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)
17,367 reads
Query Optimization
Optimized Plan Forcing with Query Store in SQL Server 2022
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
5,804 reads
Deep SQL Query Optimization with SQL Grease
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
Optimize Your SQL by Reformulating the Spec
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)
5,515 reads
2016-01-14
1,834 reads
Query Optimizer and Cartesian Products
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
The Query Optimizer: Date Correlation Optimisation
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
Statistics Used by the Query Optimizer in Microsoft SQL Server 2008
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
Blogs
Prep data for AI vs. Fabric Data Agent Instructions: What Goes Where?
By James Serra
Making Data AI-Ready, Part 3 (This is the final article in a three-part series...
Keeping Track of my ConEmu CLIs
By Steve Jones
I use ConEmu for my terminal interface. I’m still on Windows 10 at home,...
10 Decisions to Make Before You Create A Fabric Workspace
Creating a Fabric workspace takes about 30 seconds. Restructuring workspaces after people have built...
Forums
Adding new column with DEFAULT II
Comments posted to this topic are about the item Adding new column with DEFAULT...
Advanced Deployment Scenarios: Stairway to Reliable Database Deployments Level 7
Comments posted to this topic are about the item Advanced Deployment Scenarios: Stairway to...
You Need a DBA Pipeline
Comments posted to this topic are about the item You Need a DBA Pipeline
Question of the Day
Adding new column with DEFAULT II
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
