Elasticsearch Start searching

Once you have ingested some data into an Elasticsearch index, you can search it by sending requests to the _search endpoint. To access the full suite of search capabilities, you use the Elasticsearch Query DSL to specify the search criteria in the request body. You specify the name of the index you want to search in the request URI.

For example, the following request retrieves all documents in the bank index sorted by account number:

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GET /bank/_search
{
  "query": { "match_all": {} },
  "sort": [
    { "account_number": "asc" }
  ]
}

By default, the hits section of the response includes the first 10 documents that match the search criteria:

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{
  "took" : 63,
  "timed_out" : false,
  "_shards" : {
    "total" : 5,
    "successful" : 5,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
        "value": 1000,
        "relation": "eq"
    },
    "max_score" : null,
    "hits" : [ {
      "_index" : "bank",
      "_type" : "_doc",
      "_id" : "0",
      "sort": [0],
      "_score" : null,
      "_source" : {"account_number":0,"balance":16623,"firstname":"Bradshaw","lastname":"Mckenzie","age":29,"gender":"F","address":"244 Columbus Place","employer":"Euron","email":"bradshawmckenzie@euron.com","city":"Hobucken","state":"CO"}
    }, {
      "_index" : "bank",
      "_type" : "_doc",
      "_id" : "1",
      "sort": [1],
      "_score" : null,
      "_source" : {"account_number":1,"balance":39225,"firstname":"Amber","lastname":"Duke","age":32,"gender":"M","address":"880 Holmes Lane","employer":"Pyrami","email":"amberduke@pyrami.com","city":"Brogan","state":"IL"}
    }, ...
    ]
  }
}

The response also provides the following information about the search request:

took -- how long it took Elasticsearch to run the query, in milliseconds
timed_out -- whether or not the search request timed out
_shards -- how many shards were searched and a breakdown of how many shards succeeded, failed, or were skipped.
max_score -- the score of the most relevant document found
hits.total.value - how many matching documents were found
hits.sort - the document's sort position (when not sorting by relevance score)
hits._score - the document's relevance score (not applicable when using match_all)

Each search request is self-contained: Elasticsearch does not maintain any state information across requests. To page through the search hits, specify the from and size parameters in your request.

For example, the following request gets hits 10 through 19:

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GET /bank/_search
{
  "query": { "match_all": {} },
  "sort": [
    { "account_number": "asc" }
  ],
  "from": 10,
  "size": 10
}

Now that you've seen how to submit a basic search request, you can start to construct queries that are a bit more interesting than match_all.

To search for specific terms within a field, you can use a match query. For example, the following request searches the address field to find customers whose addresses contain mill or lane:

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GET /bank/_search
{
  "query": { "match": { "address": "mill lane" } }
}

To perform a phrase search rather than matching individual terms, you use match_phrase instead of match. For example, the following request only matches addresses that contain the phrase mill lane:

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GET /bank/_search
{
  "query": { "match_phrase": { "address": "mill lane" } }
}

To construct more complex queries, you can use a bool query to combine multiple query criteria. You can designate criteria as required (must match), desirable (should match), or undesirable (must not match).

For example, the following request searches the bank index for accounts that belong to customers who are 40 years old, but excludes anyone who lives in Idaho (ID):

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GET /bank/_search
{
  "query": {
    "bool": {
      "must": [
        { "match": { "age": "40" } }
      ],
      "must_not": [
        { "match": { "state": "ID" } }
      ]
    }
  }
}

Each must, should, and must_not element in a Boolean query is referred to as a query clause. How well a document meets the criteria in each must or should clause contributes to the document's relevance score. The higher the score, the better the document matches your search criteria. By default, Elasticsearch returns documents ranked by these relevance scores.

The criteria in a must_not clause is treated as a filter. It affects whether or not the document is included in the results, but does not contribute to how documents are scored. You can also explicitly specify arbitrary filters to include or exclude documents based on structured data.

For example, the following request uses a range filter to limit the results to accounts with a balance between $20,000 and$ 30,000 (inclusive).

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GET /bank/_search
{
  "query": {
    "bool": {
      "must": { "match_all": {} },
      "filter": {
        "range": {
          "balance": {
            "gte": 20000,
            "lte": 30000
          }
        }
      }
    }
  }
}