Elasticsearch7.5 字段类型说明
（小声BB，有道云笔记上传图片要收钱无奈直接用CSDN）
alias/字段别名
简介：
别名可以代替搜索请求中的目标字段
PUT trips
{
"mappings": {
"properties": {
"distance": {
"type": "long"
},
"route_length_miles": {
"type": "alias",
"path": "distance"
},
"transit_mode": {
"type": "keyword"
}
}
}
}
GET _search
{
"query": {
"range" : {
"route_length_miles" : {
"gte" : 39
}
}
}
}
在搜索请求的某些部分以及当请求字段功能时，可以提供字段通配符模式。
在这些情况下，通配符模式除了具体字段外，还将匹配字段别名：
GET trips/_field_caps?fields=route_*,transit_mode
字段说明：
- 别名可以在查询中，聚合和排序字段使用（大部分功能都能支持别名）
- 目标必须是具体字段，而不是对象或其他字段别名
- 在创建别名时，目标字段必须存在
- 如果定义了嵌套对象，则字段别名必须与其目标具有相同的嵌套作用域
- 字段别名只能有一个目标（一个字段仅支持一个别名）
- 更新索引别名或字段别名时不能使用别名
arrays
简介：
ES没有专用的array数据类型，但可存储字符串、数字、一维、多维、对象的数组
字符串数组
[ "one", "two" ]
数字数组
[ 1, 2 ]
多维数组
[ 1, [ 2, 3 ]]
一维数组
[ 1, 2, 3 ]
对象数组
[ { "name": "Mary", "age": 12 }, { "name": "John", "age": 10 }]
不支持混合类型数组
[ 10，"some string"]
PUT my_index/_doc/1
{
"message": "some arrays in this document...",
"tags": [ "elasticsearch", "wow" ],
"lists": [
{
"name": "prog_list",
"description": "programming list"
},
{
"name": "cool_list",
"description": "cool stuff list"
}
]
}
PUT my_index/_doc/2
{
"message": "no arrays in this document...",
"tags": "elasticsearch",
"lists": {
"name": "prog_list",
"description": "programming list"
}
}
GET my_index/_search
{
"query": {
"match": {
"tags": "elasticsearch"
}
}
}
字段说明
- 字段声明时，可声明字符串或其他类型，但可用数组作为存储
- 数组可以包含null值
binary
简介：
接受二进制值作为 Base64编码的字符串。该字段默认情况下不存储，并且不可搜索
PUT my_index
{
"mappings": {
"properties": {
"name": {
"type": "text"
},
"blob": {
"type": "binary"
}
}
}
}
PUT my_index/_doc/1
{
"name": "Some binary blob",
"blob": "U29tZSBiaW5hcnkgYmxvYg=="
}
字段说明
- Base64编码的二进制值不能包含嵌入式换行符\n
boolean
简介：
布尔字段接受JSON true和false值，但也可以接受解释为true或false的字符串
PUT my_index
{
"mappings": {
"properties": {
"is_published": {
"type": "boolean"
}
}
}
}
POST my_index/_doc/1
{
"is_published": "true"
}
GET my_index/_search
{
"query": {
"term": {
"is_published": true
}
}
}
GET my_index/_search
{
"aggs": {
"publish_state": {
"terms": {
"field": "is_published"
}
}
},
"script_fields": {
"is_published": {
"script": {
"lang": "painless",
"source": "doc['is_published'].value"
}
}
}
}
date
简介：
存储日期格式字段
PUT my_index
{
"mappings": {
"properties": {
"date": {
"type": "date",
"format": "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||epoch_millis"
}
}
}
}
PUT my_index/_doc/1
{ "date": "2015-01-01" }
PUT my_index/_doc/2
{ "date": "2015-01-01T12:10:30Z" }
PUT my_index/_doc/3
{ "date": 1420070400001 } //毫秒作为单位
GET my_index/_search
{
"sort": { "date": "asc"}
}
字段说明
- 日期将始终以字符串形式呈现
- 默认格式，是"strict_date_optional_time||epoch_millis"
- strict_date_optional_time是date_optional_time的严格级别，这个严格指的是年份、月份、天必须分别以4位、2位、2位表示，不足两位的话第一位需用0补齐。不满足这个格式的日期字符串是放不进es中的
