1 准备数据
- 建立索引 shop（名字随意）
POST /shop/_mapping
{ "properties": { "id": { "type": "long" }, "age": { "type": "integer" }, "username": { "type": "keyword" }, "nickname": { "type": "text", "analyzer": "ik_max_word" }, "money": { "type": "float" }, "desc": { "type": "text", "analyzer": "ik_max_word" }, "sex": { "type": "byte" }, "birthday": { "type": "date" }, "face": { "type": "text", "index": false } }
}- 录入数据
POST /shop/_doc/1001
{
"id": 1001,
"age": 18,
"username": "imoocAmazing",
"nickname": "慕课网",
"money": 88.8,
"desc": "我在慕课网学习java和前端，学习到了很多知识",
"sex": 0,
"birthday": "1992-12-24",
"face": "https://www.imooc.com/static/img/index/logo.png"
}
POST /shop/_doc/1002
{
"id": 1002,
"age": 19,
"username": "justbuy",
"nickname": "周杰棍",
"money": 77.8,
"desc": "今天上下班都很堵，车流量很大",
"sex": 1,
"birthday": "1993-01-24",
"face": "https://www.imooc.com/static/img/index/logo.png"
}
POST /shop/_doc/1003
{
"id": 1003,
"age": 20,
"username": "bigFace",
"nickname": "飞翔的巨鹰",
"money": 66.8,
"desc": "慕课网团队和导游坐飞机去海外旅游，去了新马泰和欧洲",
"sex": 1,
"birthday": "1996-01-14",
"face": "https://www.imooc.com/static/img/index/logo.png"
}
POST /shop/_doc/1004
{
"id": 1004,
"age": 22,
"username": "flyfish",
"nickname": "水中鱼",
"money": 55.8,
"desc": "昨天在学校的池塘里，看到有很多鱼在游泳，然后就去慕课网上课了",
"sex": 0,
"birthday": "1988-02-14",
"face": "https://www.imooc.com/static/img/index/logo.png"
}
POST /shop/_doc/1005
{
"id": 1005,
"age": 25,
"username": "gotoplay",
"nickname": "ps游戏机",
"money": 155.8,
"desc": "今年生日，女友送了我一台play station游戏机，非常好玩，非常不错",
"sex": 1,
"birthday": "1989-03-14",
"face": "https://www.imooc.com/static/img/index/logo.png"
}
POST /shop/_doc/1006
{
"id": 1006,
"age": 19,
"username": "missimooc",
"nickname": "我叫小慕",
"money": 156.8,
"desc": "我叫凌云慕，今年20岁，是一名律师，我在琦䯲星球做演讲",
"sex": 1,
"birthday": "1993-04-14",
"face": "https://www.imooc.com/static/img/index/logo.png"
}
POST /shop/_doc/1007
{
"id": 1007,
"age": 19,
"username": "msgame",
"nickname": "gamexbox",
"money": 1056.8,
"desc": "明天去进货，最近微软处理很多游戏机，还要买xbox游戏卡带",
"sex": 1,
"birthday": "1985-05-14",
"face": "https://www.imooc.com/static/img/index/logo.png"
}
POST /shop/_doc/1008
{
"id": 1008,
"age": 19,
"username": "muke",
"nickname": "慕学习",
"money": 1056.8,
"desc": "大学毕业后，可以到imooc.com进修",
"sex": 1,
"birthday": "1995-06-14",
"face": "https://www.imooc.com/static/img/index/logo.png"
}
POST /shop/_doc/1009
{
"id": 1009,
"age": 22,
"username": "shaonian",
"nickname": "骚年轮",
"money": 96.8,
"desc": "骚年在大学毕业后，考研究生去了",
"sex": 1,
"birthday": "1998-07-14",
"face": "https://www.imooc.com/static/img/index/logo.png"
}
POST /shop/_doc/1010
{
"id": 1010,
"age": 30,
"username": "tata",
"nickname": "隔壁老王",
"money": 100.8,
"desc": "隔壁老外去国外出差，带给我很多好吃的",
"sex": 1,
"birthday": "1988-07-14",
"face": "https://www.imooc.com/static/img/index/logo.png"
}
POST /shop/_doc/1011
{
"id": 1011,
"age": 31,
"username": "sprder",
"nickname": "皮特帕克",
"money": 180.8,
"desc": "它是一个超级英雄",
"sex": 1,
"birthday": "1989-08-14",
"face": "https://www.imooc.com/static/img/index/logo.png"
}
POST /shop/_doc/1012
{
"id": 1012,
"age": 31,
"username": "super hero",
"nickname": "super hero",
