索引(Indexing)文档
存储数据到ES的操作称为索引(indexing)。一个ES集群可以包含多个索引(indices)，每个索引包含多个类型(types)，每个类型可以存储多个文档(documents)，每个文档那个包含多个字段(fields)。
index vs index vs index
ES术语中有多个index出现，这里做一下词义辨析。
Index (noun): 做名词时，类似与关系性数据库的数据库概念，存储着相关的文档。复数形式为indices或indexesIndex (verb): To index a document is to store a document in an index (noun) so that it can be retrieved and queried. It is much like the INSERT keyword in SQL except that, if the document already exists, the new document would replace the old.Inverted index: 倒排索引，详情参见官方文档: https://www.elastic.co/guide/en/elasticsearch/guide/current/inverted-index.html
下面的范例将在megacorp这个index的employee类型存储文档:
PUT /megacorp/employee/1
{
"first_name" : "John",
"last_name" : "Smith",
"age" : 25,
"about" : "I love to go rock climbing",
"interests": [ "sports", "music" ]
}
/megacorp/employee/1包含了三个信息:
megacorp: The index nameemployee: The type name1: The ID of this particular employee
ES会尝试解析这个json文档，猜测字段类型之后进行索引。
添加更多的文档:
PUT /megacorp/employee/2
{
"first_name" : "Jane",
"last_name" : "Smith",
"age" : 32,
"about" : "I like to collect rock albums",
"interests": [ "music" ]
}
PUT /megacorp/employee/3
{
"first_name" : "Douglas",
"last_name" : "Fir",
"age" : 35,
"about": "I like to build cabinets",
"interests": [ "forestry" ]
}
取出文档
GET /megacorp/employee/1
{
"_index" : "megacorp",
"_type" : "employee",
"_id" : "1",
"_version" : 1,
"found" : true,
"_source" : {
"first_name" : "John",
"last_name" : "Smith",
"age" : 25,
"about" : "I love to go rock climbing",
"interests": [ "sports", "music" ]
}
}
使用GET方法请求文档的地址即可，返回的数据中包含一些元数据，同时，原始存储文档将会在_source这个字段中。
TIP: 把
PUT换成GET就可以取出对应的数据，还可以用DELETE删除指定文档，HEAD方法可以判断文档是否存在，想要替换文档，只需要再用PUT方法即可
搜索文档
GET方法可以简单直接得到一个具体的文档，当我们想做简单的搜索时，使用以下请求:
GET /megacorp/employee/_search
{
"took": 6,
"timed_out": false,
"_shards": { ... },
"hits": {
"total": 3,
"max_score": 1,
"hits": [
{
"_index": "megacorp",
"_type": "employee",
"_id": "3",
"_score": 1,
"_source": {
"first_name": "Douglas",
"last_name": "Fir",
"age": 35,
"about": "I like to build cabinets",
"interests": [ "forestry" ]
}
},
{
"_index": "megacorp",
"_type": "employee",
"_id": "1",
"_score": 1,
"_source": {
"first_name": "John",
"last_name": "Smith",
"age": 25,
"about": "I love to go rock climbing",
"interests": [ "sports", "music" ]
}
},
{
"_index": "megacorp",
"_type": "employee",
"_id": "2",
"_score": 1,
"_source": {
"first_name": "Jane",
"last_name": "Smith",
"age": 32,
"about": "I like to collect rock albums",
"interests": [ "music" ]
}
}
]
}
}
和获取一个具体的文档类似，最后不用ID，而是换成了_search这个endpoint。搜索的结果包含在hits这个数组中。默认情况下，搜索只会返回前10个结果。
通过追加q=参数，可以添加简单查询条件:
GET /megacorp/employee/_search?q=last_name:Smith
{
...
"hits": {
"total": 2,
"max_score": 0.30685282,
"hits": [
{
...
"_source": {
"first_name": "John",
"last_name": "Smith",
"age": 25,
"about": "I love to go rock climbing",
"interests": [ "sports", "music" ]
}
},
{
...
"_source": {
"first_name": "Jane",
"last_name": "Smith",
"age": 32,
"about": "I like to collect rock albums",
"interests": [ "music" ]
}
}
]
}
}
更多关于Search Lite的语法与限制，请参考官方文档: https://www.elastic.co/guide/en/elasticsearch/guide/current/search-lite.html#query-string-query
Search with Query DSL
Search Lite便于命令行下进行快速查找，但是功能有限。ES提供了一个更强大，更灵活的Query DSL。
GET /megacorp/employee/_search
{
"query" : {
"match" : {
"last_name" : "Smith"
}
}
}
更复杂的查询
查询年龄在30岁以上的员工:
GET /megacorp/employee/_search
{
"query" : {
"filtered" : {
"filter" : {
"range" : {
"age" : { "gt" : 30 }
}
},
"query" : {
"match" : {
"last_name" : "smith"
}
}
}
}
}
返回结果:
{
...
"hits": {
"total": 1,
"max_score": 0.30685282,
"hits": [
{
...
"_source": {
"first_name": "Jane",
"last_name": "Smith",
"age": 32,
"about": "I like to collect rock albums",
"interests": [ "music" ]
}
}
]
}
}
全文搜索(Full-Text Search)
GET /megacorp/employee/_search
{
"query" : {
"match" : {
"about" : "rock climbing"
}
}
}
{
...
"hits": {
"total": 2,
"max_score": 0.16273327,
"hits": [
{
...
"_score": 0.16273327,
"_source": {
"first_name": "John",
"last_name": "Smith",
"age": 25,
"about": "I love to go rock climbing",
"interests": [ "sports", "music" ]
}
},
{
...
"_score": 0.016878016,
"_source": {
"first_name": "Jane",
"last_name": "Smith",
"age": 32,
"about": "I like to collect rock albums",
"interests": [ "music" ]
}
}
]
}
}
全文检索会返回一个
_score字段，返回一个分数。默认按照得分由高到低排序
短语检索(Phrase Search)
和全文检索相比，短语检索是精确匹配。
GET /megacorp/employee/_search
{
"query" : {
"match_phrase" : {
"about" : "rock climbing"
}
}
}
{
...
"hits": {
"total": 1,
"max_score": 0.23013961,
"hits": [
{
...
"_score": 0.23013961,
"_source": {
"first_name": "John",
"last_name": "Smith",
"age": 25,
"about": "I love to go rock climbing",
"interests": [ "sports", "music" ]
}
}
]
}
}
高亮搜索结果
查询条件添加一个highlight参数即可，会将ES匹配到的结果以<em></em>标签高亮显示出来。
GET /megacorp/employee/_search
{
"query" : {
"match_phrase" : {
"about" : "rock climbing"
}
},
"highlight": {
"fields" : {
"about" : {}
}
}
}
{
...
"hits": {
"total": 1,
"max_score": 0.23013961,
"hits": [
{
...
"_score": 0.23013961,
"_source": {
"first_name": "John",
"last_name": "Smith",
"age": 25,
"about": "I love to go rock climbing",
"interests": [ "sports", "music" ]
},
"highlight": {
"about": [
"I love to go <em>rock</em> <em>climbing</em>"
]
}
}
]
}
}
更多详情参考官方文档: https://www.elastic.co/guide/en/elasticsearch/reference/current/search-request-highlighting.html