ElasticSearch

ElasticSearch Create, Query, Delete Index – Java Example

ElasticSearch Java APIs can be used to create, update, query (retrieve items) and delete the index. In this post, you will learn about using Java APIs for performing CRUD operations in relation with managing indices and querying items in ElasticSearch.

  • Create an empty index with data type mapping
  • Create/update the index using BulkRequest APIs
  • Search Index using QueryBuilder and SearchRequestBuilder APIs
  • Delete the index

Create an Empty Index with Data-type Mapping

public class App {
    public static void main(String[] args) {
        String indexName = "recruitment";
        String indexType = "companies";
        //
        // Create an instance of Transport Client
        //
        TransportClient client = new PreBuiltTransportClient(Settings.EMPTY)
                .addTransportAddress(new TransportAddress(InetAddress.getByName("127.0.0.1"), "9300"));
        //
        // Create the JSON mapping
        //
        String jsonMapping = "{\n" +
                          "  \"properties\": {\n" +
                          "       \"created_on\":  { \"type\": \"date\", \"format\": \"dd-MM-YYYY\" },\n" +
                          "       \"name\": { \"type\": \"text\" },\n" +
                          "       \"emp_count\": { \"type\": \"integer\" }\n" +
                          "    }\n" +
                          " }";
        //
        // Create an empty index
        //
        client.admin().indices().prepareCreate(indexName).get();
        //
        // Put the mapping
        //
        PutMappingRequest pmr = Requests.putMappingRequest(indexName).type(indexType).source(jsonMapping, XContentType.JSON);
        client.admin().indices().putMapping(pmr).actionGet();
        //
        // Close the client
        //
        client.close();
    }
}

Create/Update the Index using BulkRequest APIs

Pay attention to some of the following:

  • Create an instance of TransportClient
  • Prepare bulk request for inserting multiple entries in index
public class App {
    public static void main(String[] args) {
        String[] data = {{"vitalflux.com", "15", "15-10-2011"},{"amazon.com", "112110", "10-08-2001"},{"facebook.com", "45123", "16-03-2006"}};
        String indexName = "recruitment";
        String indexType = "companies";
        Map<;String, Object>; source = new HashMap<;String, Object>;();
        //
        // Create an instance of Transport Client
        //
        TransportClient client = new PreBuiltTransportClient(Settings.EMPTY)
                .addTransportAddress(new TransportAddress(InetAddress.getByName("127.0.0.1"), "9300"));
        //
        // Prepare Bulk Request
        //
        BulkRequestBuilder bulkRequest = client.prepareBulk();
        for (String[] entry : data) {
            source.put("name", entry[0]);
            source.put("emp_count", entry[1]);
            source.put("created_on", entry[2]);
            bulkRequest.add(client.prepareIndex(indexName, indexType).setSource(source));
        }
        //
        // Invoke the API for creating the index
        //
        BulkResponse bulkResponse = bulkRequest.get();
        //
        // Close the client
        //
        client.close();
    }
}

Delete the Index

Pay attention to some of the following:

  • Create an instance of TransportClient
  • Create an instance of DeleteIndexRequest for deleting an index
public class App {
    public static void main(String[] args) {
        String indexName = "recruitment";
        //
        // Create an instance of TransportClient
        //
        TransportClient client = new PreBuiltTransportClient(Settings.EMPTY)
                .addTransportAddress(new TransportAddress(InetAddress.getByName("127.0.0.1"), "9300"));
        //
        // Delete the index with name as indexName
        //
        DeleteIndexRequest request = new DeleteIndexRequest(indexName);
        DeleteIndexResponse deleteIndexResponse = this.client.admin().indices().delete(request).actionGet();
    }
}

Search Index using QueryBuilder and SearchRequestBuilder APIs

Pay attention to some of the following:

