elasticsearch - 为什么两个相同的文档分数不同？

我目前正在研究轮胎 gem (我对Elasticsearch和lucene还是陌生的)，并尝试了一些方法。我将需要进行一些(可能是不平凡的)计分，所以我会设法捕获这一点。我阅读了在网上可以找到的有关计分公式的所有内容，并尝试将我找到的内容与解释的查询进行匹配。

如果我正确阅读这些数字，则标题为“foo foo foo foo foo”的文档的分数会有所不同，这肯定不是预期的。我想我在索引编制过程中或之后都缺少一个步骤，但是我无法弄清楚。

下面是我的代码。我并没有完全按照轮胎DSL的预期方式进行，因为我想弄清楚-某些时候以后看起来可能更疲倦。

require 'tire'
require 'pp'

class Model
  INDEX = 'myindex'
  TYPE = 'company'

  class << self
    def delete_index
      Tire.index(INDEX) { delete }
    end

    def create_mapping
      Tire.index INDEX do
        create mappings: {
          TYPE => {
            properties: {
              title: { type: 'string' }
            }
          }
        }
      end
    end

    def refresh_index
      Tire.index INDEX do
        refresh
      end
    end
  end

  def initialize(attributes = {})
    @attributes = attributes.merge(:_id => object_id) #use oid as id, just for testing
  end

  def _type
    TYPE
  end

  def id
    object_id.to_s #convert to string because tire compares to object_id!
  end

  def index
    item = self
    Tire.index INDEX do
      store item
    end
  end

  def to_indexed_json
    @attributes.to_json
  end

  ENTITIES = [
    new(title: "foo foo foo foo"),
    new(title: "foo"),
    new(title: "bar"),
    new(title: "foo bar"),
    new(title: "xxx"),
    new(title: "foo foo foo foo"),
    new(title: "foo foo"),
    new(title: "foo bar baz")
  ]

  QUERIES = {
    :foo => { query_string: { query: "foo" } },
    :all => { match_all: {} }
  }

  def self.custom_explained_search(q)
    Tire.search(Model::INDEX, :wrapper => Model, :explain => true) do |search|
      search.query do |query|
        query.send :instance_variable_set, :@value, q
      end
    end
  end
end

class Tire::Results::Collection
  def explained
    @response["hits"]["hits"].map do |hit|
      {
        "_id" => hit["_id"],
        "_explanation" => hit["_explanation"],
        "title" => hit["_source"]["title"]
      }
    end
  end
end

Model.delete_index
Model.create_mapping
Model::ENTITIES.each &:index
Model.refresh_index
s = Model.custom_explained_search(Model::QUERIES[:foo])
pp s.results.explained

打印结果是这样的:

