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)
17,362 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)
17,362 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
5,799 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)
5,513 reads
2016-01-14
1,833 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 use ConEmu for my terminal interface. I’m still on Windows 10 at home,...
Creating a Fabric workspace takes about 30 seconds. Restructuring workspaces after people have built...
By Steve Jones
It’s a small change, but a handy one. Flyway Desktop (FWD) now includes the...
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Which number did the two COUNT(*) return:
DROP TABLE IF EXISTS #tmp CREATE TABLE #tmp (id INT NOT NULL) INSERT INTO #tmp (id) SELECT gs.value FROM GENERATE_SERIES(1, 5) AS gs ALTER TABLE #tmp ADD my_value INT NOT NULL CONSTRAINT df_tmp_my_value DEFAULT 1 SELECT COUNT(*) FROM #tmp AS t WHERE my_value = 1 ALTER TABLE #tmp DROP CONSTRAINT df_tmp_my_value ALTER TABLE #tmp ADD CONSTRAINT df_tmp_my_value DEFAULT 2 FOR my_value SELECT COUNT(*) FROM #tmp AS t WHERE my_value = 1See possible answers