elasticsearch _field_stats 源码分析
_field_stats 实现的功能:https://www.elastic.co/guide/en/elasticsearch/reference/5.6/search-field-stats.html
获取索引下字段的统计信息,如下表,同时还可以针对这些统计值进行过滤:
Field statistics
The field stats api is supported on string based, number based and date based fields and can return the following statistics per field:
|
|
The total number of documents. |
|
|
The number of documents that have at least one term for this field, or -1 if this measurement isn’t available on one or more shards. |
|
|
The percentage of documents that have at least one value for this field. This is a derived statistic and is based on the |
|
|
The sum of each term’s document frequency in this field, or -1 if this measurement isn’t available on one or more shards. Document frequency is the number of documents containing a particular term. |
|
|
The sum of the term frequencies of all terms in this field across all documents, or -1 if this measurement isn’t available on one or more shards. Term frequency is the total number of occurrences of a term in a particular document and field. |
Field stats index constraints ——kibana里按照时间范围进行绘图就是用到这个。
Field stats index constraints allows to omit all field stats for indices that don’t match with the constraint. An index constraint can exclude indices' field stats based on the min_value and max_value statistic. This option is only useful if the level option is set to indices. Fields that are not indexed (not searchable) are always omitted when an index constraint is defined.
For example index constraints can be useful to find out the min and max value of a particular property of your data in a time based scenario. The following request only returns field stats for the answer_count property for indices holding questions created in the year 2014:
POST _field_stats?level=indices
{
"fields" : ["answer_count"],
![]()
"index_constraints" : {
![]()
"creation_date" : {
![]()
"max_value" : {
![]()
"gte" : "2014-01-01T00:00:00.000Z"
},
"min_value" : {
![]()
"lt" : "2015-01-01T00:00:00.000Z"
}
}
}
}
对应ES5.5的源码部分:elasticsearch/search/lookup/IndexField.java
import org.apache.lucene.search.CollectionStatistics;
import org.elasticsearch.common.util.MinimalMap; import java.io.IOException;
import java.util.HashMap;
import java.util.Map; /**
* Script interface to all information regarding a field.
* */
public class IndexField extends MinimalMap<String, IndexFieldTerm> { /*
* TermsInfo Objects that represent the Terms are stored in this map when
* requested. Information such as frequency, doc frequency and positions
* information can be retrieved from the TermInfo objects in this map.
*/
private final Map<String, IndexFieldTerm> terms = new HashMap<>(); // the name of this field
private final String fieldName; /*
* The holds the current reader. We need it to populate the field
* statistics. We just delegate all requests there
*/
private final LeafIndexLookup indexLookup; /*
* General field statistics such as number of documents containing the
* field.
*/
private final CollectionStatistics fieldStats;
public IndexField(String fieldName, LeafIndexLookup indexLookup) throws IOException { assert fieldName != null;
this.fieldName = fieldName; assert indexLookup != null;
this.indexLookup = indexLookup; fieldStats = this.indexLookup.getIndexSearcher().collectionStatistics(fieldName);
} /* get number of documents containing the field */
public long docCount() throws IOException {
return fieldStats.docCount();
} /* get sum of the number of words over all documents that were indexed */
public long sumttf() throws IOException {
return fieldStats.sumTotalTermFreq();
} /*
* get the sum of doc frequencies over all words that appear in any document
* that has the field.
*/
public long sumdf() throws IOException {
return fieldStats.sumDocFreq();
}
// 。。。。。。。
}
elasticsearch _field_stats 源码分析的更多相关文章
- Elasticsearch之源码分析(shard分片规则)
前期博客是 Elasticsearch之源码编译 (1)elasticsearch在建立索引时,根据id或(id,类型)进行hash,得到hash值之后再与该索引的分片数量取模,取模的值即为存入的分片 ...
- ElasticSearch Index操作源码分析
ElasticSearch Index操作源码分析 本文记录ElasticSearch创建索引执行源码流程.从执行流程角度看一下创建索引会涉及到哪些服务(比如AllocationService.Mas ...
