NocoBase Loading Performance Differences According To Roles

In the realm of NocoBase, a fascinating observation has surfaced concerning the loading performance variations attributed to different user roles. This article delves into a reported issue where page load times and select item performance diverge significantly between roles such as Root/Admin and Member. Let's explore the intricacies of this performance disparity and shed light on potential causes and solutions.

Understanding the Bug: A Performance Divide in NocoBase

The core issue lies in the stark contrast in page loading performance based on user roles within NocoBase. When users with Root or Admin roles access pages, the loading times are impressively swift, typically ranging from 1 to 2 seconds. However, a noticeable slowdown occurs when users with the Member role attempt to load the same pages, with loading times extending to approximately 10 seconds. This discrepancy raises concerns about the efficiency and user experience for Members within the NocoBase platform.

This performance bottleneck extends beyond page loading, manifesting itself in the selection of table items within select components. Specifically, when a table is related to another table, and a select component is used in the related table form to choose items from the primary table, the same performance issue arises. This suggests a systemic challenge where role-based access or data handling introduces delays for Member roles.

The issue is particularly evident when dealing with tables containing a substantial number of records. For instance, a table with 600 records exacerbates the loading time difference between Root/Admin and Member roles. This observation underscores the importance of optimizing data retrieval and rendering processes to ensure a consistent and responsive user experience across all roles. To address this bug effectively, a comprehensive understanding of the underlying factors contributing to the performance disparity is crucial. This involves scrutinizing database queries, access control mechanisms, and data rendering strategies to identify potential bottlenecks and implement targeted optimizations.

Environment Details: Setting the Stage for Troubleshooting

To effectively diagnose and resolve performance issues, understanding the environment in which the bug manifests is paramount. In this specific case, the NocoBase version in use is 1.7.20, providing a crucial baseline for investigation. The database underpinning the NocoBase instance is PostgreSQL 15, a robust and widely-used relational database management system. The choice of PostgreSQL as the database backend introduces specific considerations for performance tuning, such as query optimization and indexing strategies.

The operating system hosting the NocoBase application is Windows 10, a common desktop environment. However, it's essential to note that the deployment method employed is Git source code, indicating a custom deployment setup. This deployment approach introduces flexibility but also necessitates careful configuration and maintenance. The Node.js version powering the NocoBase application is v22.14.0, highlighting the runtime environment in which the application operates. The Node.js version can influence performance characteristics, particularly in areas such as asynchronous operations and event handling.

The specific combination of these environmental factors—NocoBase version, database type and version, operating system, deployment method, and Node.js version—shapes the context in which the performance issue occurs. Understanding these details allows developers and administrators to tailor their troubleshooting efforts and focus on areas where performance optimizations are most likely to yield results. For example, the use of PostgreSQL 15 suggests a need to examine query performance and indexing strategies, while the Git source code deployment method emphasizes the importance of proper configuration and code optimization.

Steps to Reproduce: Pinpointing the Performance Bottleneck

To effectively address the performance disparity between roles in NocoBase, a clear and detailed reproduction process is essential. The following steps outline how to replicate the page loading performance issue:

1. Establish a Table with a Substantial Number of Records: Create a table within NocoBase containing approximately 600 records. This sizable dataset serves as a catalyst for highlighting performance differences between roles.
2. Craft a Page Utilizing the Table Block: Design a page within NocoBase and incorporate a table block to display the contents of the previously created table. The table block serves as the visual representation of the data, allowing users to interact with and view the records.
3. Observe Loading Times with Root and Admin Roles: Log in to NocoBase using an account with Root or Admin privileges. Navigate to the page created in step 2 and observe the loading time. Under these roles, the page should load relatively quickly, typically within 1 to 2 seconds.
4. Compare Loading Times with the Member Role: Log out of the Root or Admin account and log in using an account with the Member role. Access the same page and carefully note the loading time. The expectation is that the page will load significantly slower, around 10 seconds or more.

These steps provide a clear and repeatable process for demonstrating the page loading performance issue. Similarly, the following steps illustrate how to reproduce the select item performance issue:

1. Construct Form Block with Select Component: Create a form block within NocoBase and include a select component. This component will be used to choose related table items.
2. Link Select Component to Related Table Items: Configure the select component to display items from a related table. This establishes a connection between the form and the data source for selection.
3. Assess Select Component Performance Across Roles: Open the select component while logged in with different roles (Root, Admin, and Member) and observe the performance. The expectation is that the loading and display of select items will be slower for the Member role compared to Root and Admin roles.

By meticulously following these steps, developers and administrators can consistently reproduce the performance issues, enabling them to focus their efforts on identifying the root causes and implementing effective solutions. The detailed reproduction process also aids in validating the effectiveness of any implemented fixes or optimizations.

