Toward Integrity Part 4
An exploration of the process of translating a conceptual model to a logical model, and ultimately, a faithful implementation using T-SQL.
An exploration of the process of translating a conceptual model to a logical model, and ultimately, a faithful implementation using T-SQL.
Gregory Larsen discusses how to use the TOP clause to help solve requests where you want to restrict the number of records returned based on a record count.
Some new interresting points about trees and CTE in SQL Server : transforming a tree from auto reference to interval model (nested sets), calculating levels in interval model, creating a view of auto ref from an interval model, hierarchical numbering of items, and more. This article includes more examples based on his previous work.
How many DBAs need a solution to track those changes made for multiple systems? Auditing is becoming more and more prevalent in all systems and having a good solution can really make your DBA job interesting. New author Keren Ramot brings us his technique that works indepedent of the database structure.
Steve Jones takes a look at what's happening in the world of alternative energy, including cleaner nuclear power and energy from motion.
How do you cope with an executive's request to "bring back a time series of activity for all subscribers who were in platinum status as of X date," or "show me a time series of orders by sales region according to the sales organization as of Y"? Here's how data warehouse pros can cope with the common requirement to look back in time.
To optimize Transact SQL (T-SQL) data types in SQL Server, learn how each type affects performance -- I/O, RAM and CPU in SQL Server.
Keeping track of the amount of space in a database is something every DBA needs to do or face the dreaded "out of space" errors appearing on every client's desktop. SQL Server guru David Poole brings us an automated way of doing just that.
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Comments posted to this topic are about the item Fun with JSON II
Comments posted to this topic are about the item Changing Data Types
Comments posted to this topic are about the item Answering Questions On Dropped Columns
I have some data in a table:
CREATE TABLE #test_data
(
id INT PRIMARY KEY,
name VARCHAR(100),
birth_date DATE
);
-- Step 2: Insert rows
INSERT INTO #test_data
VALUES
(1, 'Olivia', '2025-01-05'),
(2, 'Emma', '2025-03-02'),
(3, 'Liam', '2025-11-15'),
(4, 'Noah', '2025-12-22');
If I run this query, how many rows are returned?
SELECT t1.[key] AS row,
t2.*
FROM OPENJSON(
(
SELECT t.* FROM #test_data AS t FOR JSON PATH
)
) t1
CROSS APPLY OPENJSON(t1.value) t2; See possible answers