Understanding the package

I’m thinking through how to use the co.elastic.clients.elasticsearch Java client to work with the provided JSON query.

Crafting the query

I’ll show step-by-step how to use the Elasticsearch Java client for constructing and running the query, converting the JSON request into client code, and addressing nested and function_score queries.

Setting up the client

I’m setting up the Elasticsearch Java client, using the co.elastic.clients.elasticsearch package. I’ll show how to execute a search query with a complex JSON query directly via Java API’s JSON parsing capabilities.

Mapping Java objects

I’m considering how to use ElasticsearchClient to run a query. Parsing JSON into a Map or using low-level client tools for mapped JSON might streamline things.

Taking a closer look

I’m evaluating the Java client and the RestHighLevelClient for executing a function_score query. Considering the co.elastic.clients.elasticsearch package for the new Java client and aiming to build and execute the query.

Showcasing query construction

I'm taking a closer look at building the query using the co.elastic.clients.elasticsearch client, mindful of time constraints. Let's explore the JSON library parsing option for a quick demonstration.

Laying out the query

I’m piecing together an ElasticsearchClient instance and crafting a function_score query using a bool query with a should clause and a nested query. This query needs function score functions with filters.

Navigating Elasticsearch

I’m piecing together a search query in Elasticsearch, focusing on function scoring for nested paths and specific tag conditions. It’s interesting to see how this deep dive enhances understanding.

Evaluating methods

I’m thinking through various ways to send a JSON query using the co.elastic.clients.elasticsearch package, including constructing the query with the package or parsing it into a Map for direct use.

Weighing options

I'm evaluating using the low-level client for the JSON query or demonstrating both approaches. Considering the verbosity of builder classes and the lack of direct support for raw JSON strings in SearchRequest, wrapping the JSON query in JsonData appears to be a viable workaround.

Initializing Elasticsearch

First, I set up the low-level Elasticsearch client by creating the necessary components: RestClientBuilder, RestClient, RestClientTransport, and ElasticsearchClient.

Streamlining JSON queries
I’m detailing a method to send raw JSON queries using the low-level Elasticsearch client, bypassing the builder classes for a more direct approach.

Breaking down the process

I’m walking through setting up the REST client, crafting the JSON query, and sending it. This method eliminates the need for builder classes, simplifying the submission process.

Constructing a complex query

I’m piecing together an Elasticsearch query using the Java API client. It’s fun to see how function scores and nested queries create a nuanced search experience, boosting relevance based on different criteria.

To help you execute your provided Elasticsearch query using the co.elastic.clients.elasticsearch package, I'll guide you through two approaches:

1. Using the Java High-Level REST Client (Elasticsearch Java API Client) to build the query step by step.
2. Sending the raw JSON query directly using the Low-Level REST Client.

---

Approach 1: Building the Query Using the Java High-Level REST Client

The co.elastic.clients.elasticsearch package corresponds to the Elasticsearch Java API Client. While it offers type safety and builder patterns, complex queries can become verbose. Below is how you can build your query:

Setup the Elasticsearch Client

java
import co.elastic.clients.elasticsearch.ElasticsearchClient;
import co.elastic.clients.transport.rest_client.RestClientTransport;
import co.elastic.clients.json.jackson.JacksonJsonpMapper;
import org.apache.http.HttpHost;
import org.elasticsearch.client.RestClient;

// Create the low-level client
RestClient restClient = RestClient.builder(new HttpHost("localhost", 9200)).build();

// Create the transport with a Jackson mapper
RestClientTransport transport = new RestClientTransport(restClient, new JacksonJsonpMapper());

// And create the API client
ElasticsearchClient client = new ElasticsearchClient(transport);

Building and Executing the Query

java
import co.elastic.clients.elasticsearch.core.SearchResponse;
import co.elastic.clients.elasticsearch._types.query_dsl.*;
import co.elastic.clients.elasticsearch._types.FunctionScoreMode;
import co.elastic.clients.elasticsearch._types.FunctionBoostMode;

