## **mapping参数解析**
官方文档地址：[https://www.elastic.co/guide/en/elasticsearch/reference/6.x/mapping-params.html]()
**1. analyzer**
指定分词器(分析器更合理)，对索引和查询都有效。如下，指定ik分词的配置
（1）定义索引并定义mapping
```
PUT test
{
"mappings": {
"it":{
"properties":{
"name" : {
"type" : "text",
"analyzer" : "ik_smart",
"search_analyzer":"ik_max_word"
}
}
}
}
}
```
（2）插入数据
```
PUT test/it/1
{
"name" : "美国留给伊拉克的是个烂摊子"
}
PUT test/it/2
{
"name" : "中国驻洛杉矶领事馆遭亚裔男子枪击，嫌犯已自首"
}
PUT test/it/3
{
"name" : "中韩渔船冲突调查：韩警平均扣留一艘国渔船"
}
PUT test/it/4
{
"name" : "公安部：各地校车将享受最高路权"
}
```
（3）查询
```
POST test/it/_search
{
"query": {
"match": {
"name": "中国"
}
}
}
```
查询结果：
```
{
"took": 8,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 1,
"max_score": 0.65109104,
"hits": [
{
"_index": "test",
"_type": "it",
"_id": "2",
"_score": 0.65109104,
"_source": {
"name": "中国驻洛杉矶领事馆遭亚裔男子枪击，嫌犯已自首"
}
}
]
}
}
```
**2. normalizer**
normalizer用于解析前的标准化配置，比如把所有的字符转化为小写等。
(1) 创建索引
```
PUT my_index/
{
"settings": {
"analysis": {
"normalizer":{
"my_normalizer":{
"type":"custom",
"char_filter" : [],
"filter" : ["lowercase", "asciifolding"]
}
}
}
},
"mappings": {
"_doc" : {
"properties" : {
"foo" : {
"type": "keyword",
"normalizer": "my_normalizer"
}
}
}
}
}
```
(2) 插入数据
```
PUT my_index/_doc/1
{
"foo": "BÀR"
}
PUT my_index/_doc/2
{
"foo": "bar"
}
PUT my_index/_doc/3
{
"foo": "baz"
}
```
(3) 查询数据
```
GET my_index/_search
{
"query": {
"term": {
"foo": "BAR"
}
}
}
GET my_index/_search
{
"query": {
"match": {
"foo": "BAR"
}
}
}
```
返回结果：
```
{
"took": 3,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 2,
"max_score": 0.2876821,
"hits": [
{
"_index": "my_index",
"_type": "_doc",
"_id": "2",
"_score": 0.2876821,
"_source": {
"foo": "bar"
}
},
{
"_index": "my_index",
"_type": "_doc",
"_id": "1",
"_score": 0.2876821,
"_source": {
"foo": "BÀR"
}
}
]
}
}
```
**3.boost**
通过指定一个boost值来控制每个查询子句的相对权重，该值默认为1。一个大于1的boost会增加该查询子句的相对权重。
(1) 创建索引并插入数据：
```
#创建索引
PUT my_index
{
"mappings": {
"_doc": {
"properties": {
"title": {
"type": "text",
"boost": 2
},
"content": {
"type": "text"
}
}
}
}
}
#插入数据
PUT my_index/_doc/1
{
"title" : "hello world",
"content" : "你好世界"
}
```
(2) 查询：
```
#查询
POST my_index/_search
{
"query": {
"match" : {
"title": {
"query": "quick brown fox"
}
}
}
}
#返回结果：
{
"took": 13,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 1,
"max_score": 1.1507283,
"hits": [
{
"_index": "my_index",
"_type": "_doc",
"_id": "1",
"_score": 1.1507283,
"_source": {
"title": "hello world",
"content": "你好世界"
}
}
]
}
}
```
boost参数被用来增加一个子句的相对权重(当boost大于1时)，或者减小相对权重(当boost介于0到1时)，但是增加或者减小不是线性的。换言之，boost设为2并不会让最终的_score加倍。 相反，新的_score会在适用了boost后被归一化(Normalized)。每种查询都有自己的归一化算法(Normalization Algorithm)。但是能够说一个高的boost值会产生一个高的_score。
**4.coerce**
coerce属性用于清除脏数据，coerce的默认值是true。整型数字5有可能会被写成字符串“5”或者浮点数5.0.coerce属性可以用来清除脏数据：
* 字符串会被强制转换为整数
* 浮点数被强制转换为整数
```
#创建索引
PUT my_index
{
"mappings": {
"_doc": {
"properties": {
"title": {
"type": "text"
},
"content": {
"type": "text"
},
"age" : {
"type" : "integer",
"coerce" : false
}
}
}
}
}
#第一次插入数据
PUT my_index/_doc/1
{
"title" : "hello world",
"content" : "你好世界",
"age" : 5 #注意此处区别
}
#第一次返回结果
{
"_index": "my_index",
"_type": "_doc",
"_id": "1",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"_seq_no": 0,
"_primary_term": 1
}
#第二次插入数据：
PUT my_index/_doc/1
{
"title" : "hello world",
"content" : "你好世界",
"age" : "5" #注意此处区别
}
#第二次返回结果
{
"error": {
"root_cause": [
{
"type": "mapper_parsing_exception",
"reason": "failed to parse [age]"
