zoukankan      html  css  js  c++  java
  • ES 搜索结果expalain 可以类似数据库性能调优来看排序算法的选择

    When we run a simple term query with explain set to true (see Understanding the Score), you will see that the only factors involved in calculating the score are the ones explained in the preceding sections:

    PUT /my_index/doc/1
    { "text" : "quick brown fox" }
    
    GET /my_index/doc/_search?explain
    {
      "query": {
        "term": {
          "text": "fox"
        }
      }
    }

    The (abbreviated) explanation from the preceding request is as follows:

    weight(text:fox in 0) [PerFieldSimilarity]:  0.15342641 

    result of:
        fieldWeight in 0                         0.15342641
        product of:
            tf(freq=1.0), with freq of 1:        1.0 

            idf(docFreq=1, maxDocs=1):           0.30685282 

            fieldNorm(doc=0):                    0.5 

    The final score for term fox in field text in the document with internal Lucene doc ID 0.

    The term fox appears once in the text field in this document.

    The inverse document frequency of fox in the text field in all documents in this index.

    The field-length normalization factor for this field.

    Of course, queries usually consist of more than one term, so we need a way of combining the weights of multiple terms. For this, we turn to the vector space model.

    见:https://www.elastic.co/guide/en/elasticsearch/guide/current/scoring-theory.html

  • 相关阅读:
    hbase distributed setup and configuration
    代码优化 性能调优
    正则表达
    [转载]Java&.Net虚拟机精简(GreenJVM&GreenDotNet发布)
    [JQuery]一款不错的jquery验证框架
    js特效集
    jQuery滚动插件2 jCarousel
    c3p0连接池
    php5 apache config
    jQuery滚动插件 (轮播)
  • 原文地址:https://www.cnblogs.com/bonelee/p/6473226.html
Copyright © 2011-2022 走看看