Before search, a query must be built, Elasticsearch provides several ways to build these queries. In this recipe, will see how to create a query object via QueryBuilder and via simple strings.
You need an up-and-running Elasticsearch installation as we described in the Downloading and installing Elasticsearch recipe in Chapter 2, Downloading and Setup.
A Maven tool, or an IDE that natively supports it for Java programming such as Eclipse or IntelliJ IDEA, must be installed.
The code for this recipe is in the chapter_14/nativeclient directory and the referred class is QueryCreation.
To create a query, we will perform the following steps:
- We need to import the
QueryBuilders:import org.elasticsearch.index.query.BoolQueryBuilder; import org.elasticsearch.index.query.RangeQueryBuilder; import org.elasticsearch.index.query.TermQueryBuilder; - We'll create a query using
QueryBuilder:TermQueryBuilder filter = termQuery("number2", 1); RangeQueryBuilder range = rangeQuery("number1").gt(500); BoolQueryBuilder query = boolQuery().must(range).filter(filter) - Now we can execute a search (the searching via native API will be discussed in the next recipes):
SearchResponse response = client.prepareSearch(index).setTypes(type).setQuery(query) .execute().actionGet(); System.out.println("Matched records of elements: " + response.getHits().getTotalHits()); - I've removed the redundant parts that are similar to the example of the previous recipe. The result will be as follows:
Matched records of elements: 250
There are several ways to define a query in Elasticsearch; they are interchangeable.
Generally, a query can be defined as a:
QueryBuilder: A helper to build a query.XContentBuilder: A helper to create JSON code. We discussed this in the Managing mapping recipe in this chapter. The JSON code to be generated is similar to the previous REST, but converted in programmatic code.Array of BytesorString: In this case, it's usually the JSON to be executed as we have seen in REST calls.Map, which contains the query and the value of the query.
In the previous example, we created a query via QueryBuilders. The first step is to import the QueryBuilder from the namespace:
import static org.elasticsearch.index.query.QueryBuilders.*;
The query of the example is a Boolean query with a termQuery as filter. The goal of the example is to show how to mix several query types to create a complex query.
We need to define a filter.
In this case we have used a term query, which is one of the most used:
TermQueryBuilder filter = termQuery("number2", 1);
The termQuery accepts a field and a value, which must be a valid Elasticsearch type.
The previous code is similar to the JSON REST {"term": {"number2":1}.
The Boolean query contains a must clause with a range query. We start to create the range query:
RangeQueryBuilder range = rangeQuery("number1").gte(500);
This range query matches, in the number1 field, all the values that are greater than or equal to (gte) 500.
After creating the range query, we can add it to a Boolean query in the must block and the filter query in the filter block:
BoolQueryBuilder bool = boolQuery().must(range).filter(filter);
In real-world complex queries, you can have a lot of nested queries in a Boolean query or filter.
In the example it's done with the following code:
client.admin().indices().prepareRefresh(index).execute().actionGet();
The possible native queries/filters are the same as REST ones and have the same parameters: the only difference is that they are accessible via builder methods.
The most common query builders are:
matchAllQuery: This allows matching all the documents to be matchedmatchQuery,matchPhraseQuery: These are used to match against text stringstermQuery,termsQuery: These are used to match a term value(s) against a specific fieldboolQuery: This is used to aggregate other queries with Boolean logicidsQuery: This is used to match a list of IDsfieldQuery: This is used to match a field with textwildcardQuery: This is used to match terms with wildcards (*?.)regexpQuery: This is used to match terms via a regular expression- Span query family (
spanTermsQuery,spanTermQuery,spanORQuery,spanNotQuery,spanFirstQuery, and so on): These are a few examples of the span query family, which are used in building span queries hasChildQuery,hasParentQuery,nestedQuery: These are used to manage related documents
The previous list is not complete, because it constantly evolves throughout the life of Elasticsearch. New query types are added to cover new search cases or they are occasionally renamed, such as text query in match query.