How to Decipher sysschedules
Take the mystery out of sysschedules and interpret the data into a plain text format.
2017-06-22
11,552 reads
Articles
SQL Server Row Count for all Tables in a Database
Dattatrey Sindol explains the different ways in which you can get the row counts from all the tables in a SQL Server database.
2017-06-22
5,549 reads
Statistics in SQL: Simple Linear Regressions
Although linear regressions can get complicated, most jobs involving the plotting of a trendline are easy. Simple Linear Regression is handy for the SQL Programmer in making a prediction of a linear trend and giving a figure for the level probability for the prediction, and what is more, they are easy to do with the aggregation that is built into SQL.
2017-06-22
5,131 reads
2017-06-21
156 reads
SQL Azure Reporting Automation
This article will talk about preparing a runbook in Azure to schedule the report of space usage of databases in Azure environment
2017-06-21
1,399 reads
Dealing with High Concurrency with Table Hints
Systems with a large number of requests on a critical database table are prone to blocking and slowness. We take a look at getting things done using T-SQL table hints.
2017-06-20
3,641 reads
Properly Persisted Computed Columns
Paul White walks through a new trace flag in SQL Server 2016 designed to yield better execution plans (and performance) for queries involving computed columns.
2017-06-20
4,841 reads
Statistics in SQL: Kendall’s Tau rank correlation
Statistical calculations in SQL are often perfectly easy to do. SQL was designed to be a natural fit for calculating correlation, regression and variance on large quantities of data. It just isn't always immediately obvious how. In the second of a series of articles, Phil factor shows how calculating a non-parametric correlation via Kendall's Tau or Spearman's Rho can be stress-free.
2017-06-20
3,513 reads
Help for DBAs Who Support SSIS…
SSIS Catalog Compare helps DBAs work with their SSIS project configurations and catalogs, deploying changes from environment to environment.
2017-06-19
1,168 reads
Scoring Outliers with R
What is normal? More to the point, what is abnormal? We will look at using R to score outliers in a typical monitoring dataset.
2017-06-19
4,097 reads
Blogs
Stop Using Pandas for Aggregations — Try DuckDB Instead
If you've ever loaded a 2 GB CSV into pandas just to run a...
Understanding Fabric Ontology
By James Serra
What problem is Fabric Ontology trying to solve? For years, most data conversations have...
QUOTENAME Basics: #SQLNewBlogger
By Steve Jones
Recently I ran across some code that used a lot of QUOTENAME() calls. A...
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The New Software Team
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Database Mail in SQL Server 2022
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The string_agg function
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Question of the Day
The string_agg function
We create the following table and then insert some records in it:
create table t1 ( id int primary key, category char(1) not null, product varchar(50) ); insert into t1 values (1, 'A', 'Product 1'), (2, 'A', 'Product 2'), (3, 'A', 'Product 3'), (4, 'B', 'Product 4'), (5, 'B', 'Product 5');What happens if we execute the following query in both Sql Server and PostgreSQL?
select id,
category,
string_agg(product, ';')
over (partition by category order by id
rows between unbounded preceding and unbounded following) as stragg
from t1; See possible answers