Sample Query with Elasticsearch [6.4]

Elasticsearch is a search engine. Elasticsearch use a full Query DSL (Domain Specific Language) . It’s a base on JSON fomat to define queries.

Query DSL ‘s consisting of two types of clauses:

1. clauses
   Leaf query clauses is looking for a value in a field, such as the match, term or range queries.
2. Compound query clauses
   Compound query clauses is combining multiple queries,such as the bool or dis_max query

Firstly, we will start with a basic examples (Leaf query) : Suppose we have a hotel node and we will to find all hotels. So,we can use the query sentence as below:

match

Match keyword is used for matching a value in the particular field. This query will return all of data in hotel node.

GET /hotel/_search
{
 “query”: { “match_all”: {} }
}

term

Term keyword is used for matching documents that contain the exact term specified.

GET /hotel/_search
{
 “query”: { “term”: {“hotel_name” : “Pull man G”} }
}

range

Rang keyword is used with the aggregate data that enables the user to define a set of ranges

GET /hotel/_search
{
     “query”: { 
         “range” : { 
            “price” : {
                 “gte” : 1000,
                 “lte” : 4000,
                 “boost” : 2.0
                      }
                   }
               }
}

Secondly, we will gives the basic examples of combining queries. ( Compound query) The sample query sentence is displayed below:

bool

Bool keyword is used for matching documents and combined with other queries

POST /hotel/_search
{
 “query”: {
    “bool” : {
       “must” : {
         “term” : {“hotel_name” : “Pullman” }
                },
       “filter”: {
          “term” : { “tag” : “hotel” }
               },
       “must_not” : {
            “range” : {
                “price” : { “gte” : 1000, “lte” : 4000 }
                      }
               },
        “should” : [
               { “term” : { “tag” : “breakfast” } }
            ],
        “boost” : 1.0
            }
         }
}

dis_max

Dis_max keyword is used with a union documents query (subqueries),
and calculate scores from each document (maximum score)and then plus a tie breaking increment .

GET /hotel/_search
{
  “query”: {
      “dis_max” : { 
           “tie_breaker” : 0.8, 
           “boost” : 2, 
           “queries” : [ 
              {
                 “term” : { “hotel_rang” : 1}
              },
              {
                 “term” : { “hotel_rang” : 2}
              }
            ]
         }
     }
}