Best Practices for Storing and Loading JSON Objects from a Large SQL Server Table Using .NET Core Introduction JSON (JavaScript Object Notation) is widely used for storing structured data in SQL Server. However, when dealing with large tables, inefficient handling of JSON data can lead to performance bottlenecks, high storage costs, and slow queries. In this article, we will cover best practices for saving and loading JSON objects from large SQL Server tables using .NET Core. We will focus on storage strategies, indexing, efficient querying, and optimized data retrieval using Entity Framework Core (EF Core) and Dapper. --- 1. Choosing the Right Storage Strategy SQL Server supports JSON natively, but choosing the correct storage method depends on your use case. Option 1: Store JSON as NVARCHAR(MAX) (Best for Flexibility & Simplicity) ✔ Ideal for semi-structured or frequently changing data. ✔ Suitable when you need to store the entire JSON object but rarely query individual fiel...
Pooling is performed in neural networks to reduce variance and computation complexity. Many times, beginners blindly use a pooling method without knowing the reason for using it. Here is a comparison of three basic pooling methods that are widely used. The three types of pooling operations are: Max pooling: The maximum pixel value of the batch is selected. Min pooling: The minimum pixel value of the batch is selected. Average pooling: The average value of all the pixels in the batch is selected. The batch here means a group of pixels of size equal to the filter size which is decided based on the size of the image. In the following example, a filter of 9x9 is chosen. The output of the pooling method varies with the varying value of the filter size. The operations are illustrated through the following figures. Average, Max and Min pooling of size 9x9 applied on an image We cannot say that a particular pooling method is better over others generally. The choice of pooling operation is made...
Polling vs. SignalR: A Detailed Comparison Both Polling and SignalR are techniques used to fetch or receive real-time updates from a server, but they work differently. Here’s a comprehensive comparison to help you choose the right approach. 1. Overview 2. How They Work Polling The client repeatedly sends requests at fixed intervals (e.g., every 5 seconds). The server responds with data (whether there are changes or not). If no new data, the response is wasted network traffic . 🔹 Example (Polling in .NET Core) public async Task<List<Message>> PollMessagesAsync() { using var httpClient = new HttpClient(); var response = await httpClient.GetAsync("https://api.example.com/messages"); return await response.Content.ReadAsAsync<List<Message>>(); } Problem: If data updates once every minute , but polling occurs every 5 seconds , that’s 11 wasted requests before useful data arrives. SignalR The client establishes a pers...
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