SearchResponse<Object> response = client.search(s -> s
    .index("data")
    .query(q -> q.functionScore(fs -> fs
        .query(innerQuery -> innerQuery.bool(b -> b
            .should(sq -> sq.nested(n -> n
                .path("tags")
                .query(nq -> nq.terms(tq -> tq
                    .field("tags.tags")
                    .terms(tvs -> tvs
                        .value("空战")
                        .value("后勤保障")
                        .value("导弹平台与动力技术")
                        .value("陆基平台与动力技术")
                        .value("基础科学")
                        .value("太空")
                    )
                ))
            ))
        ))
        .functions(flist -> flist
            .function(f -> f
                .filter(fq -> fq.nested(nf -> nf
                    .path("tags")
                    .query(nq -> nq.terms(tq -> tq
                        .field("tags.tags")
                        .terms(tvs -> tvs.value("空战"))
                    ))
                ))
                .weight(1.0)
            )
            .function(f -> f
                .filter(fq -> fq.nested(nf -> nf
                    .path("tags")
                    .query(nq -> nq.terms(tq -> tq
                        .field("tags.tags")
                        .terms(tvs -> tvs.value("太空"))
                    ))
                ))
                .weight(1.0)
            )
            // Repeat for other tags...
        )
        .scoreMode(FunctionScoreMode.Sum)
        .boostMode(FunctionBoostMode.Sum)
    )), Object.class);

Note: You'll need to repeat the .function(...) block for each tag in your functions array.

Explanation

• Nested Queries: We use .nested() to handle nested fields like tags.
• Terms Query: We build the terms queries using .terms() and provide the list of tags.
• Function Score Query: We construct the function score query with .functionScore() and specify functions, scoreMode, and boostMode.
• Executing the Search: The client.search() method executes the query, and we capture the response.

---

Approach 2: Sending the Raw JSON Query Using the Low-Level REST Client

If you prefer to use your JSON query directly, you can use the Low-Level REST Client to send the raw JSON string.

Setup the Low-Level REST Client

java
import org.elasticsearch.client.RestClient;
import org.apache.http.HttpHost;

RestClient restClient = RestClient.builder(new HttpHost("localhost", 9200)).build();

Sending the Raw JSON Query

java
import org.elasticsearch.client.Request;
import org.elasticsearch.client.Response;

String jsonString = "{\n" +
"  \"query\": {\n" +
"    \"function_score\": {\n" +
"      \"query\": {\n" +
"        \"bool\": {\n" +
"          \"should\": [\n" +
"            {\n" +
"              \"nested\": {\n" +
"                \"path\": \"tags\",\n" +
"                \"query\": {\n" +
"                  \"terms\": {\n" +
"                    \"tags.tags\": [\"空战\", \"后勤保障\", \"导弹平台与动力技术\", \"陆基平台与动力技术\", \"基础科学\",\"太空\"]\n" +
"                  }\n" +
"                }\n" +
"              }\n" +
"            }\n" +
"          ]\n" +
"        }\n" +
"      },\n" +
"      \"functions\": [\n" +
"        {\n" +
"          \"filter\": {\n" +
"            \"nested\": {\n" +
"              \"path\": \"tags\",\n" +
"              \"query\": {\n" +
"                \"terms\": {\n" +
"                  \"tags.tags\": [\"空战\"]\n" +
"                }\n" +
"              }\n" +
"            }\n" +
"          },\n" +
"          \"weight\": 1\n" +
"        },\n" +
"        // Include other functions here...\n" +
"      ],\n" +
"      \"score_mode\": \"sum\",\n" +
"      \"boost_mode\": \"sum\"\n" +
"    }\n" +
"  }\n" +
"}";

Request request = new Request("POST", "/data/_search");
request.setJsonEntity(jsonString);

Response response = restClient.performRequest(request);

Explanation

• Request Creation: We create a new Request object specifying the HTTP method and endpoint.
• Setting the JSON Entity: We use setJsonEntity() to include your raw JSON query.
• Executing the Request: restClient.performRequest(request) sends the request to Elasticsearch.