}
],
"type": "mapper_parsing_exception",
"reason": "failed to parse [age]",
"caused_by": {
"type": "illegal_argument_exception",
"reason": "Integer value passed as String"
}
},
"status": 400
}
```
**5.copy-to**
copy_to属性用于配置自定义的_all字段。换言之，就是多个字段可以合并成一个超级字段。比如，first_name和last_name可以合并为full_name字段。
```
#创建索引
PUT my_index
{
"mappings": {
"_doc": {
"properties": {
"first_name":{
"type" : "text",
"copy_to" : "full_name"
},
"second_name" : {
"type" : "text" ,
"copy_to" : "full_name"
},
"full_name" : {
"type" : "text"
}
}
}
}
}
#插入数据
PUT my_index/_doc/1
{
"first_name" : "hello",
"second_name" : "world"
}
#查询
POST my_index/_search
{
"query": {
"match": {
"full_name": {
"query": "hello world",
"operator": "and"
}
}
}
}
#返回结果
{
"took": 6,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 1,
"max_score": 0.5753642,
"hits": [
{
"_index": "my_index",
"_type": "_doc",
"_id": "1",
"_score": 0.5753642,
"_source": {
"first_name": "hello",
"second_name": "world"
}
}
]
}
}
```
**6.doc_values**
doc_values是为了加快排序、聚合操作，在建立倒排索引的时候，额外增加一个列式存储映射，是一个空间换时间的做法。默认是开启的，对于确定不需要聚合或者排序的字段可以关闭。
```
PUT my_index
{
"mappings": {
"_doc": {
"properties": {
"first_name":{
"type" : "text",
"copy_to" : "full_name"
},
"second_name" : {
"type" : "text" ,
"copy_to" : "full_name",
"doc_values" : false
},
"full_name" : {
"type" : "text"
}
}
}
}
}
```
**7.dynamic**
dynamic属性用于检测新发现的字段（即插入记录是存在字段没有被定义的情况），有三个取值：
* true:新发现的字段添加到映射中。（默认）
* flase:新检测的字段被忽略。必须显式添加新字段。
* strict:如果检测到新字段，就会引发异常并拒绝文档
```
#创建索引
PUT my_index
{
"mappings": {
"_doc": {
"dynamic":"strict",
"properties": {
"first_name":{
"type" : "text",
"copy_to" : "full_name"
},
"second_name" : {
"type" : "text" ,
"copy_to" : "full_name",
"doc_values" : false
},
"full_name" : {
"type" : "text"
}
}
}
}
}
#添加文档，添加不存在的字段
PUT my_index/_doc/1
{
"first_name" : "hello",
"second_name" : "world",
"age" : 10
}
#返回结果
{
"error": {
"root_cause": [
{
"type": "strict_dynamic_mapping_exception",
"reason": "mapping set to strict, dynamic introduction of [age] within [_doc] is not allowed"
}
],
"type": "strict_dynamic_mapping_exception",
"reason": "mapping set to strict, dynamic introduction of [age] within [_doc] is not allowed"
},
"status": 400
}
```
**8.enabled**
ELasticseaech默认会索引所有的字段，enabled设为false的字段，es会跳过字段内容，该字段只能从_source中获取，但是不可搜。而且字段可以是任意类型。
```
#创建索引
PUT my_index
{
"mappings": {
"_doc": {
"dynamic":"strict",
"properties": {
"first_name":{
"type" : "text",
"copy_to" : "full_name"
},
"second_name" : {
"type" : "text" ,
"copy_to" : "full_name",
"doc_values" : false
},
"full_name" : {
"type" : "text"
},
"age":{
"enabled": false
}
}
}
}
}
#插入数据
PUT my_index/_doc/1
{
"first_name" : "hello",
"second_name" : "world",
"age" : 10
}
#查询
POST my_index/_search
{
"query": {
"match": {
"age": {
"query": 10
}
}
}
}
#返回结果
{
"took": 3,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 0,
"max_score": null,
"hits": []
}
}
```
**9.format**
当type(字段类型)为date时指定日期的保存格式。除了使用系统内置的格式还可以使用自己熟悉的格式，例如：yyyy/mm/dd。(格式将在接下来的章节中详细讲解)
**10.ignore_above**
ignore_above用于指定字段索引和存储的长度最大值，超过最大值的会被忽略(不能用于type类型为text的字段中)
```
#添加索引
PUT my_index
{
"mappings": {
"_doc": {
"dynamic":"strict",
"properties": {
"keyword" : {
"type":"keyword",
"ignore_above" : 5
}
}
}
}
}
#添加第一条数据（不超过5个字符）
PUT my_index/_doc/1
{
"keyword" : "hello"
}
#添加第二条数据（超过5个字符）
PUT my_index/_doc/2
{
"keyword" : "hello world"
}
#查询字段
POST my_index/_search
{
"query": {
"match": {
"keyword": {
"query": "hello"
}
}
}
}
#查询结果，超过5个字符的将被忽略
