什么是自动补全
随用户输入,给与提示信息,如下图:
ES实现原理
⽤户每输⼊⼀个 字符,就需要即时发送⼀个查询请求到后段查找匹配项。
对性能要求⽐较苛刻。Elasticsearch 采⽤FST,FST 会被 ES 整个加载进内存, 速度很快。
实现方式:
Completion Suggester 实现****
1.定义 Mapping,使⽤ “completion” type
2.索引数据
3.运⾏ “suggest” 查询,得到搜索建议。
例子
1****.****定义 Mapping,使⽤ “completion” type
DELETE inputcompletion
# 设置mapping
PUT inputcompletion
{
"mappings": {
"_doc": {
"properties": {
"input_completion": {
"type": "completion"
}
}
}
}
}
2.索引数据
POST inputcompletion/_doc/_bulk
{ "index" : { } }
{ "input_completion": "elasticsearch 教程"}
{ "index" : { } }
{ "input_completion": "elasticsearch api 中文"}
{ "index" : { } }
{ "input_completion": "elasticsearch"}
3.运⾏ “suggest” 查询,得到搜索建议。
POST inputcompletion/_doc/_search?pretty
{
"size": 0,
"suggest": {
"input-suggester": {
"prefix": "ela",
"completion": {
"field": "input_completion"
}
}
}
}
结果
{
"took": 3,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 0,
"max_score": 0,
"hits": []
},
"suggest": {
"input-suggester": [
{
"text": "ela",
"offset": 0,
"length": 3,
"options": [
{
"text": "elasticsearch",
"_index": "inputcompletion",
"_type": "_doc",
"_id": "ezqix3cBMB6-gr9-ORLt",
"_score": 1,
"_source": {
"input_completion": "elasticsearch"
}
},
{
"text": "elasticsearch api 中文",
"_index": "inputcompletion",
"_type": "_doc",
"_id": "ejqix3cBMB6-gr9-ORLt",
"_score": 1,
"_source": {
"input_completion": "elasticsearch api 中文"
}
},
{
"text": "elasticsearch 教程",
"_index": "inputcompletion",
"_type": "_doc",
"_id": "eTqix3cBMB6-gr9-ORLt",
"_score": 1,
"_source": {
"input_completion": "elasticsearch 教程"
}
}
]
}
]
}
}
Context Suggester带上下文的推荐****
例如:再手机品类下搜索,小米提示小米手机,再食品下,提示真空小米
定义两种类型的 Context
Category – 任意的字符串
Geo – 地理位置信息
实现 Context Suggester 的具体步骤
1.定制⼀个 Mapping 索引数据
2.并且为每个⽂档加⼊ Context 信息
3.结合 Context 进⾏ Suggestion 查询
例子
1. 定制⼀个 Mapping 索引数据
DELETE inputcompletion
PUT inputcompletion
{
"mappings": {
"_doc": {
"properties": {
"input_completion": {
"type": "completion",
"contexts":[{
"type":"category",
"name":"goods_category"
}]
}
}
}
}
}
2.并且为每个⽂档加⼊ Context 信息
POST inputcompletion/_doc
{
"comment":"小米手机",
"input_completion":{
"input":["小米"],
"contexts":{
"goods_category":"手机"
}
}
}
POST inputcompletion/_doc
{
"comment":"真空小米",
"input_completion":{
"input":["小米"],
"contexts":{
"goods_category":"食品"
}
}
}
3. 结合 Context 进⾏ Suggestion 查询
POST inputcompletion/_search
{
"suggest": {
"MY_SUGGESTION": {
"prefix": "小米",
"completion":{
"field":"input_completion",
"contexts":{
"goods_category":"食品"
}
}
}
}
}
结果
{
"took": 3,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 0,
"max_score": 0,
"hits": []
},
"suggest": {
"MY_SUGGESTION": [
{
"text": "小米",
"offset": 0,
"length": 2,
"options": [
{
"text": "小米",
"_index": "inputcompletion",
"_type": "_doc",
"_id": "bjqgx3cBMB6-gr9-vBL2",
"_score": 1,
"_source": {
"comment": "真空小米",
"input_completion": {
"input": [
"小米"
],
"contexts": {
"goods_category": "食品"
}
}
},
"contexts": {
"goods_category": [
"食品"
]
}
}
]
}
]
}
}
参考
https://www.elastic.co/guide/en/elasticsearch/reference/7.1/search-suggesters-completion.html
https://www.elastic.co/guide/en/elasticsearch/reference/7.1/suggester-context.html