, table, and database).
2009-07-24
2,506 reads
By Steve Jones
I haven’t done one of these in awhile, but I saw an article recently...
In last months one of the scenarios where you can use AI has been...
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I upgraded a SQL Server 2019 instance to SQL Server 2025. I wanted to test the fuzzy string search functions. I run this code:
SELECT JARO_WINKLER_DISTANCE('tim', 'tom')
I get this error message:Msg 195, Level 15, State 10, Line 1 'JARO_WINKLER_DISTANCE' is not a recognized built-in function name.What is wrong? See possible answers