- epoch_millis约束值必须大于等于Long.MIN_VALUE，小于等于Long.MAX_VALUE
- 仅支持"yyyy-MM-dd"、“yyyyMMdd”、“yyyyMMddHHmmss”、“yyyy-MM-ddTHH:mm:ss”、“yyyy-MM-ddTHH:mm:ss.SSS”、"yyyy-MM-ddTHH:mm:ss.SSSZ"格式
geo_point
简介：
用于记录经纬度的字段
PUT my_index
{
"mappings": {
"properties": {
"location": {
"type": "geo_point"
}
}
}
}
PUT my_index/_doc/1
{
"text": "Geo-point as an object",
"location": {
"lat": 41.12,
"lon": -71.34
}
}
PUT my_index/_doc/2
{
"text": "Geo-point as a string",
"location": "41.12,-71.34"
}
PUT my_index/_doc/3
{
"text": "Geo-point as a geohash",
"location": "drm3btev3e86"
}
PUT my_index/_doc/4
{
"text": "Geo-point as an array",
"location": [ -71.34, 41.12 ]
}
PUT my_index/_doc/5
{
"text": "Geo-point as a WKT POINT primitive",
"location" : "POINT (-71.34 41.12)"
}
GET my_index/_search
{
"query": {
"geo_bounding_box": {
"location": {
"top_left": {
"lat": 42,
"lon": -72
},
"bottom_right": {
"lat": 40,
"lon": -74
}
}
}
}
}
字段说明：
- 不管字符串形式还是数组形式，都是纬度在前，经度在后
- 在一个任意形状的边界内，查找符合规定的经纬度数据
- 按距离对文档进行排序搜索
- 字符串地理位置按排序lat,lon，而数组地理位置按相反的顺序排序：lon,lat
- 一个点可以表示为geohash。Geohash是交错的纬度和经度的位的base32编码的字符串。geohash中的每个字符都会增加5位精度。因此，哈希越长，它越精确。为了进行索引，将目标哈希值转换为纬度-经度对。在此过程中，仅使用前12个字符，因此在geohash中指定超过12个字符不会提高精度。12个字符提供60位，这应该将可能的错误减少到2cm以下
原文：
A point can be expressed as a geohash. Geohashes are base32 encoded strings of the bits of the latitude and longitude interleaved. Each character in a geohash adds additional 5 bits to the precision. So the longer the hash, the more precise it is. For the indexing purposed geohashs are translated into latitude-longitude pairs. During this process only first 12 characters are used, so specifying more than 12 characters in a geohash doesn’t increase the precision. The 12 characters provide 60 bits, which should reduce a possible error to less than 2cm
IP
简介：
ip字段可以索引/存储IPv4或 IPv6地址
PUT my_index
{
"mappings": {
"properties": {
"ip_addr": {
"type": "ip"
}
}
}
}
PUT my_index/_doc/1
{
"ip_addr": "192.168.1.1"
}
GET my_index/_search
{
"query": {
"term": {
"ip_addr": "192.168.0.0/16"
}
}
}
GET my_index/_search
{
"query": {
"term": {
"ip_addr": "2001:db8::/48"
}
}
}
join
简介：
该join数据类型是创建相同的索引文件中的父/子关系的特殊领域
PUT my_index
{
"mappings": {
"properties": {
"my_join_field": {
"type": "join",
"relations": {
"question": "answer"
//父级名称：子级名称
}
}
}
}
}
//父级数据
PUT my_index/_doc/1?refresh
{
"text": "This is a question",
"my_join_field": {
"name": "question"
}
}
//父级数据
PUT my_index/_doc/2?refresh
{
"text": "This is another question",
"my_join_field": {
"name": "question"
}
}
//创建父级数据时，可使用字符串与对象两种方式
PUT my_index/_doc/1?refresh
{
"text": "This is a question",
"my_join_field": "question"
}
//创建父级数据时，可使用字符串与对象两种方式
PUT my_index/_doc/2?refresh
{
"text": "This is another question",
