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You want to optimize search speed on a large text field description. How can defining the mapping help achieve this?

hard🚀 Application Q15 of 15
Elasticsearch - Mappings and Data Types
You want to optimize search speed on a large text field description. How can defining the mapping help achieve this?
ABy setting the field type to <code>text</code> with a custom analyzer for better indexing
BBy setting the field type to <code>keyword</code> to avoid full-text analysis
CBy omitting the field from the mapping so Elasticsearch guesses the type
DBy setting the field type to <code>integer</code> to speed up searches
Step-by-Step Solution
Solution:

  1. Step 1: Understand field types for text search

    Text fields use analyzers to break text into searchable tokens. Custom analyzers can improve search relevance and speed.

  2. Step 2: Evaluate options for optimization

    Setting type to text with a custom analyzer helps optimize indexing and searching. keyword is for exact matches, not full-text search. Omitting mapping causes guessing, which is less efficient. Integer type is invalid for text.

  3. Final Answer:

    By setting the field type to text with a custom analyzer for better indexing -> Option A

  4. Quick Check:

    Custom analyzer on text field = faster, better search [OK]
Quick Trick: Use custom analyzers on text fields for faster search [OK]
Common Mistakes:
MISTAKES
  • Using keyword type for full-text search
  • Not defining mapping and relying on defaults
  • Assigning wrong data types like integer to text fields

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