Optimize Bulk Update and Delete Operations #802
Description
Feature Suggestion: Optimize Bulk Update and Delete Operations
Background
Currently, the BulkUpdateAsync and BulkDeleteAsync methods provided by Z.EntityFramework.Extensions.EFCore are very useful for batch operations. However, there are scenarios where these operations can be further optimized, particularly in terms of selecting columns in subqueries and ensuring efficient locking mechanisms.
Suggestion
I would like to suggest an optimization for the BulkUpdateAsync and BulkDeleteAsync methods. Specifically, when performing bulk updates or deletes based on complex conditions, it would be beneficial to:
-
Select only necessary columns in subqueries:
When forming subqueries to identify rows for updating or deleting, only the primary key or unique identifier columns should be selected. This ensures minimal data retrieval and reduces overhead. -
Efficient Locking Mechanisms:
Ensure that the operations are optimized to use row or page locks where possible, instead of escalating to table locks, to improve concurrency and performance.
Example
Here is an example of the current SQL generated and the proposed optimized SQL:
Current SQL:
UPDATE A
SET A.[Visits] = B.[Visits] + 1
FROM [Blogs] AS A
INNER JOIN
(
SELECT [b].[BlogId], [b].[Url], [b].[Visits]
FROM [Blogs] AS [b]
WHERE [b].[SomeOtherCondition] = 'Value' AND [b].[AnotherCondition] < 0
) AS B
ON A.[BlogId] = B.[BlogId]
Proposed Optimized SQL:
UPDATE A
SET A.[Visits] = B.[Visits] + 1
FROM [Blogs] AS A
INNER JOIN
(
SELECT [b].[BlogId]
FROM [Blogs] AS [b]
WHERE [b].[SomeOtherCondition] = 'Value' AND [b].[AnotherCondition] < 0
) AS B
ON A.[BlogId] = B.[BlogId]
Benefits
Performance: Reducing the number of columns selected in subqueries decreases the amount of data processed and transferred, improving query performance.
Concurrency: Using more granular locking mechanisms (row or page locks) enhances concurrency and reduces contention, especially in high-traffic applications.
Conclusion
Implementing these optimizations will make the bulk operations more efficient and better suited for high-performance scenarios. Thank you for considering this suggestion.