Amoro: Merging CalculateQuotaOccupy For Optimization

Hey guys! Today, let's dive into an exciting improvement we can make within the Amoro project. This is all about streamlining our code, making it more maintainable, and ensuring consistency across different parts of the system. We're going to talk about merging similar implementations of the calculateQuotaOccupy function. Sounds interesting? Let's jump in!

The Current Situation: Redundancy in Calculation

Currently, within Amoro, we have two instances where we're using the calculateQuotaOccupy function. This function is crucial for determining the occupation results for each table in the optimizing management Web UI, and it's also used when scheduling a table for optimization. Take a look at these scenarios:

1. Displaying Occupation Results in Web UI:

   When you're navigating the optimizing management Web UI, you'll see the occupation results for each table. This helps in understanding the current state and resource usage of your tables.

   <img width="778" height="666" alt="Image" src="https://github.com/user-attachments/assets/6d47a638-4eea-491f-9a68-82b3ac679a05" />
   

2. Scheduling Tables for Optimization:

   When a table is scheduled for optimization, its occupation needs to be calculated. This calculation helps in determining the scheduling priority, ensuring that the most critical tables are optimized first.

   <img width="809" height="475" alt="Image" src="https://github.com/user-attachments/assets/60f13635-019b-45ee-98c6-e457bee9358b" />
   

Now, here’s the kicker: these two calculations are nearly identical. This means we have the same logic implemented in two different places, which, as you might guess, isn't the best practice. Why? Well, let’s explore the problems this redundancy can cause and why merging these implementations is a smart move.

The Problem with Redundant Code

Redundant code, where the same logic is duplicated across different parts of a codebase, can lead to several issues. In our case with the calculateQuotaOccupy function, having two nearly identical implementations poses a few key challenges:

• Inconsistency: Imagine a scenario where we need to update the logic for calculating quota occupancy. If we have two separate implementations, we need to remember to update both. It’s easy to miss one, leading to inconsistencies in how occupancy is calculated and displayed in different parts of the system. This can create confusion and potentially lead to incorrect decisions based on the data.
• Maintainability: Maintaining duplicate code is a headache. Every time a change is required, it needs to be applied in multiple places. This increases the effort and time required for maintenance, and it also raises the risk of introducing bugs. The more places you have to change the same logic, the higher the chance that you’ll make a mistake somewhere.
• Increased Complexity: Duplicate code adds unnecessary complexity to the codebase. It makes the code harder to read, understand, and debug. When developers have to navigate through multiple implementations of the same logic, it slows down the development process and increases the likelihood of errors.

Given these challenges, it's clear that merging the implementations of calculateQuotaOccupy is a worthwhile endeavor. By consolidating the logic into a single function, we can avoid these pitfalls and create a more robust and maintainable system. So, how do we go about improving this situation? Let's dive into the proposed solution.

The Proposed Solution: A Unified calculateQuotaOccupy Function

The solution here is straightforward but highly effective: we're going to merge the two nearly identical calculateQuotaOccupy function implementations into a single, unified function. This means we’ll have one source of truth for calculating quota occupancy, which will be used both in the optimizing management Web UI and when scheduling tables for optimization. This approach brings several key benefits:

• Consistency: By having a single implementation, we ensure that the calculation of quota occupancy is consistent across the entire system. Whether you're viewing the occupation results in the Web UI or the system is determining scheduling priorities, the calculation will be the same. This eliminates any confusion or discrepancies that might arise from having different implementations.
• Maintainability: With just one function to maintain, making updates and bug fixes becomes much simpler. If we need to change the logic for calculating quota occupancy, we only need to modify it in one place. This reduces the risk of introducing errors and saves time and effort.
• Reduced Complexity: Consolidating the code reduces the overall complexity of the system. It makes the codebase easier to read, understand, and debug. This is especially beneficial for new developers joining the project, as they only need to understand one implementation of the function.

Implementing the Solution: OptimizingUtil to the Rescue

So, where should this unified calculateQuotaOccupy function live? The suggestion is to implement it in a utility class called OptimizingUtil. Utility classes are designed to hold reusable functions that can be used across different parts of the system. This makes OptimizingUtil the perfect place for our consolidated function.

