SQL Window Functions Series: LAG() and LEAD()
Dive deep into the powerful SQL window functions, LAG() and LEAD(). Explore their intricacies, discover real-world examples, and avoid common pitfalls.
2023-12-11
9,717 reads
Dive deep into the powerful SQL window functions, LAG() and LEAD(). Explore their intricacies, discover real-world examples, and avoid common pitfalls.
2023-12-11
9,717 reads
In the final article of this series, Edward Pollack demonstrates the maintenance of columnstore indexes. He also takes a look at nonclustered columnstore and memory-optimized columnstore indexes.
2020-08-06
Because of its many roles, tempdb is the source of performance issues in SQL Server, and there are recommended configuration changes to mitigate this. In this article, Fabiano Amorim demonstrates another issue with tempdb performance that you probably didn’t know about.
2020-07-02
Table variables can cause performance issues with joins when they contain a large number of rows. In SQL Server 2019, Microsoft has improved how the optimizer works with table variables which can improve performance without making changes to your code. In this article, Greg Larsen explains how this feature works and if it really does make a difference.
2020-06-22
Microsoft has added a group of features called Intelligent Query Processing to SQL Server 2017 and 2019. In this article, Greg Larsen explains one of the features, Scalar UDF Inlining.
2020-03-02
Window functions are more intuitive and simpler in many cases than alternative SQL methods.
2013-12-02
8,777 reads
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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
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