The Necessity of Large-Scale Data Pagination
When dealing with expansive datasets, retrieving all records in a single request is computationally expensive and compromises user experience. Efficient data paging ensures that only a specific subset of data is transmitted, reducing latency and resource consumption.
Leveraging LINQ for Linear Pagination
In the .NET ecosystem, Language Integrated Query (LINQ) provides a robust suite of operators—specifically Skip and Take—to facilitate server-side paging with minimal boilerplate.
Prerequisites: Data Modeling and Serialization
For this implementation, we utilize the Newtonsoft.Json library for efficient POCO (Plain Old CLR Object) mapping from a JSON payload.
Install-Package Newtonsoft.Json
public class PostEntry
{
public int UserId { get; set; }
public int Id { get; set; }
public string Title { get; set; }
public string Body { get; set; }
}
Orchestrating the Paging Logic
The following method demonstrates how to calculate the offset dynamically based on the requested page number and page size.
/// <summary>
/// Retrieves a paginated subset of data from a remote source.
/// </summary>
/// <param name="pageSize">Number of records per page.</param>
/// <param name="pageIndex">The specific page to retrieve (1-based).</param>
public List<PostEntry> FetchPaginatedData(int pageSize, int pageIndex, string apiEndpoint)
{
using (WebClient client = new WebClient())
{
string rawJson = client.DownloadString(apiEndpoint);
var fullDataset = JsonConvert.DeserializeObject<List<PostEntry>>(rawJson);
// Applying Skip and Take to derive the specific window of data
return fullDataset
.Skip(pageSize * (pageIndex - 1))
.Take(pageSize)
.ToList();
}
}
Key Architectural Considerations
- Server-Side vs. Client-Side: While this example performs paging in memory after retrieving the full dataset, in production environments (like Entity Framework), these operators are translated directly into SQL
OFFSETandFETCH NEXTcommands, ensuring the database only returns the requested rows. - Performance Optimization: For high-traffic APIs, consider implementing a caching layer (e.g., Redis) or using
IQueryableto defer execution until the paging constraints are applied at the database level. - Scalability: Always validate input parameters (e.g., negative page numbers or excessively large page sizes) to prevent resource exhaustion attacks.
Access the Implementation: A complete, runnable project demonstrating these concepts is available on GitHub.