6 points to consider about when to use Table I/Os vs Cache in C business functions

6 points to consider about when to use Table I/Os vs Cache in C business functions.

Author : Deepak Sharma



In JD Edwards (JDE) C business functions, deciding whether to use table I/Os or cache for data

access depends on the specific requirements of your application and the performance

considerations. Here’s a brief overview of when to use each approach:


1. Table I/Os:

-Use table I/Os when you need to access data from the database and have real-time data requirements.

-Table I/Os directly interact with the database tables, fetching data when needed.

-This approach ensures you get the latest data from the database.

-Table I/Os are suitable when dealing with small data sets or when caching data might consume more memory than necessary.


2. Cache:

-Use cache when you need to frequently access the same data, and real-time data is not strictly required.

-Caching data can significantly improve performance by reducing the number of database hits. 

-Data that doesn’t change frequently or is shared across multiple users can be good candidates for caching.

-Cache can be especially beneficial for data that requires complex processing, as it eliminates the need to repeat the same calculations on each access.

-JDE provides the Cache Manager to manage caching. You can define and control the caching behavior for specific data through cache management.


When deciding between table I/Os and cache, consider the following factors:


  1. Data Volatility- If the data frequently changes or needs to be up to date at all times, table I/Os might be a better choice to ensure real-time data accuracy.
  2. Data Size- If the dataset is relatively small and can be managed in memory without causing memory issues, using table I/Os might be acceptable. However, for larger datasets, caching can help improve performance significantly.
  3. Data Usage Patterns- Analyze how frequently the data is accessed and if there are any repetitive or redundant data requests. Frequent and repetitive access to the same data suggests caching may be beneficial.
  4. Data Processing Complexity- If the data requires complex calculations or joins with other tables, caching the results of these calculations can significantly improve the overall performance.
  5. Concurrency- Consider how multiple users accessing the same data simultaneously might affect the system. Caching can help reduce the load on the database in situations with high concurrency.
  6. Resource Utilization- Evaluate the system resources available. Caching data consumes memory, so ensure that caching won’t lead to memory constraints.

Ultimately, the decision to use table I/Os or cache depends on striking a balance between real- time data requirements and performance optimization. In many cases, a combination of both approaches may be the most appropriate solution, using cache for frequently accessed data and table I/Os for real-time updates or when the cache needs to be refreshed. Properly optimizing data access methods can lead to significant improvements in JDE application performance and user experience.

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