ElasticSearch基本查询(Filter查询)ElasticSearch基本查询(Filter查询)

50 阅读 0 评论 33 点赞

我是靠谱客的博主俊逸灯泡，最近开发中收集的这篇文章主要介绍ElasticSearch基本查询(Filter查询)ElasticSearch基本查询(Filter查询)，觉得挺不错的，现在分享给大家，希望可以做个参考。

概述

ElasticSearch基本查询(Filter查询)

1、数据准备

2、简单的过滤查询

3、bool过滤查询

4、范围过滤

5、过滤非空、判断存在

6、过滤器缓存

7、聚合查询

对人工智能感兴趣的同学，可以点击以下链接：

现在人工智能非常火爆，很多朋友都想学，但是一般的教程都是为博硕生准备的，太难看懂了。最近发现了一个非常适合小白入门的教程，不仅通俗易懂而且还很风趣幽默。所以忍不住分享一下给大家。点这里可以跳转到教程。

https://www.cbedai.net/u014646662

filter是不计算相关性的，同时可以cache。因此，filter速度要快于query。

1、数据准备

POST /lib4/items/_bulk
{"index": {"_id": 1}}
{"price": 40,"itemID": "ID100123","title":"successful"}
{"index": {"_id": 2}}
{"price": 50,"itemID": "ID100124","title":"successful"}
{"index": {"_id": 3}}
{"price": 25,"itemID": "ID100124","title":"failed"}
{"index": {"_id": 4}}
{"price": 30,"itemID": "ID100125","title":"failed"}
{"index": {"_id": 5}}
{"price": 40,"itemID": "ID100125","title":"failed"}
{"index": {"_id": 6}}
{"price": null,"itemID": "ID100127,"title":"failed"}

2、简单的过滤查询

GET /lib4/items/_search
{
"post_filter":{
"term":{"price": 40}
}
}
GET /lib4/items/_search
{
"post_filter":{
"terms":{"price":[25,50]}
}
}
GET /lib4/items/_search
{
"post_filter":{
"terms":{"itemID.keyword":["ID100124","ID100123"]}
}
}

查看分词器分析的结果：

GET /lib4/_mapping

{
"lib4": {
"mappings": {
"items": {
"properties": {
"itemID": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"price": {
"type": "long"
},
"title": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
}
}
}
}
}
}

3、bool过滤查询

可以实现组合过滤查询
格式：

{
"bool": {
"must": [],
"should": [],
"must_not": []
}
}

must:必须满足的条件---and
should：可以满足也可以不满足的条件--or
must_not:不需要满足的条件--not
下一篇博客会做更详细的介绍，这里主要是说过滤

GET /lib4/items/_search
{
"post_filter":{
"bool":{
"should":[
{"term": {"itemID.keyword": "ID100124"} },
{"term":{"price":25}}
],
"must_not":{"term":{"price":50}}
}
}
}

嵌套使用bool：


GET /lib4/items/_search
{
"post_filter": {
"bool": {
"should": [
{"term": {"itemID.keyword": "id100123"}},
{
"bool": {
"must": [
{"term": {"price": 40}}
]
}
}
]
}
}
}

4、范围过滤

gt: >
lt: <
gte: >=
lte: <=

get lib4/items/_search
{
"post_filter":{
"range":{
"price":{"gt":20,"lt":50}
}
}
}

5、过滤非空

get lib4/items/_search
{
"query":{
"constant_score": {
"filter": {
"exists": {
"field": "price"
}
}
}
}
}

get lib4/items/_search
{
"query":{
"constant_score": {
"filter": {"exists": {
"field": "price"
}}
}
}
}

6、过滤器缓存

ElasticSearch提供了一种特殊的缓存，即过滤器缓存（filter cache），用来存储过滤器的结果，被缓存的过滤器并不需要消耗过多的内存（因为它们只存储了哪些文档能与过滤器相匹配的相关信息），而且可供后续所有与之相关的查询重复使用，从而极大地提高了查询性能。
注意：ElasticSearch并不是默认缓存所有过滤器，
以下过滤器默认不缓存：

numeric_range、script、geo_bbox、geo_distance、geo_distance_range、geo_polygon、geo_shape、and、or、not

默认是开启缓存的过滤器：
exists,missing,range,term,terms

开启方式：在filter查询语句后边加上

"_catch":true

7、聚合查询

sum、min、max、avg、cardinality:求基数、terms:分组

以求和为例：

GET /lib4/items/_search
{
"size":0,
"aggs": {
"price_sum": { //名字自定义
"sum": {
"field": "price"
}
}
}
}

执行结果

{
"took": 9,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 5,
"max_score": 0,
"hits": []
},
"aggregations": {
"price_sum": {
"value": 185
}
}
}

对那些有游泳兴趣的用户按年龄分组

GET /lib3/user/_search
{
"query": {
"match": {
"interests": "youyong"
}
},
"size": 0,
"aggs":{
"age_group_by":{
"terms": {
"field": "age",
"order": {
"avg_of_age": "desc"
}
},
"aggs": {
"avg_of_age": {
"avg": {
"field": "age"
}
}
}
}
}
}
//数据参见上一篇博客

执行结果如下：

{
"took": 9,
"timed_out": false,
"_shards": {
"total": 3,
"successful": 3,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 4,
"max_score": 0,
"hits": []
},
"aggregations": {
"age_group_by": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": 22,
"doc_count": 1,
"avg_of_age": {
"value": 22
}
},
{
"key": 20,
"doc_count": 2,
"avg_of_age": {
"value": 20
}
},
{
"key": 18,
"doc_count": 1,
"avg_of_age": {
"value": 18
}
}
]
}
}
}