Technical Article

Regular Expression Transformation

The regular expression transformation exposes the power of regular expression matching within the pipeline. One or more columns can be selected, and for each column an individual expression can be applied. If all columns selected pass their tests then rows are passed down the successful match output. Rows that fail to pass all tests are directed down the alternate output.

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Fun with JSON II

By Steve Jones - SSC Editor

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Changing Data Types

By Steve Jones - SSC Editor

Comments posted to this topic are about the item Changing Data Types

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Question of the Day

Fun with JSON II

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;

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