Filters

Search filters allow you to narrow down results based on specific criteria using logical operators and field conditions.

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Understanding Filters

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Filter Types

1. Logical Operators

   • AND: All conditions must match
   • OR: Any condition can match
   • NOR: No conditions should match

2. Field Operators

   • eq: Exact match
   • neq: Not equal
   • gt: Greater than
   • gte: Greater than or equal
   • lt: Less than
   • lte: Less than or equal
   • in: Value in array
   • nin: Value not in array
   • exists: Field exists
   • regex: Regular expression match

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Filter Structure

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Basic Filter

{
  "filters": {
    "AND": [
      {
        "key": "category",
        "operator": "eq",
        "value": "electronics"
      }
    ]
  }
}

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Complex Filter

{
  "filters": {
    "case_sensitive": true,
    "AND": [
      {
        "key": "price",
        "operator": "gte",
        "value": 100
      },
      {
        "key": "in_stock",
        "operator": "eq",
        "value": true
      }
    ],
    "OR": [
      {
        "key": "category",
        "operator": "eq",
        "value": "electronics"
      },
      {
        "key": "category",
        "operator": "eq",
        "value": "accessories"
      }
    ],
    "NOR": [
      {
        "key": "status",
        "operator": "eq",
        "value": "discontinued"
      }
    ]
  }
}

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Best Practices

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Performance Optimization

• Use indexed fields for filtering
• Combine related conditions under single operators
• Order conditions from most to least selective
• Use appropriate operators for data types

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Common Use Cases

1. Metadata Filtering

   • Filter by author, date, status
   • Filter by categories or tags
   • Filter by custom metadata fields

2. Content Filtering

   • Filter by content type
   • Filter by content length
   • Filter by content language

3. Quality Filtering

   • Filter by confidence scores
   • Filter by relevance thresholds
   • Filter by feature quality metrics

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Limitations

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Technical Limitations

• Only indexed fields can be filtered
• Complex filters may impact performance
• Maximum of 20 conditions per operator
• Nested filters not supported

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Performance Impact

• Each additional filter adds overhead
• Complex regex operations are expensive
• Large IN/NIN arrays affect performance
• Case-sensitive filtering requires more resources

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Data Type Constraints

• Date fields must use ISO 8601 format
• Numeric comparisons require consistent types
• Boolean values must be true/false
• String comparisons are exact by default

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Error Handling

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Common Errors

• Invalid field names
• Unsupported operators
• Type mismatches
• Missing required values

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Resolution Steps

1. Verify field names are correct
2. Check operator compatibility
3. Validate value types
4. Ensure all required fields are present

For implementation details and examples, see the Search API Reference.