2024-10-09
315 reads
2024-10-09
315 reads
2024-10-02
398 reads
In-Memory OLTP was introduced with SQL Server 2014 as a way to improve transaction performance. There are several scenarios that are not supported, such as some data types, and Darko Martinovic describes the issues and provides workarounds. He also has provided a tool to assist in migrating disk-based tables to In-Memory optimized tables.
2018-06-11
3,363 reads
This paper shares the approach used to understand and determine: 1) Using ‘Hekaton’ in SQL Server 2014 against RPM, including performance analysis. 2)
Understand the specifics involved while migrating to Hekaton.
2017-08-09
3,784 reads
2017-03-24
996 reads
2016-10-06
1,039 reads
By HeyMo0sh
Over time, I’ve realised that one of the hardest parts of cloud management isn’t...
By HeyMo0sh
One of the biggest challenges I’ve faced in cloud operations is maintaining clear visibility...
By Steve Jones
I come to Heathrow often. Today is likely somewhere close to 60 trips to...
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