Expected Behavior: A Vision of Performance Parity

The anticipated behavior within NocoBase is that page loading and select item operations should exhibit consistent performance regardless of the user's role. The fundamental expectation is that all users, whether Root, Admin, or Member, should experience swift and responsive interactions with the application. This means that page load times and the display of select items should be optimized to minimize delays and provide a seamless user experience. The goal is to eliminate the performance disparity currently observed between roles, where Member users encounter significantly slower loading times compared to Root and Admin users.

A crucial aspect of achieving this performance parity is ensuring that data access and rendering processes are optimized for all roles. This involves scrutinizing database queries, access control mechanisms, and data rendering strategies to identify and address any bottlenecks that disproportionately impact certain roles. For instance, if role-based access control introduces delays in data retrieval for Member roles, the access control implementation may need to be refined to ensure efficient data access for all users. Similarly, if data rendering processes are not optimized for large datasets, loading times may suffer, particularly for tables with a substantial number of records.

Ultimately, the desired behavior is a NocoBase environment where performance is not contingent on the user's role. This not only enhances the overall user experience but also promotes fairness and accessibility within the application. When all users can interact with NocoBase seamlessly and efficiently, the platform becomes more valuable and productive for everyone involved. Achieving this vision requires a concerted effort to optimize various aspects of the application, from data access and processing to rendering and user interface interactions.

Visual Aids: Screenshots for Enhanced Understanding

To facilitate a deeper understanding of the performance issues within NocoBase, visual aids such as screenshots play a crucial role. Screenshots can effectively capture the discrepancies in page loading times and select item performance observed across different roles. For example, a screenshot illustrating the loading time for a page under the Root or Admin role, juxtaposed with a screenshot showcasing the significantly longer loading time for the same page under the Member role, can vividly highlight the performance disparity. Similarly, screenshots depicting the delayed display of select items for the Member role, compared to the near-instantaneous display for Root or Admin roles, can underscore the performance bottleneck in select operations.

The strategic use of screenshots can also aid in pinpointing the specific elements or components that contribute to the performance issues. For instance, a screenshot highlighting a slow-loading table block or a sluggish select component can direct attention to the areas where optimization efforts should be focused. Screenshots can also serve as a valuable tool for communicating the nature and severity of the performance issues to developers and administrators, enabling them to prioritize and address the issues effectively. In addition to capturing performance metrics, screenshots can also illustrate the user experience impact of the performance issues. For example, a screenshot showing a blank or partially loaded page for an extended period can convey the frustration and inconvenience faced by users with the Member role. By visually representing the user experience impact, screenshots can help drive a sense of urgency and importance in resolving the performance issues.

Logs: Tracing the Root Cause of Performance Issues

Logs serve as a vital resource for tracing the root cause of performance issues within NocoBase. Specifically, server logs provide a detailed record of the application's behavior, including API requests, database queries, and any errors or warnings encountered. When performance issues manifest as API errors, server logs become indispensable for identifying the nature of the errors, their frequency, and the circumstances under which they occur. By analyzing the log entries associated with API errors, developers can gain valuable insights into the underlying causes of the performance bottlenecks.

The process of log analysis involves scrutinizing the timestamps, error messages, and other contextual information contained within the log entries. For instance, if a particular API request consistently results in a timeout error or a database query takes an excessively long time to execute, the logs will provide evidence of these issues. By correlating log entries with the observed performance issues, developers can narrow down the potential causes and focus their debugging efforts on the most likely culprits. In addition to API errors, server logs can also reveal performance-related issues that do not necessarily result in explicit errors. For example, slow database queries or inefficient code execution may not trigger errors but can still contribute to performance degradation. By monitoring the execution times of various operations, developers can identify areas where optimizations are needed.

The effectiveness of log analysis depends on the level of detail and granularity provided by the logging configuration. A well-configured logging system will capture sufficient information to enable thorough analysis without overwhelming developers with irrelevant data. It's also essential to have a robust log management system in place, allowing developers to easily search, filter, and analyze log entries. In the context of the role-based performance issues within NocoBase, server logs can be instrumental in identifying whether specific database queries or API requests are being executed differently for different roles. By comparing the log entries for Root/Admin roles with those for Member roles, developers can pinpoint any discrepancies in data access patterns or query execution plans that may be contributing to the performance disparity.

By leveraging logs effectively, developers can gain a deep understanding of the inner workings of the NocoBase application and identify the root causes of performance issues. This knowledge is essential for implementing targeted optimizations and ensuring a consistent and responsive user experience for all roles.

By addressing the performance disparities between roles, NocoBase can deliver a smoother and more equitable experience for all users, enhancing its overall usability and effectiveness.