- Elasticsearch源码分析 - 源码构建
原文地址:https://mp.weixin.qq.com/s?__biz=MzU2Njg5Nzk0NQ==&mid=2247483694&idx=1&sn=bd03afe5a ...
- ElasticSearch 启动时加载 Analyzer 源码分析
ElasticSearch 启动时加载 Analyzer 源码分析 本文介绍 ElasticSearch启动时如何创建.加载Analyzer,主要的参考资料是Lucene中关于Analyzer官方文档 ...
- Elasticsearch源码分析—线程池(十一) ——就是从队列里处理请求
Elasticsearch源码分析—线程池(十一) 转自:https://www.felayman.com/articles/2017/11/10/1510291570687.html 线程池 每个节 ...
- elasticsearch源码分析之search模块(server端)
elasticsearch源码分析之search模块(server端) 继续接着上一篇的来说啊,当client端将search的请求发送到某一个node之后,剩下的事情就是server端来处理了,具体 ...
- elasticsearch源码分析之search模块(client端)
elasticsearch源码分析之search模块(client端) 注意,我这里所说的都是通过rest api来做的搜索,所以对于接收到请求的节点,我姑且将之称之为client端,其主要的功能我们 ...
- Solr4.8.0源码分析(13)之LuceneCore的索引修复
Solr4.8.0源码分析(13)之LuceneCore的索引修复 题记:今天在公司研究elasticsearch,突然看到一篇博客说elasticsearch具有索引修复功能,顿感好奇,于是点进去看 ...
- 转-filebeat 源码分析
背景 在基于elk的日志系统中,filebeat几乎是其中必不可少的一个组件,例外是使用性能较差的logstash file input插件或自己造个功能类似的轮子:). 在使用和了解filebeat ...
随机推荐
- HDU_4826_dp
Labyrinth Time Limit: 2000/1000 MS (Java/Others) Memory Limit: 32768/32768 K (Java/Others)Total S ...
- Concurrency and Application Design
Concurrency and Application Design In the early days of computing, the maximum amount of work per un ...
- Python 之lxml解析库
一.XPath常用规则 二.解析html文件 from lxml import etree # 读取HTML文件进行解析 def parse_html_file(): html = etree.par ...
- Error: Registry key 'Software\JavaSoft\Java Runtime has value '1.8', but '1.7' is
cmd下输入 java命令时出现该错误: Error: Registry key 'Software\JavaSoft\Java Runtimehas value '1.8', but '1.7' i ...
- JAVA经典题--计算一个字符串中每个字符出现的次数
需求: 计算一个字符串中每个字符出现的次数 思路: 通过toCharArray()拿到一个字符数组--> 遍历数组,将数组元素作为key,数值1作为value存入map容器--> 如果k ...
- python 函数编写指南
#函数编写指南:1.给函数指定描述性名称,且只在其中是用小写字母和下划线 2.每个函数都应包含简要的阐述其功能的注释,该注释应紧跟在函数定义后面,且采用文档字符串格式 3.给形参指定默认值时,等号两边 ...
- 6 DataFrame处理丢失数据--数据清洗
处理丢失数据 有两种丢失数据: · None · np.nan(NaN) 1 None None是Python自带的,其类 ...
- 第2章 Python序列
Python序列类似于C或Basic中的一维.多维数组等,但功能要强大很多,使用也更加灵活.方便,Head First Python一书就戏称列表是“打了激素”的数组. Python中常用的序列结构有 ...
- Tensorflow读取csv文件(转)
常用的直接读取方法实例:#加载包 import tensorflow as tf import os #设置工作目录 os.chdir("你自己的目录") #查看目录 print( ...
- 如何实现在scrapy调试爬虫
# -*- coding:utf-8 -*- from scrapy.cmdline import execute import sys import os '''在爬虫文件夹下面自定义一个main. ...