  • Create an instance of TransportClient
  • Create one or more instances of QueryBuilder using APIs such as matchQuery, rangeQuery
  • Create an instance of SearchRequestBuilder for building the search request
  • Invoke the Get API to get the search results
  • Iterate through the search result
public class App {
    public static void main(String[] args) {
        String indexName = "recruitment";
        String indexType = "companies";
        //
        // Create an instance of TransportClient
        //
        TransportClient client = new PreBuiltTransportClient(Settings.EMPTY)
                .addTransportAddress(new TransportAddress(InetAddress.getByName("127.0.0.1"), "9300"));
        //
        // Create instances of QueryBuilders
        //
        QueryBuilder nameQueryBuilder = QueryBuilders.matchQuery("name", "faceboak").fuzziness(Fuzziness.ONE).boost(1.0f).prefixLength(0).fuzzyTranspositions(true);
        QueryBuilder countQueryBuilder = QueryBuilders.rangeQuery("emp_count").from(10000).to(50000);
        QueryBuilder dateQueryBuilder = QueryBuilders.rangeQuery("created_on").format("yyyy-MM-dd").from("2006-01-01");
        //
        // Create an instance of SearchRequestBuilder; Below represents the single query builder
        //
        SearchRequestBuilder requestBuilderWithSingleQueryBuilder = client.prepareSearch(indexName).setTypes(indexType).setQuery(queryBuilder).setSize(100);
        //
        // Create Bool Query Builder with different queries
        //
        QueryBuilder boolQueryBuilder = QueryBuilders.boolQuery().must(nameQueryBuilder).must(countQueryBuilder).must(dateQueryBuilder);
        SearchRequestBuilder requestBuilderWithBoolQuery = client.prepareSearch(INDEX_NAME).setTypes(INDEX_TYPE).setQuery(boolQueryBuilder).setSize(1000);
        //
        // Get the search result
        //
        SearchResponse response1 = requestBuilderWithSingleQueryBuilder.get();
        SearchResponse response2 = requestBuilderWithBoolQuery.get();
        //
        // Iterate through search results
        //
        SearchHit[] srchHits = response.getHits().getHits();
        Object[] result = new Object[srchHits.length];
        int i = 0;
        for (SearchHit srchHit : srchHits) {
            result[i++] = srchHit.getSourceAsMap();
        }
        //
        // Print the results
        //
        System.out.println("Results Count: " + result.length);
        for (Object detail : result) {
            Map<;String, Object>; map = (Map<;String, Object>;) detail;
            System.out.println("Name: " + map.get("name") + ", Date: " + map.get("created_on") + ", Employee Count: " + map.get("emp_count"));
        }
    }
}

Further Reading / References

You may also some of the following pages in relation to ElasticSearch on our website:

Summary

In this post, you learned about using CRUD operations on indices with ElasticSearch Java APIs.

Did you find this article useful? Do you have any questions or suggestions about this article in relation to working with Elasticsearch Java APIs for doing CRUD operations on indices? Leave a comment and ask your questions and I shall do my best to address your queries.

Ajitesh Kumar

I have been recently working in the area of Data analytics including Data Science and Machine Learning / Deep Learning. I am also passionate about different technologies including programming languages such as Java/JEE, Javascript, Python, R, Julia, etc, and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data, etc. I would love to connect with you on Linkedin. Check out my latest book titled as First Principles Thinking: Building winning products using first principles thinking.

Recent Posts

Agentic Reasoning Design Patterns in AI: Examples

In recent years, artificial intelligence (AI) has evolved to include more sophisticated and capable agents,…

2 months ago

LLMs for Adaptive Learning & Personalized Education

Adaptive learning helps in tailoring learning experiences to fit the unique needs of each student.…

2 months ago

Sparse Mixture of Experts (MoE) Models: Examples

With the increasing demand for more powerful machine learning (ML) systems that can handle diverse…

3 months ago

Anxiety Disorder Detection & Machine Learning Techniques

Anxiety is a common mental health condition that affects millions of people around the world.…

3 months ago

Confounder Features & Machine Learning Models: Examples

In machine learning, confounder features or variables can significantly affect the accuracy and validity of…

3 months ago

Credit Card Fraud Detection & Machine Learning

Last updated: 26 Sept, 2024 Credit card fraud detection is a major concern for credit…

3 months ago