本文基于ES6.4版本,我也是出于学习阶段,对学习内容做个记录,如果文中有错误,请指出。

实验数据:

index:book

type:novel

mappings:

{
"mappings": {
"novel": {
"dynamic": "false",
"properties": {
"word_count": {
"type": "integer"
},
"author": {
"type": "keyword"
},
"title": {
"type": "text"
},
"publish_date": {
"format": "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||epoch_millis",
"type": "date"
}
}
}
}
}

通过put创建索引,使用head可视化界面,数据如下:

Elasticsearch的查询分为:

1、子条件查询:查询特定字段的特定值

Query context

查询过程中,除了判断Document是否满足条件,还会计算出_score表示匹配程度,数值越大,证明匹配程度越高

1、查询全部:/book/novel/_search

"hits": {
"total": 10,
"max_score": 1.0,
"hits": [
{
"_index": "book",
"_type": "novel",
"_id": "5",
"_score": 1.0,
"_source": {
"title": "永夜君王",
"word_count": "110000",
"publish_date": "2015-03-01",
"author": "烟雨江南"
}
},
{
"_index": "book",
"_type": "novel",
"_id": "8",
"_score": 1.0,
"_source": {
"title": "万古令",
"word_count": "110000",
"publish_date": "2015-03-01",
"author": "听奕"
}
},
{
"_index": "book",
"_type": "novel",
"_id": "9",
"_score": 1.0,
"_source": {
"title": "天帝传",
"word_count": "110000",
"publish_date": "2015-03-01",
"author": "飞天鱼"
}
},
{
"_index": "book",
"_type": "novel",
"_id": "10",
"_score": 1.0,
"_source": {
"title": "剑来",
"word_count": "110000",
"publish_date": "2015-03-01",
"author": "烽火戏诸侯"
}
},
{
"_index": "book",
"_type": "novel",
"_id": "2",
"_score": 1.0,
"_source": {
"title": "完美世界",
"word_count": "130000",
"publish_date": "2017-03-01",
"author": "辰东"
}
},
{
"_index": "book",
"_type": "novel",
"_id": "4",
"_score": 1.0,
"_source": {
"title": "民国谍影",
"word_count": "110000",
"publish_date": "2019-03-01",
"author": "寻青藤"
}
},
{
"_index": "book",
"_type": "novel",
"_id": "6",
"_score": 1.0,
"_source": {
"title": "遮天",
"word_count": "110000",
"publish_date": "2015-03-01",
"author": "辰东"
}
},
{
"_index": "book",
"_type": "novel",
"_id": "1",
"_score": 1.0,
"_source": {
"title": "万古神帝",
"word_count": "30000",
"publish_date": "2017-01-01",
"author": "飞天鱼"
}
},
{
"_index": "book",
"_type": "novel",
"_id": "7",
"_score": 1.0,
"_source": {
"title": "圣墟",
"word_count": "110000",
"publish_date": "2015-03-01",
"author": "辰东"
}
},
{
"_index": "book",
"_type": "novel",
"_id": "3",
"_score": 1.0,
"_source": {
"title": "星辰变",
"word_count": "100000",
"publish_date": "2018-03-01",
"author": "我吃西红柿"
}
}
]
}

2、查询id为1的数据:/book/novel/1

{
"_index": "book",
"_type": "novel",
"_id": "1",
"_version": 1,
"found": true,
"_source": {
"title": "万古神帝",
"word_count": "30000",
"publish_date": "2017-01-01",
"author": "飞天鱼"
}
}

3、只查询title和author字段:/1?_source=title,author

{
"_index": "book",
"_type": "novel",
"_id": "1",
"_version": 1,
"found": true,
"_source": {
"author": "飞天鱼",
"title": "万古神帝"
}
}

4、只是显示_source部分:/book/novel/1/_source

{
"title": "万古神帝",
"word_count": "30000",
"publish_date": "2017-01-01",
"author": "飞天鱼"
}

5、筛选单字段查询:/book/novel/_search

{
"query": {
"match": {
"author": "飞天鱼"
}
}
}
"hits": {
"total": 2,
"max_score": 1.2039728,
"hits": [
{
"_index": "book",
"_type": "novel",
"_id": "9",
"_score": 1.2039728,
"_source": {
"title": "天帝传",
"word_count": "110000",
"publish_date": "2015-03-01",
"author": "飞天鱼"
}
},
{
"_index": "book",
"_type": "novel",
"_id": "1",
"_score": 0.6931472,
"_source": {
"title": "万古神帝",
"word_count": "30000",
"publish_date": "2017-01-01",
"author": "飞天鱼"
}
}
]
}

