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Specialized queries

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Specialized queries

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This group contains queries which do not fit into the other groups:

more_like_this query: This query finds documents which are similar to the specified text, document, or collection of documents.
script query: This query allows a script to act as a filter. Also see the function_score query.
percolate query: This query finds percolator queries based on documents.
wrapper query: A query that accepts other queries as json or yaml string.

More Like This Query

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See More Like This Query

String[] fields = {"name.first", "name.last"};               
String[] texts = {"text like this one"};                     

moreLikeThisQuery(fields, texts, null)
    .minTermFreq(1)                                          
    .maxQueryTerms(12);

	fields
	text
	ignore threshold
	max num of Terms in generated queries

Script Query

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See Script Query

scriptQuery(
        new Script("doc['num1'].value > 1")                  
    );

inlined script

If you have stored on each data node a script named myscript.painless with:

doc['num1'].value > params.param1

You can use it then with:

Map<String, Object> parameters = new HashMap<>();
parameters.put("param1", 5);
scriptQuery(new Script(
        ScriptType.STORED,                                   
        null,                                          
        "myscript",                                          
        singletonMap("param1", 5)));

	Script type: either `ScriptType.FILE`, `ScriptType.INLINE` or `ScriptType.INDEXED`
	Scripting engine
	Script name
	Parameters as a `Map<String, Object>`

Percolate Query

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See: * Percolate Query

Settings settings = Settings.builder().put("cluster.name", "elasticsearch").build();
TransportClient client = new PreBuiltTransportClient(settings);
client.addTransportAddress(new TransportAddress(new InetSocketAddress(InetAddresses.forString("127.0.0.1"), 9300)));

Before the percolate query can be used an percolator mapping should be added and a document containing a percolator query should be indexed:

// create an index with a percolator field with the name 'query':
client.admin().indices().prepareCreate("myIndexName")
                        .addMapping("_doc", "query", "type=percolator", "content", "type=text")
                        .get();

//This is the query we're registering in the percolator
QueryBuilder qb = termQuery("content", "amazing");

//Index the query = register it in the percolator
client.prepareIndex("myIndexName", "_doc", "myDesignatedQueryName")
    .setSource(jsonBuilder()
        .startObject()
            .field("query", qb) // Register the query
        .endObject())
    .setRefreshPolicy(RefreshPolicy.IMMEDIATE) // Needed when the query shall be available immediately
    .get();

This indexes the above term query under the name myDesignatedQueryName.

In order to check a document against the registered queries, use this code:

//Build a document to check against the percolator
XContentBuilder docBuilder = XContentFactory.jsonBuilder().startObject();
docBuilder.field("content", "This is amazing!");
docBuilder.endObject(); //End of the JSON root object

PercolateQueryBuilder percolateQuery = new PercolateQueryBuilder("query", "_doc", BytesReference.bytes(docBuilder));

// Percolate, by executing the percolator query in the query dsl:
SearchResponse response = client().prepareSearch("myIndexName")
        .setQuery(percolateQuery))
        .get();
//Iterate over the results
for(SearchHit hit : response.getHits()) {
    // Percolator queries as hit
}

Wrapper Query

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See Wrapper Query

String query = "{\"term\": {\"user\": \"kimchy\"}}"; 
wrapperQuery(query);

query defined as query builder

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