---

Recommendation

Given the complexity of your query, Approach 2 might be more straightforward, as it allows you to use your JSON query directly without translating it into Java objects.

---

Additional Tips

• Error Handling: Ensure you include appropriate error handling (try-catch blocks) to handle potential exceptions.

• Closing Resources: Remember to close the RestClient instance after use to free up resources.

  java
  restClient.close();

• Dependencies: Make sure you have the necessary Elasticsearch client libraries in your project's dependencies (e.g., Maven, Gradle).

---

Let me know if you need further assistance or clarification on any of the steps!

Integrating JSON query

I’m noting the user's goal to integrate raw JSON queries into the topkSearch method of DdiDataService class, which currently uses the high-level client and builder pattern.

Integrating low-level client

I’m pulling together a plan to combine the topkSearch method with a low-level REST client for raw JSON queries. This involves integrating and adapting for seamless execution.

Examining DdiDataService

I’m tackling the role of the DdiDataService class and its topkSearch method. This method is designed to pinpoint data according to user profiles.

Crafting the search

I’m piecing together a search method by gathering profiles, domains, sources, and keywords. Constructing various queries based on user needs.

Adapting the method

I’m thinking through how to incorporate a low-level REST client into the topkSearch method, using a raw JSON query instead of SearchUtils.query.

Integrating JSON query

I’m refining the code to include a raw JSON query in the topkSearch method. This involves replacing the existing query-building code with the low-level client.

Revisiting the approach

I’m mapping out how to revise the recommendToday method to utilize the low-level client, ensuring the raw JSON query is sent and correctly mapped into the DataIndex class.

Constructing JSON query

I’m piecing together a JSON query in the recommendToday method, sending it via the low-level REST client, and parsing the results into SearchPage<DataIndex>.

Assessing client options

I’m considering how to adapt the DdiDataService class to use the low-level RestClient. Options include leveraging Spring Data Elasticsearch or transitioning to the new Java API client.

Refining RestClient integration

I'm considering how to configure the RestClient within the recommendToday method. Options include injecting it or initializing it in the constructor, considering Spring Boot dependencies and deprecated APIs.

Integrating RestClient

I'm considering modifying the DdiDataService class to include a RestClient field, initializing it in the constructor, and using it to send and parse requests.

Evaluating integration methods

I'm considering the complexity of integrating a low-level client. Using the high-level client to send a raw JSON query, specifically through the SearchRequest class in the new Java API client, seems practical.

Exploring JSON query methods

I’m working through various methods for setting raw JSON queries in Elasticsearch, like the Builder and low-level client, to ensure seamless integration in the recommendToday method.

Integrating RestClient

I’m gathering info on setting up RestClient in the DdiDataService class. It’s being initialized in the constructor using localhost for its host and port.

Updating the method

I’m updating the recommendToday method by constructing a JSON query, sending a search request, handling exceptions, and parsing the response using ObjectMapper to create and return a SearchPage<DataIndex> object.

Evaluating options

I'm weighing the choice between the low-level REST client and the high-level Java API client for sending a raw JSON query. The high-level client offers JsonData for JSON strings, while the low-level client remains an option.

Mapping complexity

OK, let me see. Given the intricate nature of aligning the response to SearchPage<DataIndex>, I'm suggesting utilizing the low-level client to transmit the raw JSON query, parse it into DataIndex objects, and form a SearchPage<DataIndex>.

Building the query

I’m thinking through the construction of a JSON query for a search method, focusing on pagination and JSON object parsing. The code defines classes to map the response, ensuring data accuracy.

Assessing options

To ensure the JSON structure aligns, I explore Elasticsearch Java API client methods like withJson() and SearchTemplateRequest. Using the high-level client simplifies response parsing.