6、limit:我们查询到2条数据,如果我们只想得到第一条数据,可以使用from和size联合查询

{
"query": {
"match": {
"author": "飞天鱼"
}
},
"from": 0,
"size": 1
}
"hits": {
"total": 2,
"max_score": 1.2039728,
"hits": [
{
"_index": "book",
"_type": "novel",
"_id": "9",
"_score": 1.2039728,
"_source": {
"title": "天帝传",
"word_count": "110000",
"publish_date": "2015-03-01",
"author": "飞天鱼"
}
}
]
}
hits.total=2,但是只返回了第一条数据,from为从第几条开始,size我返回的条数
7、order by
这里选择对word_count字段进行倒叙排序
{
"query": {
"match": {
"author": "辰东"
}
},
"sort": [
{
"word_count": {
"order": "desc"
}
}
]
}
"hits": {
"total": 3,
"max_score": null,
"hits": [
{
"_index": "book",
"_type": "novel",
"_id": "2",
"_score": null,
"_source": {
"title": "完美世界",
"word_count": "130000",
"publish_date": "2017-03-01",
"author": "辰东"
},
"sort": [
130000
]
},
{
"_index": "book",
"_type": "novel",
"_id": "6",
"_score": null,
"_source": {
"title": "遮天",
"word_count": "110000",
"publish_date": "2015-03-01",
"author": "辰东"
},
"sort": [
110000
]
},
{
"_index": "book",
"_type": "novel",
"_id": "7",
"_score": null,
"_source": {
"title": "圣墟",
"word_count": "110000",
"publish_date": "2015-03-01",
"author": "辰东"
},
"sort": [
110000
]
}
]
}

8、其余匹配match_phrase

query、match的方式本质上就是模糊查询,而且中文会自动分词到最大粒度,可以看到会查询到只要匹配任意一个字都是可以的

{
"query": {
"match": {
"title": "万古神帝"
}
}
}
"hits": {
"total": 3,
"max_score": 2.439878,
"hits": [
{
"_index": "book",
"_type": "novel",
"_id": "1",
"_score": 2.439878,
"_source": {
"title": "万古神帝",
"word_count": "30000",
"publish_date": "2017-01-01",
"author": "飞天鱼"
}
},
{
"_index": "book",
"_type": "novel",
"_id": "8",
"_score": 2.4079456,
"_source": {
"title": "万古令",
"word_count": "110000",
"publish_date": "2015-03-01",
"author": "听奕"
}
},
{
"_index": "book",
"_type": "novel",
"_id": "9",
"_score": 1.2039728,
"_source": {
"title": "天帝传",
"word_count": "110000",
"publish_date": "2015-03-01",
"author": "飞天鱼"
}
}
]
}

所以这里有了其余匹配match_phrase,结果只有完全包含"万古神帝"的title才可以被查询到

{
"query": {
"match_phrase": {
"title": "万古神帝"
}
}
}
"hits": {
"total": 1,
"max_score": 2.439878,
"hits": [
{
"_index": "book",
"_type": "novel",
"_id": "1",
"_score": 2.439878,
"_source": {
"title": "万古神帝",
"word_count": "30000",
"publish_date": "2017-01-01",
"author": "飞天鱼"
}
}
]
}

9、多条件查询multi_match:查询title或者author包含"万古神帝"的数据

{
"query": {
"multi_match": {
"query": "万古神天",
"fields": ["title","author"]
}
}
}
"hits": {
"total": 4,
"max_score": 2.4079456,
"hits": [
{
"_index": "book",
"_type": "novel",
"_id": "8",
"_score": 2.4079456,
"_source": {
"title": "万古令",
"word_count": "110000",
"publish_date": "2015-03-01",
"author": "听奕"
}
},
{
"_index": "book",
"_type": "novel",
"_id": "1",
"_score": 1.8299085,
"_source": {
"title": "万古神帝",
"word_count": "30000",
"publish_date": "2017-01-01",
"author": "飞天鱼"
}
},
{
"_index": "book",
"_type": "novel",
"_id": "9",
"_score": 1.2039728,
"_source": {
"title": "天帝传",
"word_count": "110000",
"publish_date": "2015-03-01",
"author": "飞天鱼"
}
},
{
"_index": "book",
"_type": "novel",
"_id": "6",
"_score": 1.1727304,
"_source": {
"title": "遮天",
"word_count": "110000",
"publish_date": "2015-03-01",
"author": "辰东"
}
}
]
}

10、语法查询query_string

{
"query": {
"query_string": {
"query": "万古"
}
}
}

这里和match没有区别,query可以使用AND和OR,match的filed也可以,注意这里一定是大写,小写就被当做搜索的内容了

{
"query": {
"query_string": {
"query": "万古 OR 剑来"
}
}
}
{
"query": {
"match": {
"title": "万古 OR 剑来"
}
}
}

指定fields:

{
"query": {
"query_string": {
"query": "万古 OR 剑来 OR 辰东 ",
"fields": ["author","title"]
}
}
}

11、精确匹配term

title为text类型,author为keyword类型,实验发现查询title只有是单个字的时候才能匹配(精确匹配查不到数据),而author必须是精确匹配

例如:title不支持精确匹配,支持模糊查询(而且是单个字才可以,多个字照样查不到数据)