[{"_id"=>"2169251840",
  "_explanation"=>
   {"value"=>0.54932046,
    "description"=>"fieldWeight(_all:foo in 0), product of:",
    "details"=>
     [{"value"=>1.4142135,
       "description"=>"btq, product of:",
       "details"=>
        [{"value"=>1.4142135, "description"=>"tf(phraseFreq=2.0)"},
         {"value"=>1.0, "description"=>"allPayload(...)"}]},
      {"value"=>0.7768564, "description"=>"idf(_all:  foo=4)"},
      {"value"=>0.5, "description"=>"fieldNorm(field=_all, doc=0)"}]},
  "title"=>"foo foo foo foo"},
 {"_id"=>"2169251720",
  "_explanation"=>
   {"value"=>0.54932046,
    "description"=>"fieldWeight(_all:foo in 1), product of:",
    "details"=>
     [{"value"=>0.70710677,
       "description"=>"btq, product of:",
       "details"=>
        [{"value"=>0.70710677, "description"=>"tf(phraseFreq=0.5)"},
         {"value"=>1.0, "description"=>"allPayload(...)"}]},
      {"value"=>0.7768564, "description"=>"idf(_all:  foo=4)"},
      {"value"=>1.0, "description"=>"fieldNorm(field=_all, doc=1)"}]},
  "title"=>"foo"},
 {"_id"=>"2169250520",
  "_explanation"=>
   {"value"=>0.48553526,
    "description"=>"fieldWeight(_all:foo in 2), product of:",
    "details"=>
     [{"value"=>1.0,
       "description"=>"btq, product of:",
       "details"=>
        [{"value"=>1.0, "description"=>"tf(phraseFreq=1.0)"},
         {"value"=>1.0, "description"=>"allPayload(...)"}]},
      {"value"=>0.7768564, "description"=>"idf(_all:  foo=4)"},
      {"value"=>0.625, "description"=>"fieldNorm(field=_all, doc=2)"}]},
  "title"=>"foo foo"},
 {"_id"=>"2169251320",
  "_explanation"=>
   {"value"=>0.44194174,
    "description"=>"fieldWeight(_all:foo in 1), product of:",
    "details"=>
     [{"value"=>0.70710677,
       "description"=>"btq, product of:",
       "details"=>
        [{"value"=>0.70710677, "description"=>"tf(phraseFreq=0.5)"},
         {"value"=>1.0, "description"=>"allPayload(...)"}]},
      {"value"=>1.0, "description"=>"idf(_all:  foo=1)"},
      {"value"=>0.625, "description"=>"fieldNorm(field=_all, doc=1)"}]},
  "title"=>"foo bar"},
 {"_id"=>"2169250380",
  "_explanation"=>
   {"value"=>0.27466023,
    "description"=>"fieldWeight(_all:foo in 3), product of:",
    "details"=>
     [{"value"=>0.70710677,
       "description"=>"btq, product of:",
       "details"=>
        [{"value"=>0.70710677, "description"=>"tf(phraseFreq=0.5)"},
         {"value"=>1.0, "description"=>"allPayload(...)"}]},
      {"value"=>0.7768564, "description"=>"idf(_all:  foo=4)"},
      {"value"=>0.5, "description"=>"fieldNorm(field=_all, doc=3)"}]},
  "title"=>"foo bar baz"},
 {"_id"=>"2169250660",
  "_explanation"=>
   {"value"=>0.2169777,
    "description"=>"fieldWeight(_all:foo in 0), product of:",
    "details"=>
     [{"value"=>1.4142135,
       "description"=>"btq, product of:",
       "details"=>
        [{"value"=>1.4142135, "description"=>"tf(phraseFreq=2.0)"},
         {"value"=>1.0, "description"=>"allPayload(...)"}]},
      {"value"=>0.30685282, "description"=>"idf(_all:  foo=1)"},
      {"value"=>0.5, "description"=>"fieldNorm(field=_all, doc=0)"}]},
  "title"=>"foo foo foo foo"}]

我读错数字了吗？还是滥用轮胎？也许只是缺少一些“重新索引整个馆藏”步骤？

最佳答案

afaik如果未定义显式排序字段，则排序默认为tf * idf(http://en.wikipedia.org/wiki/Tf * idf)的变体。

从字面上看:术语频率*反文档频率。

从维基百科:

术语频率(术语计数):给定文档中的术语计数只是给定术语在该文档中出现的次数

反向文档频率用于衡量该术语在所有文档中是通用还是罕见。通过将文档总数除以包含该术语的文档数量，然后取该商的对数来获得

在这种情况下，排序的“词频”部分很可能导致“foo foo foo foo foo”在搜索“foo”时得分高于其他文档

此外，关于更改id时看到的效果:我不确定，但是我猜想ES必须在内部存储id排序的文档(我不确定)。

如果是这种情况，则具有相同排序得分的2个文档将根据id作为决胜局进行排序。您当然可以定义多种排序以更改此行为(例如:sort = sorta + desc，sortb + desc。在这种情况下，sortb用作所有在scoreA得分相同的文档的决胜局)

关于elasticsearch - 为什么两个相同的文档分数不同？，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/11229568/