Utilizing raw JSON queries

I’m working through using ElasticsearchClient to send raw JSON queries. This approach skips the builder pattern, making code simpler and more concise.

Integrating Elasticsearch

I’m working through adding the ElasticsearchClient to the DdiDataService class and updating the constructor to include this new dependency. This involves initializing the client and utilizing it in the recommendToday method for executing raw JSON queries.

Refining the elasticsearch query

I’m crafting a JSON query for elasticsearch, focusing on a nested structure with tags and specific filters. This is part of a method to recommend data based on these criteria.

Piecing together alternatives

I’m piecing together various options for constructing an Elasticsearch query response, including using the search method, SearchTemplate API, transmitting raw JSON, and leveraging ElasticsearchClient's transport for the low-level client.

Setting up the RestClient

I’m adding the RestClient field to the DdiDataService class, initializing it in the constructor, and preparing to integrate raw JSON query handling and response parsing in the recommendToday method.

Crafting the JSON

I’m constructing a JSON query for Elasticsearch, aiming to filter and score the results based on specific tags. This involves adjusting query parameters and implementing functions for precise data handling.

Certainly! Let's integrate Approach 2 into your topkSearch method in the DdiDataService class. We'll modify the recommendToday method to use the Low-Level REST Client to send the raw JSON query and parse the response into a SearchPage<DataIndex> object.

---

Step-by-Step Integration

1. Add the Low-Level REST Client to Your Service

   First, we'll need to add an instance of the Low-Level REST Client to your DdiDataService class.

   java
   import org.elasticsearch.client.RestClient;
   import org.apache.http.HttpHost;
   
   // Inside your DdiDataService class
   private final RestClient restClient;
   
   public DdiDataService(DataRepository dataRepository, ElasticsearchOperations elasticsearchOperations,
                         DataSelectRepository dataSelectRepository, DomainService domainService) {
       this.dataRepository = dataRepository;
       this.elasticsearchOperations = elasticsearchOperations;
       this.dataSelectRepository = dataSelectRepository;
       this.domainService = domainService;
       
       // Initialize the low-level REST client
       this.restClient = RestClient.builder(new HttpHost("localhost", 9200)).build();
   }

   Note: Adjust the HttpHost parameters according to your Elasticsearch cluster's configuration.

2. Modify the recommendToday Method

   We'll replace the existing code in recommendToday to use the Low-Level REST Client and send the raw JSON query.

   java
   import org.elasticsearch.client.Request;
   import org.elasticsearch.client.Response;
   import org.elasticsearch.client.ResponseException;
   import org.elasticsearch.client.RestClient;
   import org.apache.http.util.EntityUtils;
   import com.fasterxml.jackson.databind.ObjectMapper;
   import org.springframework.data.domain.PageImpl;
   import org.springframework.data.elasticsearch.core.SearchHitSupport;
   