{
"query": {
"term": {
"title": "剑来"
}
}
}

如果只是查询一个字就可以

{
"query": {
"term": {
"title": "来"
}
}
}
"hits": {
"total": 1,
"max_score": 1.3940737,
"hits": [
{
"_index": "book",
"_type": "novel",
"_id": "10",
"_score": 1.3940737,
"_source": {
"title": "剑来",
"word_count": "110000",
"publish_date": "2015-03-01",
"author": "烽火戏诸侯"
}
}
]
}

查询author字段:有三条数据

{
"query": {
"term": {
"author": "辰东"
}
}
}
"hits": [
{
"_index": "book",
"_type": "novel",
"_id": "7",
"_score": 0.6931472,
"_source": {
"title": "圣墟",
"word_count": "110000",
"publish_date": "2015-03-01",
"author": "辰东"
}
},
{
"_index": "book",
"_type": "novel",
"_id": "2",
"_score": 0.47000363,
"_source": {
"title": "完美世界",
"word_count": "130000",
"publish_date": "2017-03-01",
"author": "辰东"
}
},
{
"_index": "book",
"_type": "novel",
"_id": "6",
"_score": 0.47000363,
"_source": {
"title": "遮天",
"word_count": "110000",
"publish_date": "2015-03-01",
"author": "辰东"
}
}
]
}

author不知道模糊查询:下面结果为null

{
"query": {
"term": {
"author": "东"
}
}
}

12、范围查找range:包括integer和日期类型,日期支持now函数,也就是当前日期

{
"query": {
"range": {
"word_count": {
"gt": 110000,
"lte": 130000
}
}
}
}
"hits": {
"total": 1,
"max_score": 1.0,
"hits": [
{
"_index": "book",
"_type": "novel",
"_id": "2",
"_score": 1.0,
"_source": {
"title": "完美世界",
"word_count": "130000",
"publish_date": "2017-03-01",
"author": "辰东"
}
}
]
}

Filter context

查询过程中,只是判断Document是否满足条件,只有yes or no。用来做数据过滤,而且ES还会对结果进行缓存,效率相对query更高一点

{
"query": {
"bool": {
"filter": {
"term": {
"word_count": 130000
}
}
}
}
}
"hits": {
"total": 1,
"max_score": 0.0,
"hits": [
{
"_index": "book",
"_type": "novel",
"_id": "2",
"_score": 0.0,
"_source": {
"title": "完美世界",
"word_count": "130000",
"publish_date": "2017-03-01",
"author": "辰东"
}
}
]
}

2、复合条件查询:组合子条件查询

1、固定分数查询:不支持match,支持filter

{
"query": {
"constant_score": {
"filter": {
"match": {
"title": "天帝传"
}
}
}
}
} {
"query": {
"constant_score": {
"filter": {
"match": {
"title": "天帝传"
}
},
"boost": 2
}
}
}

2、bool查询:

should:就是or的关系

{
"query": {
"bool": {
"should": [
{
"match": {
"author": "辰东"
}
},
{
"match": {
"title": "天帝传"
}
}
]
}
}
}

must:相当于and

{
"query": {
"bool": {
"must": [
{
"match": {
"author": "辰东"
}
},
{
"match": {
"title": "天帝传"
}
}
]
}
}
}

must_not:相当于<>

{
"query": {
"bool": {
"must_not": {
"term": {
"author": "辰东"
}
}
}
}
}

bool查询也可以使用filter:

{
"query": {
"bool": {
"must": [
{
"match": {
"author": "辰东"
}
},
{
"match": {
"title": "天帝传"
}
}
],
"filter": [
{
"term": {
"word_count": 110000
}
}
]
}
}
}

aggregations:

{
"aggs": {
"group_by_author": {
"terms": {
"field": "author"
}
}
}
}
"aggregations": {
"group_by_author": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "辰东",
"doc_count": 3
},
{
"key": "飞天鱼",
"doc_count": 2
},
{
"key": "听奕",
"doc_count": 1
},
{
"key": "寻青藤",
"doc_count": 1
},
{
"key": "我吃西红柿",
"doc_count": 1
},
{
"key": "烟雨江南",
"doc_count": 1
},
{
"key": "烽火戏诸侯",
"doc_count": 1
}
]
}
}

支持多聚合结果:

{
"aggs": {
"group_by_author": {
"terms": {
"field": "author"
}
},
"group_by_word_count": {
"terms": {
"field": "word_count"
}
}
}
}

aggregations除了支持term,还有stats、min、max、avg等

{
"aggs": {
"group_by_author": {
"stats": {
"field": "word_count"
}
}
}
}
"aggregations": {
"group_by_author": {
"count": 10,
"min": 30000.0,
"max": 130000.0,
"avg": 103000.0,
"sum": 1030000.0
}
}

avg:

{
"aggs": {
"group_by_author": {
"avg": {
"field": "word_count"
}
}
}
}

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