Elasticsearch Wildcard Query

What it does

The Wildcard Query in Elasticsearch allows for flexible pattern matching using wildcard operators, and allows searching for documents that contain terms matching a specified pattern. It uses two wildcard operators:

• *: Matches any number of characters (including zero)
• ?: Matches any single character

Syntax

GET /_search
{
  "query": {
    "wildcard": {
      "field_name": {
        "value": "pattern*"
      }
    }
  }
}

For more details, refer to the official Elasticsearch documentation on Wildcard Query.

Example Query

GET /products/_search
{
  "query": {
    "wildcard": {
      "product_name": {
        "value": "iph*ne"
      }
    }
  }
}

This query will match documents where the product_name field contains terms like "iphone", "iphone 12", "iphone pro", etc.

Common Issues

1. Performance: Wildcard queries, especially with leading wildcards, can be slow and resource-intensive.
2. Case sensitivity: Wildcard queries are case-sensitive by default.
3. Unexpected matches: Be cautious with patterns that might match unintended terms.

Best Practices

1. Avoid using wildcards at the beginning of a pattern when possible, as it can significantly slow down the query.
2. Consider using the case_insensitive parameter for case-insensitive matching.
3. Use more specific patterns to improve performance and accuracy.
4. For better performance on large datasets, consider using n-grams or edge n-grams instead of wildcard queries.

Frequently Asked Questions

Q: How can I make a wildcard query case-insensitive?
A: You can use the case_insensitive parameter set to true in your query:

{
  "wildcard": {
    "field": {
      "value": "pattern*",
      "case_insensitive": true
    }
  }
}

Q: Can I use multiple wildcards in a single pattern?
A: Yes, you can use multiple wildcards in a single pattern. For example, "a*b?c" is a valid pattern.

Q: How does wildcard query performance compare to regex query?
A: Wildcard queries are generally faster than regex queries, especially for simpler patterns. However, both can be slow for large datasets or complex patterns.

Q: Can I use wildcard queries on numeric fields?
A: Wildcard queries are designed for text fields. For numeric fields, consider using range queries or term queries instead.

Q: Is there a limit to the number of terms a wildcard query can match?
A: While there's no hard limit, matching too many terms can impact performance. It's best to use more specific patterns to limit the number of potential matches.