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How to Efficiently Paginate a ResultSet for Data Management?

Mary-Kate Olsen
Mary-Kate OlsenOriginal
2024-10-24 07:23:02181browse

How to Efficiently Paginate a ResultSet for Data Management?

Paginating a ResultSet

Introduction

To display large result sets in a manageable way, pagination is essential. By enabling users to navigate through the data incrementally, pagination improves the user experience and performance.

Converting a ResultSet to a Paginated View

To convert a ResultSet into a paginated view, the following steps are required:

1. Addition of Request Parameters

Enhance the JSP page with request parameters to define the starting row (firstrow) and the number of rows to fetch (rowcount).

2. Creation of Paging Buttons

Add paging buttons to the JSP page that manipulate the firstrow parameter. The "Next" button should increment firstrow by rowcount, while the "Previous" button should decrement firstrow by rowcount. Ensure to handle extreme values gracefully.

3. Execution of Sublist Query

Retrieve a sublist of the ResultSet using a specific SQL query. Depending on the database, the syntax varies:

  • MySQL/PostgreSQL:

    <code class="sql">SELECT id, username, job, place FROM contact ORDER BY id LIMIT %d OFFSET %d</code>
  • Oracle:

    <code class="sql">SELECT id, username, job, place FROM (SELECT id, username, job, place FROM contact ORDER BY id) WHERE ROWNUM BETWEEN %d AND %d</code>
  • DB2:

    <code class="sql">SELECT id, username, job, place FROM (SELECT row_number() OVER (ORDER BY id) AS row, id, username, job, place FROM contact) AS temp WHERE row BETWEEN %d AND %d</code>

4. Data Presentation

Utilize JSTL c:forEach to render the sublist in the JSP page.

5. Paging Control

Include a form with hidden fields for firstrow and rowcount, as well as submit buttons for next and previous pages. This allows users to manually navigate through the data.

Performance Considerations

Avoid fetching the entire table into memory and storing it in the session scope for pagination. This approach can strain memory resources, especially with large result sets and multiple concurrent users. Instead, use the sublist query approach outlined above to paginate efficiently.

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