"money": 188.8,
"desc": "BatMan, GreenArrow, SpiderMan, IronMan... are all Super Hero",
"sex": 1,
"birthday": "1980-08-14",
"face": "https://www.imooc.com/static/img/index/logo.png"
}2 使用 QueryString 查询
查询[字段]包含[内容]的文档
GET /shop/_doc/_search?q=desc:慕课网
GET /shop/_doc/_search?q=nickname:慕&q=age:253 DSL
3.1 match - 查询
全文检索
POST /shop/_search
{
"query": {
"match": {
"desc": "慕课网"
}
}
}3.2 exists - 判断某个字段是否存在
exists可以理解为SQL中的exists函数，就是判断是否存在该字段。
POST /shop/_search
{
"query": {
"exists": {
"field": "desc"
}
}
}3.3 match_all - 查询所有与分页
可以查询集群所有索引库的信息，包括一些隐藏索性库的信息。
3.3.1 在索引中查询所有的文档
GET /shop/_doc/_search或者指定返回属性
POST /shop/_doc/_search
{
"query": {
"match_all": {}
},
"_source": ["id", "nickname", "age"]
}- Head 可视化操作
3.3.2 分页查询
默认查询是只有10条记录，可以通过分页来展示
POST /shop/_doc/_search
{
"query": {
"match_all": {}
},
"from": 0,
"size": 10
}
POST /shop/_doc/_search
{
"query": {
"match_all": {}
},
"_source": [
"id",
"nickname",
"age"
],
"from": 5,
"size": 5
}- Head 可视化操作
3.4 term - 精确查询
term主要用于精确匹配哪些值，比如数字，日期，布尔值或 not_analyzed 的字符串(未经分析的文本数据类型)
3.4.1 term精确搜索与match分词搜索
搜索的时候会把用户搜索内容，比如“慕课网强大”作为一整个关键词去搜索，而不会对其进行分词后再搜索
POST /shop/_doc/_search
{
"query": {
"term": {
"desc": "慕课网"
}
}
}
对比
POST /shop/_doc/_search
{
"query": {
"match": {
"desc": "慕课网"
}
}
}- 注：match会对
慕课网慕课网先进行分词（其实就是全文检索），在查询，而term则不会，直接把
作为一个整的词汇去搜索。 - head 可视化操作对比：
3.4.2 terms 多个词语匹配检索
相当于是tag标签查询，比如慕课网的一些课程会打上前端/后端/大数据/就业课这样的标签，可以完全匹配做类似标签的查询
POST /shop/_doc/_search
{
"query": {
"terms": {
"desc": ["慕课网", "学习", "骚年"]
}
}
}3.5 match_phrase
match：分词后只要有匹配就返回，match_phrase：分词结果必须在text字段分词中都包含，而且顺序必须相同，而且必须都是连续的。（搜索比较严格）
slop：允许词语间跳过的数量
POST /shop/_doc/_search
{
"query": {
"match_phrase": {
"desc": {
"query": "大学 毕业 研究生",
"slop": 2
}
}
}
}3.6 match（operator）/ids
3.6.1 match 扩展
- operator
- or：搜索内容分词后，只要存在一个词语匹配就展示结果
- and：搜索内容分词后，都要满足词语匹配
POST /shop/_doc/_search
{
"query": {
"match": {
"desc": "慕课网"
}
}
}
# 等同于
{
"query": {
"match": {
"desc": {
"query": "xbox游戏机",
"operator": "or"
}
}
}
}
# 相当于 select * from shop where desc='xbox' or|and desc='游戏机'- minimum_should_match: 最低匹配精度，至少有[分词后的词语个数]x百分百，得出一个数据值取整。举个例子：当前属性设置为
70，若一个用户查询检索内容分词后有10个词语，那么匹配度按照 10x70%=7，则desc中至少需要有7个词语匹配，就展示；若分词后有8个，则 8x70%=5.6，则desc中至少需要有5个词语匹配，就展示。
minimum_should_match 也能设置具体的数字，表示个数
POST /shop/_doc/_search
{
"query": {
"match": {
"desc": {
"query": "女友生日送我好玩的xbox游戏机",
"minimum_should_match": "60%"
}
}
}
}3.6.2 根据文档主键ids搜索
GET /shop/_doc/1001查询多个
POST /shop/_doc/_search
{
"query": {
"ids": {
"type": "_doc",
"values": ["1001", "1010", "1008"]
}
}
}3.7 multi_match/boost
3.7.1 multi_match - 多字段查询
满足使用match在多个字段中进行查询的需求
POST /shop/_doc/_search
{
"query": {
"multi_match": {
"query": "皮特帕克慕课网",
"fields": ["desc", "nickname"]
}
}
}3.7.2 boost - 权重
权重，为某个字段设置权重，权重越高，文档相关性得分就越高。通畅来说搜索商品名称要比商品简介的权重更高。
POST /shop/_doc/_search
{
"query": {
"multi_match": {
"query": "皮特帕克慕课网",
"fields": ["desc", "nickname^10"]
}
}
}nickname^10 代表搜索提升10倍相关性，也就是说用户搜索的时候其实以这个nickname为主，desc为辅，nickname的匹配相关度当然要提高权重比例了。
3.8 bool - 布尔查询
可以组合多重查询
- must：查询必须匹配搜索条件，譬如 and
- should：查询匹配满足1个以上条件，譬如 or
- must_not：不匹配搜索条件，一个都不要满足
- 实操1：
POST /shop/_doc/_search
