Saturday 23 September 2023

What is the difference between round and ceiling in SQL Server?

In SQL Server, both the ROUND and CEILING functions are used to perform mathematical rounding of numerical values, but they have different behaviors:

  1. ROUND:

    • The ROUND function is used to round a numeric value to a specified number of decimal places.
    • It performs "normal" rounding, which means that if the decimal part is equal to or greater than 0.5, it rounds up; otherwise, it rounds down.
    • It can be used with both positive and negative numbers.
    • The ROUND function takes two arguments: the numeric value to be rounded and the number of decimal places to round to.

    Example:


    SELECT ROUND(3.14159, 2); -- Returns 3.14 
  2. SELECT ROUND(3.6); -- Returns 4 
  3. SELECT ROUND(-3.6); -- Returns -4
  4. CEILING:

    • The CEILING function is used to round a numeric value up to the nearest integer that is greater than or equal to the original value.
    • It always rounds up, regardless of the decimal part of the number.
    • It is commonly used when you want to ensure that a value is rounded up to the nearest whole number, even if the decimal part is very small.
    • The CEILING function takes a single argument, which is the numeric value to be rounded up.

    Example:

    SELECT CEILING(3.14159); -- Returns 4 SELECT CEILING(3.6); -- Returns 4 SELECT CEILING(-3.6); -- Returns -3

In summary, the key difference between ROUND and CEILING in SQL Server is in how they handle rounding. ROUND performs standard rounding based on the decimal part of the number, while CEILING always rounds up to the next integer, regardless of the decimal part. Your choice between them depends on the specific rounding behavior you need for your calculations.

How to implement Azure Application Insight in Web app?

Azure Application Insights is a powerful service for monitoring and gaining insights into the performance and usage of your web applications. To implement Application Insights in a web app, follow these steps:

Step 1: Create an Application Insights resource

Log in to the Azure portal (https://portal.azure.com).

Click on "+ Create a resource" on the left-hand menu.

Search for "Application Insights" in the Azure Marketplace.

Select "Application Insights" from the search results.

Click the "Create" button to create a new Application Insights resource.

Fill in the required details like Subscription, Resource Group, Region, and give it a name. You can also configure the pricing tier based on your needs. Click "Review + create" and then "Create" to provision the resource.

Step 2: Instrument your Web App

Now that you have an Application Insights resource, you need to instrument your web app to send telemetry data to it. This involves adding the Application Insights SDK to your application code. The exact steps may vary depending on the technology stack of your web app.

Below are some common scenarios:

ASP.NET Core Application (C#):

Open your ASP.NET Core project in Visual Studio.

Install the Microsoft.ApplicationInsights.AspNetCore NuGet package if not already installed:


Install-Package Microsoft.ApplicationInsights.AspNetCore

In the Startup.cs file, add the following code in the ConfigureServices method to configure Application Insights:


services.AddApplicationInsightsTelemetry(Configuration["ApplicationInsights:InstrumentationKey"]);
In the appsettings.json file, add your Application Insights Instrumentation Key:


"ApplicationInsights": {
  "InstrumentationKey": "YOUR_INSTRUMENTATION_KEY"
}

Node.js Application:

Install the applicationinsights npm package:


npm install applicationinsights --save

In your Node.js code, require and configure Application Insights using your Instrumentation Key:


const appInsights = require("applicationinsights");
appInsights.setup("YOUR_INSTRUMENTATION_KEY").start();

Other Platforms: Application Insights has SDKs and integrations for various platforms. You can find specific instructions for your technology stack in the official documentation.

Step 3: Verify Integration

After instrumenting your web app, you can verify if telemetry data is being sent to Application Insights:

Run your web app.

In the Azure portal, navigate to your Application Insights resource.

Go to the "Overview" or "Logs" section to see telemetry data, including requests, exceptions, and performance metrics.

Step 4: Analyze and Monitor

With Application Insights set up, you can use it to:

  • Monitor application performance and detect issues.
  • Create custom dashboards and alerts.
  • Analyze user behavior and track conversions.
  • Debug and diagnose problems using distributed tracing.
Application Insights is a powerful tool for gaining insights into your web app's behaviour and performance, helping you improve its reliability and user experience.

Whay is difference between Azure Service Fabric and Azure Function App.

Azure Service Fabric and Azure Function App are both Azure services that can be used for building and deploying applications, but they serve different purposes and have distinct characteristics. Here's a comparison of Azure Service Fabric and Azure Function App: Azure Service Fabric: Service Type: Service Fabric is a platform for building and managing microservices-based applications. It allows you to create and manage services that can be stateful or stateless and supports complex, multi-service applications. Programming Model: You have more control over the code and architecture of your services in Service Fabric. You can choose to use various programming languages (e.g., C#, Java, etc.) and frameworks (e.g., ASP.NET Core, Java Spring Boot) to develop your services. Service Types: Service Fabric supports stateful and stateless services, allowing you to build applications with persistent data and complex service orchestration. Scaling: It provides more granular control over scaling and load balancing. You can manually scale or use auto-scaling rules. Application Types: Service Fabric is suitable for building a wide range of applications, including microservices, containers, and legacy applications. Deployment: You have more control over how services are deployed and upgraded, including version management and rolling upgrades. Use Cases: It's ideal for complex, large-scale applications, especially those requiring high availability, stateful services, and complex service orchestration. Azure Function App: Service Type: Azure Functions is a serverless compute service that allows you to execute code in response to events without managing the underlying infrastructure. Programming Model: Azure Functions use a serverless programming model, where you write individual functions that are triggered by events (e.g., HTTP requests, timers, message queues). You don't need to worry about infrastructure management. Service Types: Azure Functions are typically stateless and designed to execute small units of code in a stateless manner. Scaling: Scaling is handled automatically by Azure Functions based on the number of incoming events or requests. You're billed only for the actual compute resources used during execution. Application Types: Azure Functions are well-suited for event-driven, small-to-medium-sized workloads where you want to focus on code and not worry about infrastructure management. Deployment: You deploy individual functions or sets of functions. Each function can have its own dependencies. Use Cases: Azure Functions are great for event-driven scenarios, such as processing messages from queues, handling HTTP requests, or responding to changes in data. In summary, the choice between Azure Service Fabric and Azure Function App depends on your specific application requirements: Choose Azure Service Fabric if you need fine-grained control over service architecture, stateful services, complex service orchestration, and you're building larger, complex applications. Choose Azure Function App if you want a serverless, event-driven architecture that automatically scales and you're building smaller, more focused functions that respond to events and triggers. Often, both services can be used together within a larger Azure solution to handle different parts of your application's functionality.