How to construct a complex search query in Elasticsearch?

Here are the high-level steps to construct a complex search query in Elasticsearch:

1. Define the search criteria: Define the criteria for the search, including the fields to search, the search terms, and any additional filters or criteria that should be applied.

2. Choose the appropriate query types: Choose the appropriate query types for each search criterion, based on the data type and structure of the indexed data. You can use a combination of full-text, term, range, and other queries to construct the search.

3. Combine the queries: Combine the queries using Boolean operators such as AND, OR, and NOT to construct a complex search query. You can use parentheses to group queries and control the order of operations.

4. Specify sorting and aggregation options: Specify any additional sorting or aggregation options for the search results, such as sorting by relevance score or aggregating by date or category.

5. Execute the search: Execute the search using the Elasticsearch search API. The search results will be returned as a JSON object that includes the matching documents and any requested aggregations or sorting options.

Here is an example of a complex search query in Elasticsearch that searches for documents that contain the terms “apple” and “orange” in the “product_name” field, and have a “price” value between 10 and 50:

GET /my-index/_search
{
  "query": {
    "bool": {
      "must": [
        {"match": {"product_name": "apple"}},
        {"match": {"product_name": "orange"}},
        {"range": {"price": {"gte": 10, "lte": 50}}}
      ]
    }
  },
  "sort": [
    {"_score": {"order": "desc"}},
    {"price": {"order": "asc"}}
  ],
  "aggs": {
    "avg_price": {"avg": {"field": "price"}}
  }
}

This search query uses a Boolean query to combine three different query types: two match queries for the “product_name” field, and a range query for the “price” field. The query also specifies sorting options based on the relevance score and the “price” field, and includes an aggregation to calculate the average “price” value of the matching documents.

Overall, constructing a complex search query in Elasticsearch requires a good understanding of the query DSL and the data structure of the indexed data. By choosing the appropriate query types and combining them using Boolean operators, you can construct powerful and flexible search queries that retrieve the most relevant results for your needs.