Скачать или смотреть How to Optimize Database Access Speed in Progress 4GL

Discover effective strategies to improve query performance in Progress 4GL, enhancing speed and efficiency of database access for large datasets.
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Optimizing Database Access Speed in Progress 4GL

When dealing with large datasets in Progress 4GL, one of the most common challenges developers face is achieving optimal database access speed. If you've noticed that retrieving records from a database can become time-consuming, especially when using complex queries or fetching data with multiple iterations, you're not alone. In this guide, we'll explore how to make database access faster, particularly when dealing with large data sets with unique indexes.

The Problem

In the situation presented, the developer experienced variability in database access times while retrieving data. Although getting the first record was quick, subsequent records often took significantly longer. This was compounded by the need to loop through a large series of records, leading to performance bottlenecks. The challenge was to speed up this database interaction without sacrificing data integrity or accuracy.

Solution Overview

To improve the efficiency of database access in Progress 4GL, we can implement the following strategies:

Using Temporary Tables

Optimizing Query Conditions

Revisiting Index Structures

Minimizing Nested Loops

Let's dive deeper into each of these strategies.

1. Using Temporary Tables

Instead of refetching records from the database for each iteration, using a temporary table (temp-table) can minimize repetitive database queries. Here’s a code snippet to illustrate this:

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By creating a temp-table that only holds necessary records, we reduce the number of database hits dramatically.

2. Optimizing Query Conditions

The WHERE clause can significantly impact performance. Instead of using conditions that may perform poorly, consider simplifying them or using alternative conditions. For example:

Less Efficient:

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More Efficient:

Instead, use specific equality checks if the values for serial_f_chr11 are limited. This can markedly improve access speed:

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3. Revisiting Index Structures

Check the indexing strategy for the tables involved. Make use of composite indexes where appropriate:

Identify appropriate composite indexes for fields queried together frequently.

Ensure single-component indexes are effective for quick lookups.

4. Minimizing Nested Loops

Where feasible, avoid deep nested loops which can greatly increase execution times:

Instead of looping over all the master records, fetching the relevant details first and then matching them against the master records can streamline the process:

[[See Video to Reveal this Text or Code Snippet]]

Conclusion

By leveraging these strategies, developers can significantly enhance the performance of database access in Progress 4GL applications. Implementing temporary tables, optimizing query conditions, reevaluating indexes, and reducing nested loops are all effective ways to tackle the challenges of large datasets. These improvements will not only lead to faster database access but also create a more efficient user experience for web applications powered by WebSpeed.

For further optimizations, always consider the specific requirements of your application and test different approaches to find the best performance gains.