"my_join_field": "question"
}
//子级数据
PUT my_index/_doc/3?routing=1&refresh
{
"text": "This is an answer",
"my_join_field": {
"name": "answer", //子级名称
"parent": "1" //父级ID
}
}
//子级数据
PUT my_index/_doc/4?routing=1&refresh
{
"text": "This is another answer",
"my_join_field": {
"name": "answer",
"parent": "2"
}
}
字段说明：
- 在为子级文档建立索引时，必须在中添加关系的名称以及文档的父级ID
- join每个索引仅允许一个字段映射
- 父文档和子文档必须在同一分片上建立索引。这意味着路由查询在获取，删除或更新 子文档时需要提供相同的值
- 一个父级文档可以有多个子级文档，但只能有一个父级文档
- 可以向现有join字段添加新关系
- 也可以将子级文档添加到现有文档中，但前提是该文档已经是父级文档
- 该join字段使用全局序号来加快连接速度。对分片进行任何更改后，都需要重建全局序号
keyword
简介：
用户储存字符串数据字段，常用于中文IK分词搜索
PUT my_index
//事例一
{
"mappings": {
"properties": {
"tags": {
"type": "keyword"
}
}
}
}
//事例二
{
"mappings": {
"properties": {
"tags": {
"type": "keyword",
"ignore_above": 32766 //用于设置超过设定字符后，不被索引或者存储
}
}
}
}
字段说明：
- 可配合字段排序、聚合搜索、精确匹配使用
数字范围
PUT my_index
{
"mappings": {
"properties": {
"number_of_bytes": {
"type": "integer"
},
"time_in_seconds": {
"type": "float"
},
"price": {
"type": "scaled_float",
"scaling_factor": 100
}
}
}
}
对象类型
简介：对象可以是单一对象也可以是多维对象
PUT my_index/_doc/1
//manager对象内包含着name对象
{
"region": "US",
"manager": {
"age": 30,
"name": {
"first": "John",
"last": "Smith"
}
}
}
//单一对象
{
"region": "US",
"manager.age": 30,
"manager.name.first": "John",
"manager.name.last": "Smith"
}
{
"mappings": {
"properties": {
"region": {
"type": "keyword"
},
"manager": {
"properties": {
"age": { "type": "integer" },
"name": {
"properties": {
"first": { "type": "text" },
"last": { "type": "text" }
}
}
}
}
}
}
}
范围数据类型
PUT range_index
{
"settings": {
"number_of_shards": 2
},
"mappings": {
"properties": {
"expected_attendees": {
"type": "integer_range"
},
"time_frame": {
"type": "date_range",
"format": "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||epoch_millis"
}
}
}
}
PUT range_index/_doc/1?refresh
//更新字段
{
"expected_attendees" : {
"gte" : 10,
"lte" : 20
},
"time_frame" : {
"gte" : "2015-10-31 12:00:00",
"lte" : "2015-11-01"
}
}
//查询数据
GET range_index/_search
{
"query" : {
"term" : {
"expected_attendees" : {
"value": 12
}
}
}
}
//得到结果
{
"took": 13,
"timed_out": false,
"_shards" : {
"total": 2,
"successful": 2,
"skipped" : 0,
"failed": 0
},
"hits" : {
"total" : {
"value": 1,
"relation": "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "range_index",
"_type" : "_doc",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"expected_attendees" : {
"gte" : 10, "lte" : 20
},
"time_frame" : {
"gte" : "2015-10-31 12:00:00", "lte" : "2015-11-01"
}
}
}
]
}
}
//日期查询
GET range_index/_search
{
"query" : {
"range" : {
"time_frame" : {
"gte" : "2015-10-31",
"lte" : "2015-11-01",
"relation" : "within"
}
}
}
}
//得到结果
{
"took": 13,
"timed_out": false,
"_shards" : {
"total": 2,
"successful": 2,