By placing the function in OptimizingUtil, we make it easily accessible to both the Web UI components and the scheduling components. This ensures that both parts of the system can use the same function without any duplication of code. Here’s a step-by-step breakdown of how we can implement this solution:

1. Identify the Common Logic: First, we need to carefully examine the two existing implementations of calculateQuotaOccupy and identify the common logic between them. This will form the core of our unified function.
2. Create the Unified Function: Next, we’ll create a new function in the OptimizingUtil class. This function will encapsulate the common logic we identified in the previous step. We’ll ensure that it can handle all the necessary inputs and produce the correct output for both use cases.
3. Replace Existing Implementations: Finally, we’ll replace the existing implementations in the Web UI components and the scheduling components with calls to the new unified function in OptimizingUtil. This will ensure that both parts of the system are using the same logic.

By following these steps, we can successfully merge the implementations of calculateQuotaOccupy and create a more maintainable and consistent system. Now, let's talk about why this seemingly small change can have a significant impact on the project.

Why This Matters: The Bigger Picture

Merging the calculateQuotaOccupy function might seem like a small, incremental change, but it's these kinds of improvements that collectively make a big difference in the long run. By addressing code redundancy and promoting code reuse, we're not just making the codebase cleaner; we're also contributing to the overall health and sustainability of the Amoro project. Let’s explore the broader implications of this improvement:

• Improved Code Quality: Code quality is a crucial aspect of any software project. By reducing redundancy, we're making the code more concise, readable, and maintainable. This makes it easier for developers to work on the project, understand the code, and contribute effectively. High-quality code is less prone to bugs and easier to test, leading to a more stable and reliable system.
• Faster Development Cycles: When the codebase is clean and well-organized, development cycles become faster. Developers spend less time navigating through complex code structures and more time implementing new features and fixing bugs. This means we can deliver value to users more quickly and respond to changing requirements more efficiently.
• Easier Collaboration: A clean and consistent codebase makes it easier for developers to collaborate. When everyone is working with the same set of functions and logic, there's less room for misunderstandings and conflicts. This promotes better teamwork and allows developers to leverage each other's expertise more effectively.
• Reduced Technical Debt: Technical debt refers to the implied cost of rework caused by choosing an easy solution now instead of using a better approach that would take longer. Code redundancy is a form of technical debt. By addressing it, we're reducing the long-term costs associated with maintaining the system. This frees up resources that can be used for more strategic initiatives.

In essence, merging the calculateQuotaOccupy function is a proactive step towards building a more robust, scalable, and maintainable system. It’s a testament to the importance of continuous improvement and the value of paying attention to the details. By addressing these small issues, we set the stage for bigger accomplishments and ensure the long-term success of the Amoro project. Now, let's talk about the next steps and how you can contribute to this effort.

Call to Action: Let’s Make This Happen!

So, guys, are you as excited about this improvement as I am? The good news is that this isn't just a theoretical discussion; it's something we can actively work on and implement. And guess what? The person who proposed this improvement is willing to submit a pull request (PR)! This is fantastic because it means we have someone ready to take the lead and make this happen.

But, of course, this is a community effort, and everyone's contribution is valuable. Whether you're an experienced developer or new to the project, there are plenty of ways you can get involved. Here are a few ideas:

• Review the Proposal: Take some time to read through the proposal and understand the problem and the proposed solution. Your feedback and insights are valuable, so don't hesitate to share your thoughts and suggestions.
• Contribute to the Implementation: If you're a developer, you can help with the implementation of the unified calculateQuotaOccupy function. You can work on identifying the common logic, creating the function in OptimizingUtil, or replacing the existing implementations.
• Test the Changes: Once the changes are implemented, thorough testing is crucial to ensure that everything is working as expected. You can help by writing unit tests, performing integration tests, or manually testing the functionality in the Web UI and the scheduling components.
• Spread the Word: Share this proposal with other members of the community and encourage them to get involved. The more people who contribute, the better the outcome will be.

Remember, every contribution, no matter how small, makes a difference. By working together, we can make Amoro an even better project. If you're interested in contributing or have any questions, don't hesitate to reach out and join the discussion. Let’s make this happen and continue to improve Amoro together!

Conclusion: Streamlining for Success

In conclusion, the proposal to merge similar calculateQuotaOccupy function implementations in Amoro is a fantastic step towards improving code quality, maintainability, and consistency. By consolidating the logic into a single function within OptimizingUtil, we're not just addressing code redundancy; we're also setting the stage for faster development cycles, easier collaboration, and reduced technical debt. This might seem like a small change, but it’s these kinds of improvements that collectively make a big impact on the long-term health and sustainability of the project.

So, let's rally together, contribute our expertise, and make this improvement a reality. Whether it's reviewing the proposal, implementing the changes, testing the functionality, or spreading the word, every contribution counts. By working together, we can ensure that Amoro continues to thrive and deliver value to its users. Thanks for taking the time to read through this discussion, and I look forward to seeing your contributions to this exciting improvement!