Elasticsearch Getting started with Elasticsearch Indexing and retrieving a document

Example

Elasticsearch is accessed through a HTTP REST API, typically using the cURL library. The messages between the search server and the client (your or your application) are sent in the form of JSON strings. By default, Elasticsearch runs on port 9200.

In the examples below, ?pretty is added to tell Elasticsearch to prettify the JSON response. When using these endpoints within an application you needn't add this query parameter.

Indexing documents

If we intend to update information within an index later, it's a good idea to assign unique IDs to the documents we index. To add a document to the index named megacorp, with type employee and ID 1 run:

curl -XPUT "http://localhost:9200/megacorp/employee/1?pretty" -d'
{
    "first_name" : "John",
    "last_name" :  "Smith",
    "age" :        25,
    "about" :      "I love to go rock climbing",
    "interests": [ "sports", "music" ]
}' 

Response:

{
  "_index": "megacorp",
  "_type": "employee",
  "_id": "1",
  "_version": 1,
  "_shards": {
    "total": 2,
    "successful": 1,
    "failed": 0
  },
  "created": true
}

The index is created if it does not exist when we send the PUT call.

Indexing without an ID

POST /megacorp/employee?pretty
{
    "first_name" :  "Jane",
    "last_name" :   "Smith",
    "age" :         32,
    "about" :       "I like to collect rock albums",
    "interests":  [ "music" ]
}

Response:

{
  "_index": "megacorp",
  "_type": "employee",
  "_id": "AVYg2mBJYy9ijdngfeGa",
  "_version": 1,
  "_shards": {
    "total": 2,
    "successful": 2,
    "failed": 0
  },
  "created": true
}

Retrieving documents

curl -XGET "http://localhost:9200/megacorp/employee/1?pretty"

Response:

{
  "_index": "megacorp",
  "_type": "employee",
  "_id": "1",
  "_version": 1,
  "found": true,
  "_source": {
    "first_name": "John",
    "last_name": "Smith",
    "age": 25,
    "about": "I love to go rock climbing",
    "interests": [
      "sports",
      "music"
    ]
  }
}

Fetch 10 documents from the megacorp index with the type employee:

curl -XGET "http://localhost:9200/megacorp/employee/_search?pretty"

Response:

{
  "took": 2,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "failed": 0
  },
  "hits": {
    "total": 2,
    "max_score": 1,
    "hits": [
      {
        "_index": "megacorp",
        "_type": "employee",
        "_id": "1",
        "_score": 1,
        "_source": {
          "first_name": "John",
          "last_name": "Smith",
          "age": 25,
          "about": "I love to go rock climbing",
          "interests": [
            "sports",
            "music"
          ]
        }
      },
      {
        "_index": "megacorp",
        "_type": "employee",
        "_id": "AVYg2mBJYy9ijdngfeGa",
        "_score": 1,
        "_source": {
          "first_name": "Jane",
          "last_name": "Smith",
          "age": 32,
          "about": "I like to collect rock albums",
          "interests": [
            "music"
          ]
        }
      }
    ]
  }
}

Simple search using the match query, which looks for exact matches in the field provided:

curl -XGET "http://localhost:9200/megacorp/employee/_search" -d'
{
    "query" : {
        "match" : {
            "last_name" : "Smith"
        }
    }
}'

Response:

{
  "took": 2,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "failed": 0
  },
  "hits": {
    "total": 1,
    "max_score": 0.6931472,
    "hits": [
      {
        "_index": "megacorp",
        "_type": "employee",
        "_id": "1",
        "_score": 0.6931472,
        "_source": {
          "first_name": "John",
          "last_name": "Smith",
          "age": 25,
          "about": "I love to go rock climbing",
          "interests": [
            "sports",
            "music"
          ]
        }
      }
    ]
  }
}