{
"took": 4,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 1,
"max_score": 0.2876821,
"hits": [
{
"_index": "my_index",
"_type": "_doc",
"_id": "1",
"_score": 0.2876821,
"_source": {
"keyword": "hello"
}
}
]
}
}
```
mapping中指定了ignore_above字段的最大长度为5，第一个文档的字段长小于等于5，因此索引成功，第二个超过5，因此不索引
**11.ignore_malformed**
ignore_malformed可以忽略不规则数据。对于账号userid字段，有人可能填写的是 整数类型，也有人填写的是邮件格式。给一个字段索引不合适的数据类型发生异常，导致整个文档索引失败。如果ignore_malformed参数设为true，异常会被忽略，出异常的字段不会被索引，其它字段正常索引。
```
#第一种情况当ignore_malformed为false时
PUT my_index
{
"mappings": {
"_doc": {
"dynamic":"strict",
"properties": {
"age" : {
"type":"integer",
"ignore_malformed" : false
}
}
}
}
}
#插入数据（整型）
PUT my_index/_doc/2
{
"age" : "10"
}
#返回结果插入成功
{
"_index": "my_index",
"_type": "_doc",
"_id": "2",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"_seq_no": 0,
"_primary_term": 1
}
#插入数据（非整形）
PUT my_index/_doc/1
{
"age" : "hello"
}
#返回结果
{
"error": {
"root_cause": [
{
"type": "mapper_parsing_exception",
"reason": "failed to parse [age]"
}
],
"type": "mapper_parsing_exception",
"reason": "failed to parse [age]",
"caused_by": {
"type": "number_format_exception",
"reason": "For input string: \"hello\""
}
},
"status": 400
}
#第二种情况，当ignore_malformed为true时
PUT my_index
{
"mappings": {
"_doc": {
"dynamic":"strict",
"properties": {
"age" : {
"type":"integer",
"ignore_malformed" : true
}
}
}
}
}
#插入整形数据和非整形数据
PUT my_index/_doc/1
{
"age" : "hello"
}
PUT my_index/_doc/2
{
"age" : "10"
}
#均插入成功
{
"_index": "my_index",
"_type": "_doc",
"_id": "2",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"_seq_no": 0,
"_primary_term": 1
}
```
**12.index_options**
用于控制倒排索引记录的内容，有如下四个配置选项
```
PUT my_index
{
"mappings": {
"my_type": {
"properties": {
"text": {
"type": "text",
"index_options": "offsets"
}
}
}
}
}
```
**13.index**
index属性用于指定字段是否索引，不索引也就不可搜索，取值可以为true或者false。
```
PUT my_index
{
"mappings": {
"_doc": {
"dynamic":"strict",
"properties": {
"name" : {
"type":"text",
"index" : false
},
"title" : {
"type" : "text"
}
}
}
}
}
```
**14.null_value**
当字段遇到null时得处理策略，默认为null,即为空，此时es会忽略该值。可以通过设定该值设定字段的默认值。（该属性不能用于type类型为:text的字段下）
```
PUT my_index
{
"mappings": {
"_doc": {
"dynamic":"strict",
"properties": {
"name" : {
"type":"text",
"index" : false
},
"title" : {
"type" : "keyword",
"null_value" : "null"
}
}
}
}
}
```
**15.fields**
fields可以让同一文本有多种不同的索引方式，比如一个String类型的字段，可以使用text类型做全文检索，使用keyword类型做聚合和排序。```
fields可以让同一文本有多种不同的索引方式，比如一个String类型的字段，可以使用text类型做全文检索，使用keyword类型做聚合和排序。```
fields可以让同一文本有多种不同的索引方式，比如一个String类型的字段，可以使用text类型做全文检索，使用keyword类型做聚合和排序。
```
PUT my_index
{
"mappings": {
"my_type": {
"properties": {
"city": {
"type": "text",
"fields": {
"raw": {
"type": "keyword"
}
}
}
}
}
}
}
PUT my_index/my_type/1
{
"city": "New York"
}
PUT my_index/my_type/2
{
"city": "York"
}
GET my_index/_search
{
"query": {
"match": {
"city": "york"
}
},
"sort": {
"city.raw": "asc"
},
"aggs": {
"Cities": {
"terms": {
"field": "city.raw"
}
}
}
}
{
"took": 31,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 2,
"max_score": null,
"hits": [
{
"_index": "my_index",
"_type": "my_type",
"_id": "1",
"_score": null,
"_source": {
"city": "New York"
},
"sort": [
"New York"
]
},
{
"_index": "my_index",
"_type": "my_type",
"_id": "2",
"_score": null,
"_source": {
"city": "York"
},
"sort": [
"York"
]
}
]
},
"aggregations": {
"Cities": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "New York",
"doc_count": 1
},
{
"key": "York",
"doc_count": 1
}
]
}
}
}
