Using DSL to Search for Data in OpenSearch

DSL Usage Example

GET /test/_search
{
  "query": {
    "match_all": {}
  }
}

Common DSL Query Statements

• Sets the query filters, which is equivalent to where in the SQL language.

  In the command below, there is no index filter in front of _search, so all indexes are queried. A bool query allows you to combine multiple search queries with boolean conditions. filter forcibly filters documents whose status field is published and publish_date is later than 2015-01-01. must specifies that both title and content must include Search.

  Note

  The difference between must and filter is that filter is equivalent to where in SQL but its results are not used for scoring. The must field is also a mandatory filter criteria, but the matching documents are scored based on relevance. The most relevant documents are displayed at the top.

  GET /_search
  {
    "query": {
      "bool": {
        "must": [
          {
            "match": {
              "title": "Search"
            }
          },
          {
            "match": {
              "content": "search"
            }
          }
        ],
        "filter": [
          {
            "term": {
              "status": "published"
            }
          },
          {
            "range": {
              "publish_date": {
                "gte": "2015-01-01"
              }
            }
          }
        ]
      }
    }
  }
  
  

• Aggregations are similar to Group by in SQL.

  An aggregation summarizes your data as metrics, statistics, or other analytics. In the example below, the results are aggregated based on the title field in the test index. If title is of the text (including keyword) type, use title.keyword for aggregation. By default, a cluster cannot directly aggregate data of the text type. titles is only an example name of the aggregation. You can name the aggregation titleaggs instead.

  GET /test/_search
  {
    "aggs": {
      "titles": {
        "terms": {
          "field": "title.keyword"
        }
      }
    }
  }
  
  

  The example above for query aggregation includes all documents in the test index. That is, match_all is used. You can set search criteria to narrow the scope of the aggregation to specific documents.