Occasionally, SQL Server database administrators are requested to provide a list of development SQL Servers, production SQL Servers and so on. Many articles, such as "Monitor Disk Space on Multiple SQL Servers" and "Inventorying hardware and OS information on all SQL Servers" require a list of servers in a text file.
It's not a SQL Server event, but SQL Server is a large part of it. TechEd is a huge conference and one of the premier events put on by Microsoft each year. Read about the first day with Andy, Brian, and Steve.
When a SQL Server object is created, its properties are called metadata. The metadata is stored in special System Tables. For example, in SQL 2000, when a new column was created, the column name and data type could be found in an internal System Table called syscolumns. All SQL objects produce metadata. Every time SQL 2000 Enterprise Manager or SQL 2005 SQL Server Management Studio is browsed, the information displayed about database, tables, and all objects, comes from this metadata.
SQL Server 2000 does a lot of things for the DBA, tuning, updating statistics, scheduling tasks, wizards and more. But one thing that it does not help with is choosing the correct data type for your data. New author Amit Lohia brings us a technique and some code that will examine your existing data and suggest places where another data type might be a better choice.
This paper will explain and show how standard ANSI SQL processors can naturally model and automatically process complex multi-leg hierarchical data structures at a full conceptual hierarchical level. This also means the query user does not need to have structure knowledge of the hierarchical structures involved. The data modeling capability includes dynamically combining logical hierarchical relational and physical XML data structures at a full hierarchical level. This also includes the ability to link below the root of the lower level structure intuitively forming a valid unified hierarchical structure. As will be shown, ANSI SQL’s high level hierarchical data processing allows the flexible conceptual control of hierarchical node promotion, fragment processing, structure transformation, and variable structure creation.
In response to an article the Brian Knight write on the death of the production DBA, Sean McCown writes about the role that DBAs may play in shops that upgrade to Yukon (SQL Server 2005).
My interest in writing this article was started by an MSDN article titled SQL Server 2005: The CLR Enters the Relational Stage. The article shows how to write a function that returns the top three countries per category. That's always been something that was difficult to do in SQL so I was curious about the approach. The article started out well but I was very unhappy by the end. It's just soooo much easier to do this in SQL Server 2005 using the new CROSS APPLY clause in Transact-SQL. So I'm going to write a query to return the top 3 orders for each customer and I'm going to do it in about 10 lines of SQL. (UPDATE: An alert reader found an even better approach!)
Searching data is an essential part of SQL Server applications, especially text searching. While Full Text Search in SQL Server 2000 works, it lacks some important features that Turbo for SQL Server can handle. Read this review of the product and see if this is a way you can enhance the search functions in your application.
Get a detailed look at how to set up SQL Server 2005 for Web service access in a heterogeneous environment, and learn more about key scenarios for Web services in SQL Server 2005.
Kurt Windisch, Vice President of the Professional Association for SQL Server, recently returned from their European Conference. He shares a few notes on the event which was held earlier this month in Germany.
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Over time, I’ve realised that one of the hardest parts of cloud management isn’t...
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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