Elasticsearch Elasticsearch Cross-Index Query: Advanced Techniques and Best Practices

By Opster Team

Updated: Jun 22, 2023

| 2 min read

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Introduction

Cross-index querying is a powerful technique in Elasticsearch that allows you to search across multiple indices simultaneously. This can be particularly useful when you have data spread across different indices, and you want to retrieve relevant information from all of them in a single query. In this article, we will discuss advanced techniques and best practices for performing cross-index queries in Elasticsearch.

1. Using Multi-Index Query Syntax

Elasticsearch supports a simple syntax for querying multiple indices at once. To perform a cross-index query, you can specify multiple index names separated by commas or use wildcards to match multiple indices. For example:

GET /index1,index2,index3/_search
{
  "query": {
    "match": {
      "field": "value"
    }
  }
}

Or using wildcards:

GET /index*/_search
{
  "query": {
    "match": {
      "field": "value"
    }
  }
}

2. Handling Fields with Different Mappings

When querying across multiple indices, you may encounter fields with different mappings. To handle this situation, you can use the `ignore_unmapped` option in your query. This will ignore any fields that do not have a mapping in the queried indices. For example:

GET /index1,index2/_search
{
  "query": {
    "bool": {
      "should": [
        {
          "term": {
            "field1": {
              "value": "search_term",
              "ignore_unmapped": true
            }
          }
        },
        {
          "term": {
            "field2": {
              "value": "search_term",
              "ignore_unmapped": true
            }
          }
        }
      ]
    }
  }
}

3. Using Field Aliases

Field aliases can be used to create a consistent field name across indices with different mappings. This can simplify your cross-index queries and make them more maintainable. To create a field alias, you can add an alias definition to your index mapping:

PUT /index1/_mapping
{
  "properties": {
    "field_alias": {
      "type": "alias",
      "path": "original_field"
    }
  }
}

Now you can use the field alias in your cross-index queries:

GET /index1,index2/_search
{
  "query": {
    "match": {
      "field_alias": "search_term"
    }
  }
}

4. Filtering Results by Index

In some cases, you may want to apply different filters or scoring rules based on the index from which the document originates. You can achieve this by using the `_index` meta field in your query. For example:

GET /index1,index2/_search
{
  "query": {
    "bool": {
      "must": [
        {
          "match": {
            "field": "search_term"
          }
        }
      ],
      "should": [
        {
          "term": {
            "_index": {
              "value": "index1",
              "boost": 2
            }
          }
        }
      ]
    }
  }
}

In this example, documents from `index1` will receive a higher score than those from `index2`.

Conclusion

In conclusion, Elasticsearch provides several advanced techniques and best practices for performing cross-index queries. By using multi-index query syntax, handling fields with different mappings, using field aliases, and filtering results by index, you can efficiently search across multiple indices and retrieve relevant information in a single query.

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