   private SearchPage<DataIndex> recommendToday(List<Query> should, Pageable pageable, boolean timeFilter) {
       // Build the raw JSON query as a String
       String jsonString = "{\n" +
               "  \"query\": {\n" +
               "    \"function_score\": {\n" +
               "      \"query\": {\n" +
               "        \"bool\": {\n" +
               "          \"should\": [\n" +
               "            {\n" +
               "              \"nested\": {\n" +
               "                \"path\": \"tags\",\n" +
               "                \"query\": {\n" +
               "                  \"terms\": {\n" +
               "                    \"tags.tags\": [\"空战\", \"后勤保障\", \"导弹平台与动力技术\", \"陆基平台与动力技术\", \"基础科学\",\"太空\"]\n" +
               "                  }\n" +
               "                }\n" +
               "              }\n" +
               "            }\n" +
               "          ]\n" +
               "        }\n" +
               "      },\n" +
               "      \"functions\": [\n" +
               "        {\n" +
               "          \"filter\": {\n" +
               "            \"nested\": {\n" +
               "              \"path\": \"tags\",\n" +
               "              \"query\": {\n" +
               "                \"terms\": {\n" +
               "                  \"tags.tags\": [\"空战\"]\n" +
               "                }\n" +
               "              }\n" +
               "            }\n" +
               "          },\n" +
               "          \"weight\": 1\n" +
               "        },\n" +
               "        {\n" +
               "          \"filter\": {\n" +
               "            \"nested\": {\n" +
               "              \"path\": \"tags\",\n" +
               "              \"query\": {\n" +
               "                \"terms\": {\n" +
               "                  \"tags.tags\": [\"太空\"]\n" +
               "                }\n" +
               "              }\n" +
               "            }\n" +
               "          },\n" +
               "          \"weight\": 1\n" +
               "        },\n" +
               "        // Include other functions here...\n" +
               "      ],\n" +
               "      \"score_mode\": \"sum\",\n" +
               "      \"boost_mode\": \"sum\"\n" +
               "    }\n" +
               "  }\n" +
               "}";
   
       // Create the Request
       Request request = new Request("POST", "/data/_search");
   
       // Set query parameters for pagination
       request.addParameter("from", String.valueOf(pageable.getOffset()));
       request.addParameter("size", String.valueOf(pageable.getPageSize()));
   
       // Set the raw JSON query
       request.setJsonEntity(jsonString);
   
       // Send the request and parse the response
       try {
           Response response = restClient.performRequest(request);
           String responseBody = EntityUtils.toString(response.getEntity());
   
           // Parse the response using ObjectMapper
           ObjectMapper objectMapper = new ObjectMapper();
           SearchResponseData searchResponseData = objectMapper.readValue(responseBody, SearchResponseData.class);
   
           // Extract hits and total
           List<DataIndex> content = searchResponseData.getHits().getHits().stream()
                   .map(HitData::getSource)
                   .collect(Collectors.toList());
   
           long totalHits = searchResponseData.getHits().getTotal().getValue();
   
           // Create Page and SearchPage
           Page<DataIndex> page = new PageImpl<>(content, pageable, totalHits);
           SearchPage<DataIndex> searchPage = SearchHitSupport.searchPageFor(page, pageable);
   
           return searchPage;
   
       } catch (ResponseException e) {
           // Handle Elasticsearch errors
           throw new RuntimeException("Elasticsearch error: " + e.getMessage(), e);
       } catch (IOException e) {
           // Handle I/O errors
           throw new RuntimeException("I/O error: " + e.getMessage(), e);
       }
   }

   Explanation:

   • Request Creation: We create a new Request object specifying the HTTP method and endpoint.
   • Pagination Parameters: We set the from and size parameters for pagination.
   • Setting the JSON Entity: We use setJsonEntity() to include your raw JSON query.
   • Executing the Request: restClient.performRequest(request) sends the request to Elasticsearch.
   • Parsing the Response: We use ObjectMapper to parse the JSON response into Java objects.
   • Creating SearchPage<DataIndex>: We convert the parsed data into a SearchPage<DataIndex> object.

3. Define Classes for Parsing the Response

   We need classes that match the structure of the Elasticsearch response to parse it correctly.

   java
   import com.fasterxml.jackson.annotation.JsonProperty;
   
   // Root class for the search response
   public static class SearchResponseData {
       private HitsData hits;
   
       public HitsData getHits() {
           return hits;
       }
   
       public void setHits(HitsData hits) {
           this.hits = hits;
       }
   }
   
   // Class representing the "hits" section
   public static class HitsData {
       private Total total;
       private List<HitData> hits;
   
       public Total getTotal() {
           return total;
       }
   
       public void setTotal(Total total) {
           this.total = total;
       }
   
       public List<HitData> getHits() {
           return hits;
       }
   
       public void setHits(List<HitData> hits) {
           this.hits = hits;
       }
   }
   
