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Скачать или смотреть Optimizing PL/SQL Procedures: Converting Merge Clause with BULK COLLECT for Improved Performance

  • vlogize
  • 2025-10-02
  • 0
Optimizing PL/SQL Procedures: Converting Merge Clause with BULK COLLECT for Improved Performance
Converting Merge clause with Bulk collect/FORALL in pl/sqlsqloracleperformanceplsqlquery optimization
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Описание к видео Optimizing PL/SQL Procedures: Converting Merge Clause with BULK COLLECT for Improved Performance

Learn how to optimize your PL/SQL procedures by using the `BULK COLLECT` feature to enhance the performance of `MERGE` clauses for updating and inserting records in Oracle.
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This video is based on the question https://stackoverflow.com/q/62620538/ asked by the user 'gudisa' ( https://stackoverflow.com/u/7785139/ ) and on the answer https://stackoverflow.com/a/62644402/ provided by the user 'KOBER' ( https://stackoverflow.com/u/13755032/ ) 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, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Converting Merge clause with Bulk collect/FORALL in pl/sql

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The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

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Introduction

In the world of database management, performance is a crucial aspect to consider when developing procedures that handle data. If you're using PL/SQL to simultaneously update and insert records from a source table to a destination table, you may notice a significant slowdown as the number of records increases. This is especially true when utilizing the MERGE statement within your procedure.
In this guide, we'll explore how you can improve the efficiency of your PL/SQL process by converting your MERGE clause to use the BULK COLLECT feature. This will allow for batch processing of records, resulting in faster execution times, especially when dealing with larger datasets.

Understanding the Problem

The original procedure is functioning correctly for a smaller number of records but is unable to maintain performance when tasked with larger datasets. The lack of bulk operations in your current implementation could be causing the slowdown.
Using a simple loop to process and execute each record can be highly inefficient because it sends multiple context switches to the database, resulting in increased execution time.

Solution: Using BULK COLLECT with MERGE Clause

To optimize your PL/SQL procedure, we'll implement BULK COLLECT for fetching records, coupled with the FORALL statement to execute the MERGE operations in bulk.

Step-by-Step Implementation

Define the Procedure and Cursor:
Start by defining your procedure with a cursor to select distinct records from the source table.

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

Open the Cursor and Fetch Data:
Open the cursor and use a LOOP structure to fetch the records using BULK COLLECT. Set an exit condition when there are no more records to fetch.

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

Use FORALL for Bulk Merge:
Utilize the FORALL statement to iterate over the collected data instead of a regular loop. This allows for bulk execution of the MERGE into the destination table.

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

Close the Cursor:
Finally, do not forget to close the cursor once processing is done to free up resources.

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

Final Procedure Example

Here’s how the complete optimized version of your procedure would look:

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

Conclusion

Converting your MERGE clause with BULK COLLECT in PL/SQL can significantly enhance the performance of your procedure. By leveraging batch processing, you'll minimize context switching, which is essential for efficiently handling larger datasets.
Implement this optimization in your procedures to enjoy improved performance and a smoother experience while working with your Oracle databases.

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