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Suppose that I have the below simplified schema:

const Venue = new mongoose.Schema(
  {
    name: {
      en: { type: String, required: true }, // English translation
      fr: { type: String, required: true }, // French translation
      es: { type: String, required: true }, // Spanish translation
      sw: { type: String, required: true },
    },
    country: {
      en: { type: String, required: true }, // English translation
      fr: { type: String, required: true }, // French translation
      es: { type: String, required: true }, // Spanish translation
      sw: { type: String, required: true },
    },
    countryIso3: String,
  },
  { collection: 'Venues', timestamps: true }
);

export default mongoose.models.Venue || mongoose.model('Venues', Venue);

So, I want to use one index definition that support dual-purpose fields (autocomplete + text search). How to do that by providing also the highlight score and inject the score boost during aggregation?

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  • This is a cool use case. I’ve had to handle something similar — combining autocomplete and full text search in Mongo isn’t straightforward with a single index. What worked for me was using a $search stage from Atlas Search with a compound index: use autocomplete for user input and text for broader matching. Then you can boost scores inside the compound using score > boost > value, and even include highlights with highlight: { path: [...] }. Curious how others optimize this too! Commented Jul 20 at 8:26
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