   // Class representing the "total" section
   public static class Total {
       private long value;
   
       public long getValue() {
           return value;
       }
   
       public void setValue(long value) {
           this.value = value;
       }
   }
   
   // Class representing each hit
   public static class HitData {
       @JsonProperty("_index")
       private String index;
   
       @JsonProperty("_type")
       private String type;
   
       @JsonProperty("_id")
       private String id;
   
       @JsonProperty("_score")
       private float score;
   
       @JsonProperty("_source")
       private DataIndex source;
   
       public String getIndex() {
           return index;
       }
   
       public void setIndex(String index) {
           this.index = index;
       }
   
       public String getType() {
           return type;
       }
   
       public void setType(String type) {
           this.type = type;
       }
   
       public String getId() {
           return id;
       }
   
       public void setId(String id) {
           this.id = id;
       }
   
       public float getScore() {
           return score;
       }
   
       public void setScore(float score) {
           this.score = score;
       }
   
       public DataIndex getSource() {
           return source;
       }
   
       public void setSource(DataIndex source) {
           this.source = source;
       }
   }

   Explanation:

   • SearchResponseData: Represents the root of the Elasticsearch response.
   • HitsData: Represents the hits section containing the total hits and the list of individual hits.
   • Total: Represents the total number of hits.
   • HitData: Represents each individual hit, including the _source field, which we'll map to DataIndex.

4. Ensure DataIndex is Serializable

   Make sure your DataIndex class is properly annotated and serializable so that ObjectMapper can map the JSON _source to DataIndex.

   java
   import com.fasterxml.jackson.annotation.JsonIgnoreProperties;
   import com.fasterxml.jackson.annotation.JsonProperty;
   
   @JsonIgnoreProperties(ignoreUnknown = true)
   public class DataIndex {
       // Your fields and methods here
   }

5. Handle Exception and Resource Cleanup

   Remember to handle exceptions and close the RestClient when it's no longer needed.

   java
   // At the end of your service class
   public void close() throws IOException {
       restClient.close();
   }

---

Final Code for recommendToday Method

Here's the complete recommendToday method with the integrated low-level REST client and raw JSON query.

java
private SearchPage<DataIndex> recommendToday(List<Query> should, Pageable pageable, boolean timeFilter) {
    // Build the raw JSON query as a String
    String jsonString = "{\n" +
            "  \"query\": {\n" +
            "    \"function_score\": {\n" +
            "      \"query\": {\n" +
            "        \"bool\": {\n" +
            "          \"should\": [\n" +
            "            {\n" +
            "              \"nested\": {\n" +
            "                \"path\": \"tags\",\n" +
            "                \"query\": {\n" +
            "                  \"terms\": {\n" +
            "                    \"tags.tags\": [\"空战\", \"后勤保障\", \"导弹平台与动力技术\", \"陆基平台与动力技术\", \"基础科学\",\"太空\"]\n" +
            "                  }\n" +
            "                }\n" +
            "              }\n" +
            "            }\n" +
            "          ]\n" +
            "        }\n" +
            "      },\n" +
            "      \"functions\": [\n" +
            "        {\n" +
            "          \"filter\": {\n" +
            "            \"nested\": {\n" +
            "              \"path\": \"tags\",\n" +
            "              \"query\": {\n" +
            "                \"terms\": {\n" +
            "                  \"tags.tags\": [\"空战\"]\n" +
            "                }\n" +
            "              }\n" +
            "            }\n" +
            "          },\n" +
            "          \"weight\": 1\n" +
            "        },\n" +
            "        {\n" +
            "          \"filter\": {\n" +
            "            \"nested\": {\n" +
            "              \"path\": \"tags\",\n" +
            "              \"query\": {\n" +
            "                \"terms\": {\n" +
            "                  \"tags.tags\": [\"太空\"]\n" +
            "                }\n" +
            "              }\n" +
            "            }\n" +
            "          },\n" +
            "          \"weight\": 1\n" +
            "        },\n" +
            "        // Include other functions here...\n" +
            "      ],\n" +
            "      \"score_mode\": \"sum\",\n" +
            "      \"boost_mode\": \"sum\"\n" +
            "    }\n" +
            "  }\n" +
            "}";

