Advanced data filtering strategies for web service data control in JDeveloper

This article aims to address the challenge of the lack of "naming guideline" filtering capabilities for Web service data control in JDeveloper. To address this problem, we have proposed two core solutions: one is to complete data pre-filtering on the server side by modifying or implementing Web services; the other is to obtain Web service data into the POJO model on the client side, and then implement data filtering and sorting through programming. The article will elaborate on the implementation ideas, advantages and disadvantages, and applicable scenarios of these two methods.

Data filtering challenges for JDeveloper web service data control

In JDeveloper, when using Web service data control to display data, sometimes you will encounter the need to filter and sort the data. However, some versions of JDeveloper (such as 12.2.1.3.0) or specific Web service data control configurations may not provide built-in "Named Criteria" functionality, which makes declarative filtering directly at the data control level difficult. At this time, we need to adopt a more flexible strategy to achieve the purpose of data filtering.

Strategy 1: Server-side preprocessing and filtering

The most ideal and efficient solution is to implement data filtering and sorting logic at the data source, that is, the Web service itself. This method transfers the computational burden of filtering from the client to the server. It is especially suitable for processing large amounts of data and can significantly improve the response speed and performance of client applications.

Implementation ideas

1. Modify an existing web service: If you have control of the web service, you can modify its interface so that it accepts filter parameters (for example, attribute names, filter values, sort fields, etc.). The web service queries and processes the data based on these parameters before returning the data.
2. Implement a new Web service: If the existing Web service cannot be modified, or the existing service is not suitable for handling filtering logic, you can consider implementing a new Web service. This new service can encapsulate the call to the original web service, filter, transform and sort the data in the middle layer, and then return the processed data to the JDeveloper application.

advantage

• Performance optimization: Reduces the amount of data transmitted over the network and reduces the computing load on the client.
• Data consistency: The filtering logic is concentrated on the server side, ensuring the consistency of data obtained by all clients.
• Scalability: Server-side filtering logic can be expanded and maintained more easily.

shortcoming

• Development costs: Web services need to be modified or developed, which may involve back-end development work.
• Dependencies: Client applications rely on the filtering capabilities provided by the Web service.

Strategy 2: Client POJO model filtering

When the Web service cannot be modified or more flexible client control is required, the raw data returned by the Web service can be obtained in the JDeveloper application, mapped to the POJO (Plain Old Java Object) model, and then programmatically filtered and sorted in the client code.

Implementation ideas

1. Get the raw data: First, you need to get the unfiltered raw data collection from the web service data control. This is usually done by calling methods provided by the data control or iterating through its data providers. For example, if the Web service returns a list of Java beans, you can get the list directly.

2. Define POJO model: Create a POJO class corresponding to the data structure returned by the Web service. This class should contain all properties that need to be displayed and filtered.

    // Example: Define a POJO that represents the data returned by the Web service
   public class MyServiceData {
       private String id;
       private String name;
       private String category;
       private double price;
   
       //Constructor public MyServiceData(String id, String name, String category, double price) {
           this.id = id;
           this.name = name;
           this.category = category;
           this.price = price;
       }
   
       // Getter and Setter methods public String getId() { return id; }
       public void setId(String id) { this.id = id; }
       public String getName() { return name; }
       public void setName(String name) { this.name = name; }
       public String getCategory() { return category; }
       public void setCategory(String category) { this.category = category; }
       public double getPrice() { return price; }
       public void setPrice(double price) { this.price = price; }
   
       @Override
       public String toString() {
           return "MyServiceData{"  
                  "id='" id '\''  
                  ", name='" name '\''  
                  ", category='" category '\''  
                  ", price=" price  
                  '}';
       }
   }

3. Implement filtering logic: Once the data is loaded into a POJO collection like List, you can use Java 8's Stream API or other collection operations to perform filtering.