"skipped" : 0,
"failed": 0
},
"hits" : {
"total" : {
"value": 1,
"relation": "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "range_index",
"_type" : "_doc",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"expected_attendees" : {
"gte" : 10, "lte" : 20
},
"time_frame" : {
"gte" : "2015-10-31 12:00:00", "lte" : "2015-11-01"
}
}
}
]
}
}
//IP范围查询
PUT range_index/_mapping
{
"properties": {
"ip_whitelist": {
"type": "ip_range"
}
}
}
//得到结果
PUT range_index/_doc/2
{
"ip_whitelist" : "192.168.0.0/16"
}
等级特征数据类型/Rank features datatype
简介：用于提高快速查询数据的字段类型
PUT my_index
{
"mappings": {
"properties": {
"pagerank": {
"type": "rank_feature"
},
"url_length": {
"type": "rank_feature",
"positive_score_impact": false
}
}
}
}
PUT my_index/_doc/1
{
"pagerank": 8,
"url_length": 22
}
GET my_index/_search
{
"query": {
"rank_feature": {
"field": "pagerank"
}
}
}
//支持小数点
PUT my_index
{
"mappings": {
"properties": {
"topics": {
"type": "rank_features"
}
}
}
}
PUT my_index/_doc/1
{
"topics": {
"politics": 20,
"economics": 50.8
}
}
PUT my_index/_doc/2
{
"topics": {
"politics": 5.2,
"sports": 80.1
}
}
GET my_index/_search
{
"query": {
"rank_feature": {
"field": "topics.politics"
}
}
}
字段说明：
- rank_feature字段仅支持单值字段和严格为正的值。多值字段和负值将被拒绝
- rank_feature字段不支持查询，排序或汇总。它们只能在rank_feature查询中使用
- rank_feature 字段仅保留9个有效位以保持精度，这意味着约0.4％的相对误差
与得分负相关的排名特征应设置 positive_score_impact为false（默认为true）。rank_feature查询将使用它来修改评分公式，以使分数随着要素的值而减少而不是增加。例如，在Web搜索中，URL长度是常用的功能，它与分数负相关
输入时搜索类型
简介：
实时输入时搜索字段
PUT my_index
{
"mappings": {
"properties": {
"my_field": {
"type": "search_as_you_type",
"max_shingle_size ": 3
}
}
}
}
PUT my_index/_doc/1?refresh
{
"my_field": "quick brown fox jump lazy dog"
}
GET my_index/_search
{
"query": {
"multi_match": {
"query": "brown f",
"type": "bool_prefix",
"fields": [
"my_field",
"my_field._2gram",
"my_field._3gram"
]
}
}
}
{
"took" : 44,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 0.8630463,
"hits" : [
{
"_index" : "my_index",
"_type" : "_doc",
"_id" : "1",
"_score" : 0.8630463,
"_source" : {
"my_field" : "quick brown fox jump lazy dog"
}
}
]
}
}
字段说明：
- 搜索位置，匹配项从输入的开头开始
- 搜索位置，匹配项在输入中的任何位置
- max_shingle_size 有效整数范围2-4
text
PUT my_index
{
"mappings": {
"properties": {
"full_name": {
"type": "text"
}
}
}
}
字段说明：
- 全文本（text），一个用于全文本搜索
- 关键字（keyword），用于聚合和排序
令牌计数类型
简介：
类型字段token_count实际上是一个integer接受字符串值，对其进行分析，然后为字符串中的令牌数编制索引的字段
PUT my_index
{
"mappings": {
"properties": {
"name": {
"type": "text",
"fields": {
"length": {
"type": "token_count",
"analyzer": "standard"
}
}
}
}
}
}
PUT my_index/_doc/1
{ "name": "John Smith" }
PUT my_index/_doc/2
{ "name": "Rachel Alice Williams" }
//本次查询仅匹配到文档2
GET my_index/_search
{
"query": {
"term": {
"name.length": 3
}
}
}