    // Create the Request
    Request request = new Request("POST", "/data/_search");

    // Set query parameters for pagination
    request.addParameter("from", String.valueOf(pageable.getOffset()));
    request.addParameter("size", String.valueOf(pageable.getPageSize()));

    // Set the raw JSON query
    request.setJsonEntity(jsonString);

    // Send the request and parse the response
    try {
        Response response = restClient.performRequest(request);
        String responseBody = EntityUtils.toString(response.getEntity());

        // Parse the response using ObjectMapper
        ObjectMapper objectMapper = new ObjectMapper();
        SearchResponseData searchResponseData = objectMapper.readValue(responseBody, SearchResponseData.class);

        // Extract hits and total
        List<DataIndex> content = searchResponseData.getHits().getHits().stream()
                .map(HitData::getSource)
                .collect(Collectors.toList());

        long totalHits = searchResponseData.getHits().getTotal().getValue();

        // Create Page and SearchPage
        Page<DataIndex> page = new PageImpl<>(content, pageable, totalHits);
        SearchPage<DataIndex> searchPage = SearchHitSupport.searchPageFor(page, pageable);

        return searchPage;

    } catch (ResponseException e) {
        // Handle Elasticsearch errors
        throw new RuntimeException("Elasticsearch error: " + e.getMessage(), e);
    } catch (IOException e) {
        // Handle I/O errors
        throw new RuntimeException("I/O error: " + e.getMessage(), e);
    }
}

---

Additional Considerations

• Dynamic Query Generation:

  If you need to dynamically generate the JSON query based on user inputs or filters, you can construct the JSON string programmatically.

  java
  // Example of building a JSON query string dynamically
  StringBuilder jsonQueryBuilder = new StringBuilder();
  jsonQueryBuilder.append("{ \"query\": { \"bool\": { \"must\": [");
  
  // Add dynamic conditions
  for (String filter : filters) {
      jsonQueryBuilder.append("{ \"term\": { \"field\": \"").append(filter).append("\" } },");
  }
  
  // Remove the last comma
  if (!filters.isEmpty()) {
      jsonQueryBuilder.setLength(jsonQueryBuilder.length() - 1);
  }
  
  jsonQueryBuilder.append("] } } }");
  String jsonString = jsonQueryBuilder.toString();

• Error Handling and Logging:

  Ensure that you have proper error handling and logging in place to catch and debug any issues that might arise during the request execution or response parsing.

• Performance Considerations:

  • Connection Management: Reuse the RestClient instance instead of creating a new one for each request.
  • Resource Cleanup: Make sure to close the RestClient when your application shuts down to release resources.

• Security Considerations:

  If your Elasticsearch cluster requires authentication, configure the RestClient with the necessary credentials.

  java
  RestClient restClient = RestClient.builder(new HttpHost("localhost", 9200))
          .setDefaultCredentialsProvider(credentialsProvider)
          .build();

• Asynchronous Execution:

  If you need non-blocking calls, the Low-Level REST Client supports asynchronous request execution.

  java
  restClient.performRequestAsync(request, new ResponseListener() {
      @Override
      public void onSuccess(Response response) {
          // Handle successful response
      }
  
      @Override
      public void onFailure(Exception exception) {
          // Handle failure
      }
  });

---

Summary

By integrating the Low-Level REST Client and sending your raw JSON query directly in the recommendToday method, we've effectively combined Approach 2 into your topkSearch functionality. This allows you to use your complex JSON queries without the verbosity of building them using the Java High-Level REST Client's builder pattern.

---

Let me know if you have any questions or need further assistance with this integration!