{
"query": {
"bool": {
"must": [
{
"multi_match": {
"query": "慕课网",
"fields": ["desc", "nickname"]
}
},
{
"term": {
"sex": 1
}
},
{
"term": {
"birthday": "1996-01-14"
}
}
]
}
}
}
POST /shop/_doc/_search
{
"query": {
"bool": {
"should（must_not）": [
{
"multi_match": {
"query": "学习",
"fields": ["desc", "nickname"]
}
},
{
"match": {
"desc": "游戏"
}
},
{
"term": {
"sex": 0
}
}
]
}
}
}- 实操2：
POST /shop/_doc/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"desc": "慕"
}
},
{
"match": {
"nickname": "慕"
}
}
],
"should": [
{
"match": {
"sex": "0"
}
}
],
"must_not": [
{
"term": {
"birthday": "1992-12-24"
}
}
]
}
}
}- Head 可视化组合查询
- 为指定词语加权
特殊场景下，某些词语可以单独加权，这样可以排得更加靠前。
POST /shop/_doc/_search
{
"query": {
"bool": {
"should": [
{
"match": {
"desc": {
"query": "律师",
"boost": 18
}
}
},
{
"match": {
"desc": {
"query": "进修",
"boost": 2
}
}
}
]
}
}
}3.9 post_filter - 过滤器
对搜索出来的结果进行数据过滤。不会到es库里去搜，不会去计算文档的相关度分数，所以过滤的性能会比较高，过滤器可以和全文搜索结合在一起使用。post_filter元素是一个顶层元素，只会对搜索结果进行过滤。不会计算数据的匹配度相关性分数，不会根据分数去排序，query则相反，会计算分数，也会按照分数去排序。
使用场景：
- query：根据用户搜索条件检索匹配记录
- post_filter：用于查询后，对结果数据的筛选
实操：查询账户金额大于80元，小于160元的用户。并且生日在1998-07-14的用户
- gte：大于等于
- lte：小于等于
- gt：大于
- lt：小于（除此以外还能做其他的match等操作也行）
POST /shop/_doc/_search
{
"query": {
"match": {
"desc": "慕课网游戏"
}
},
"post_filter": {
"range": {
"money": {
"gt": 60,
"lt": 1000
}
}
}
}3.10 sort - 排序
es的排序同sql，可以desc也可以asc。也支持组合排序。
- 实操：
POST /shop/_doc/_search
{
"query": {
"match": {
"desc": "慕课网游戏"
}
},
"post_filter": {
"range": {
"money": {
"gt": 55.8,
"lte": 155.8
}
}
},
"sort": [
{
"age": "desc"
},
{
"money": "desc"
}
]
}- 对文本排序
由于文本会被分词，所以往往要去做排序会报错，通常我们可以为这个字段增加额外的一个附属属性，类型为keyword，用于做排序。
- 创建新的索引
POST /shop2/_mapping
{
"properties": {
"id": {
"type": "long"
},
"nickname": {
"type": "text",
"analyzer": "ik_max_word",
"fields": {
"keyword": {
"type": "keyword"
}
}
}
}
}- 插入数据
POST /shop2/_doc
{
"id": 1001,
"nickname": "美丽的风景"
}
POST /shop2/_doc
{
"id": 1002,
"nickname": "漂亮的小哥哥"
}
POST /shop2/_doc
{
"id": 1003,
"nickname": "飞翔的巨鹰"
}
POST /shop2/_doc
{
"id": 1004,
"nickname": "完美的天空"
}
POST /shop2/_doc
{
"id": 1005,
"nickname": "广阔的海域"
}- 排序
POST /shop2/_doc/_search
{
"sort": [
{
"nickname.keyword": "desc"
}
]
}3.11 highlight - 高亮显示
POST /shop/_doc/_search
{
"query": {
"match": {
"desc": "慕课网"
}
},
"highlight": {
"pre_tags": ["<span>"],
"post_tags": ["</span>"],
"fields": {
"desc": {}
}
}
}3.12 prefix - 前缀
根据前缀去查询
POST /shop/_doc/_search
{
"query": {
"prefix": {
"desc": "imo"
}
}
}3.13 fuzzy - 模糊搜索
模糊搜索，并不是指的sql的模糊搜索，而是用户在进行搜索的时候的打字错误现象，搜索引擎会自动纠正，然后尝试匹配索引库中的数据。
POST /shop/_doc/_search
{
"query": {
"fuzzy": {
"desc": "imoov.coom"
}
}
}
# 或多字段搜索
POST /shop/_doc/_search
{
"query": {
"multi_match": {
"fields": [ "desc", "nickname"],
"query": "imcoc supor",
"fuzziness": "AUTO"
}
}
}
POST /shop/_doc/_search
{
"query": {
"multi_match": {
"fields": [ "desc", "nickname"],
"query": "演说",
"fuzziness": "1"
}
}
}3.14 wildcard - 占位符查询
占位符查询。
- ？：1个字符
- ：1个或多个字符
POST /shop/_doc/_search
{
"query": {
"wildcard": {
"desc": "*oo?"
}
}
}
{
"query": {
"wildcard": {
"desc": "演*"
}
}
}
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