    import java.util.ArrayList;
   import java.util.List;
   import java.util.stream.Collectors;
   
   public class DataFilterService {
   
       public static List<myservicedata> filterData(List<myservicedata> originalData, String filterCategory) {
           if (originalData == null || originalData.isEmpty()) {
               return new ArrayList();
           }
   
           // Use Java 8 Stream API for filtering List<myservicedata> filteredList = originalData.stream()
               .filter(data -&gt; data.getCategory() != null &amp;&amp; data.getCategory().equalsIgnoreCase(filterCategory))
               .collect(Collectors.toList());
   
           return filteredList;
       }
   
       public static void main(String[] args) {
           // Simulate the raw data obtained from the Web service List<myservicedata> rawData = new ArrayList();
           rawData.add(new MyServiceData("001", "Product A", "Electronics", 120.50));
           rawData.add(new MyServiceData("002", "Product B", "Books", 25.00));
           rawData.add(new MyServiceData("003", "Product C", "Electronics", 300.00));
           rawData.add(new MyServiceData("004", "Product D", "Home", 50.75));
           rawData.add(new MyServiceData("005", "Product E", "Electronics", 75.20));
   
           System.out.println("Original data:");
           rawData.forEach(System.out::println);
   
           // Filter data: only display products in the "Electronics" category String targetCategory = "Electronics";
           List<myservicedata> filteredResults = filterData(rawData, targetCategory);
   
           System.out.println("\nFiltered data (Category: " targetCategory "):");
           filteredResults.forEach(System.out::println);
   
           // Example: further sorting (descending by price)
           List<myservicedata> sortedFilteredResults = filteredResults.stream()
               .sorted((d1, d2) -&gt; Double.compare(d2.getPrice(), d1.getPrice())) // Descending order.collect(Collectors.toList());
   
           System.out.println("\nFiltered and sorted data (descending order by price):");
           sortedFilteredResults.forEach(System.out::println);
       }
   }</myservicedata></myservicedata></myservicedata></myservicedata></myservicedata></myservicedata>

advantage

• Client control: The filtering logic is completely implemented on the client and does not rely on Web service modifications.
• Flexibility: Complex, customized filtering and sorting rules can be implemented.
• Fast iteration: Filtering logic can be quickly tested and adjusted without affecting web services.

shortcoming

• Performance bottleneck: If the amount of data returned by the web service is very large, loading all the data into client memory and filtering it may cause performance degradation and excessive memory consumption.
• Network overhead: Even if only part of the data is needed, the entire raw data must be obtained from the web service.
• Code complexity: Additional Java code needs to be written to handle data mapping and filtering.

Things to note and best practices

• Data volume assessment: When choosing a filtering strategy, first evaluate the expected volume of data returned by the web service. For a small amount of data, client-side POJO filtering is feasible; for a large amount of data, server-side filtering is preferred.
• User experience: Client-side filtering may introduce delays in data loading and processing, affecting user experience. Consider providing loading instructions while the filtering operation is in progress.
• Code maintainability: Whatever strategy you adopt, make sure your filtering logic is clear, modular, and easy to maintain.
• Error handling: During the data acquisition and filtering process, possible exceptions should be properly handled, such as network errors, data format mismatch, etc.
• JDeveloper integration: In JDeveloper, binding a filtered POJO list to a UI component (such as an ADF Table) usually requires a custom method of an ADF Faces Managed Bean or Data Control.

Summarize

When JDeveloper's web service data control cannot be declaratively filtered through "naming guidelines", we have two main high-level strategies: server-side preprocessing filtering and client-side POJO model filtering . Server-side filtering is the first choice for processing large amounts of data and pursuing high performance, but it requires the support of the Web server; client-side POJO filtering provides a high degree of flexibility and control, and is suitable for scenarios where the amount of data is small or the Web service cannot be modified. Developers should weigh the pros and cons of both strategies and choose the most appropriate solution based on specific project needs, data size, and development resources.

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