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Home/ Questions/Q 6589581
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Editorial Team
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Editorial Team
Asked: May 25, 20262026-05-25T17:11:33+00:00 2026-05-25T17:11:33+00:00

this is a very novice question but I’m trying to understand how boosting certain

  • 0

this is a very novice question but I’m trying to understand how
boosting certain elements in a document works.

I started with this query,

{
  "from": 0,
  "size": 6,
  "fields": [
    "_id"
  ],
  "sort": {
    "_score": "desc",
    "vendor.name.stored": "asc",
    "item_name.stored": "asc"
  },
  "query": {
    "filtered": {
      "query": {
        "query_string": {
          "fields": [
            "_all"
          ],
          "query": "Calprotectin",
          "default_operator": "AND"
        }
      },
      "filter": {
        "and": [
          {
            "query": {
              "query_string": {
                "fields": [
                  "targeted_countries"
                ],
                "query": "All US"
              }
            }
          }
        ]
      }
    }
  }
}

then i needed to boost certain elements in the document more than the others
so I did this

{
  "from": 0,
  "size": 60,
  "fields": [
    "_id"
  ],
  "sort": {
    "_score": "desc",
    "vendor.name.stored": "asc",
    "item_name.stored": "asc"
  },
  "query": {
    "filtered": {
      "query": {
        "query_string": {
          "fields": [
            "item_name^4",
            "vendor^4",
            "id_plus_name",
            "category_name^3",
            "targeted_countries",
            "vendor_search_name^4",
            "AdditionalProductInformation^0.5",
            "AskAScientist^0.5",
            "BuyNowURL^0.5",
            "Concentration^0.5",
            "ProductLine^0.5",
            "Quantity^0.5",
            "URL^0.5",
            "Activity^1",
            "Form^1",
            "Immunogen^1",
            "Isotype^1",
            "Keywords^1",
            "Matrix^1",
            "MolecularWeight^1",
            "PoreSize^1",
            "Purity^1",
            "References^1",
            "RegulatoryStatus^1",
            "Specifications/Features^1",
            "Speed^1",
            "Target/MoleculeDescriptor^1",
            "Time^1",
            "Description^2",
            "Domain/Region/Terminus^2",
            "Method^2",
            "NCBIGeneAliases^2",
            "Primary/Secondary^2",
            "Source/ExpressionSystem^2",
            "Target/MoleculeSynonym^2",
            "Applications^3",
            "Category^3",
            "Conjugate/Tag/Label^3",
            "Detection^3",
            "GeneName^3",
            "Host^3",
            "ModificationType^3",
            "Modifications^3",
            "MoleculeName^3",
            "Reactivity^3",
            "Species^3",
            "Target^3",
            "Type^3",
            "AccessionNumber^4",
            "Brand/Trademark^4",
            "CatalogNumber^4",
            "Clone^4",
            "entrezGeneID^4",
            "GeneSymbol^4",
            "OriginalItemName^4",
            "Sequence^4",
            "SwissProtID^4",
            "option.AntibodyProducts^4",
            "option.AntibodyRanges&Modifications^1",
            "option.Applications^4",
            "option.Conjugate^3",
            "option.GeneID^4",
            "option.HostSpecies^3",
            "option.Isotype^3",
            "option.Primary/Secondary^2",
            "option.Reactivity^4",
            "option.Search^1",
            "option.TargetName^1",
            "option.Type^4"
          ],
          "query": "Calprotectin",
          "default_operator": "AND"
        }
      },
      "filter": {
        "and": [
          {
            "query": {
              "query_string": {
                "fields": [
                  "targeted_countries"
                ],
                "query": "All US"
              }
            }
          }
        ]
      }
    }
  }
} 

the query slowed down considerably, am I doing this correctly? Is there a
way to speed it up? I’m currently in the process of doing the boosting when I index the document, but using it in the query that way is best for the way my application runs. Any help is much appreciated

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1 Answer

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  1. Editorial Team
    Editorial Team
    2026-05-25T17:11:34+00:00Added an answer on May 25, 2026 at 5:11 pm

    Query time boosting is used for assigning larger weight to a term. If you want to permanently boost a field, use index time boosting. If you don’t want to use this boosting all the time, then it makes sense to create a separate mapping just for it with store: "no" set.

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