Скачать или смотреть Are NO_DATA_FOUND Exceptions Bad for Stored Procedure Performance in Oracle PL/SQL?

Explore whether using `NO_DATA_FOUND` exceptions in Oracle PL/SQL stored procedures negatively impacts performance compared to using the `COUNT(*)` method.
---
This video is based on the question https://stackoverflow.com/q/221909/ asked by the user 'AJ.' ( https://stackoverflow.com/u/27457/ ) and on the answer https://stackoverflow.com/a/222347/ provided by the user 'RussellH' ( https://stackoverflow.com/u/30000/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, comments, revision history etc. For example, the original title of the Question was: Oracle PL/SQL - Are NO_DATA_FOUND Exceptions bad for stored procedure performance?

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 2.5' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 3.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Understanding the Performance Impact of NO_DATA_FOUND Exceptions in PL/SQL

When writing stored procedures in Oracle PL/SQL, one common concern developers have is how exceptions, specifically NO_DATA_FOUND, affect performance. This question often arises, particularly when there is heavy conditioning in the procedure that determines whether a record exists. Let's delve into this problem and explore the best practices for handling it efficiently.

The Dilemma: Doing It the Two Ways

In developing your PL/SQL code, you might be faced with the decision of how to check for existence of data. You have at least two approaches:

Using a Count Query:

[[See Video to Reveal this Text or Code Snippet]]

Using Exception Handling:

[[See Video to Reveal this Text or Code Snippet]]

While the second option may seem more elegant and concise, the question arises: Does using exceptions impact performance negatively compared to the count method?

Evaluating the Count Method

Using the COUNT(*) method has its pitfalls. Here's why:

Race Condition Vulnerability: There is an inherent risk if another session modifies the data after the count is retrieved but before the subsequent select operation. This can lead to a situation where the expected data may no longer exist, resulting in an unhandled exception.

The Benefit of Exception Handling

On the other hand, the exception-based approach is generally safer. Here's why:

Robustness: By trying to fetch the data directly and catching the NO_DATA_FOUND exception, your code remains resilient against data changes. If the record does not exist, your procedure handles this gracefully instead of crashing.

Simplicity: The exception-based code directly retrieves the desired values without the need for preliminary checks, thereby reducing unnecessary lines of code and keeping things cleaner.

Performance Considerations: Benchmarking the Approaches

To get a clearer picture of the performance, let’s look at some benchmark results from a test scenario:

Count Method Performance:

[[See Video to Reveal this Text or Code Snippet]]

Elapsed Time: 00:00:02.70

Exception Handling Performance:

[[See Video to Reveal this Text or Code Snippet]]

Elapsed Time: 00:00:03.06

Conclusion: Best Practice Recommendations

While both methods have their performance nuances, it appears that the exception handling approach is not significantly slower than the count method. Moreover, the potential risk of exceptions arising from the count method due to concurrent data modifications makes the exception handling method the preferable choice in most scenarios.

Key Takeaways:

Use the exception-based approach for better error handling and simplicity.

Avoid relying on COUNT(*) due to potential race conditions and unhandled exceptions.

Measure actual performance based on your unique use case, but lean towards safety and clarity in your code.

By opting for robust programming paradigms, you ensure that your PL/SQL stored procedures not only perform well but also gracefully handle unforeseen data changes.