Delta Table Performance Is Governed By Transaction Size: Data Engineering with Fabric
This next article examines the impact of transaction sizes on the performance of our Delta Parquet tables.
2024-09-11
2,186 reads
This next article examines the impact of transaction sizes on the performance of our Delta Parquet tables.
2024-09-11
2,186 reads
In this next installment, John performs the research you might do if your management asked you to examine Fabric.
2024-08-21
3,522 reads
In this next article, learn about the different file formats and which work well inside your Microsoft Fabric Lakehouse.
2024-08-07
3,082 reads
Learn how to manage files and folders in Microsoft Fabric with PowerShell.
2024-07-10
1,859 reads
In this new article, we examine how to work with OneLake storage.
2024-06-26
1,688 reads
Learn how to use the OneLake Explorer and Data Wrangler extension in VS Code to empower users to work with data in Microsoft Fabric.
2024-05-22
1,822 reads
This next article in the series creates objects at the gold layer for consumption by combining tables from the silver layer of the lake house.
2024-05-15
3,457 reads
This article explains metadata driven pipelines and shows an example in Microsoft Fabric.
2024-05-01
5,032 reads
Learn how to perform full and incremental loads in Fabric with a little SparkSQL.
2024-04-17
6,567 reads
In this article, learn how you can manage files and folders for both full and incremental loading situations.
2024-03-27
3,698 reads
By HeyMo0sh
Microsoft Fabric (not to be confused with the more general term “fabric” in DevOps)...
By James Serra
I’m honored to be hosting T-SQL Tuesday — edition #192. For those who may...
By Vinay Thakur
Continuing from Day 2 , we learned introduction on Generative AI and Agentic AI,...
hi everyone I am not sure how to write the query that will produce...
Comments posted to this topic are about the item Rollback vs. Roll Forward
Comments posted to this topic are about the item Foreign Keys - Foes or...
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 *
FROM OPENJSON(
(
SELECT t.* FROM #test_data AS t FOR JSON PATH
)
) t; See possible answers