Golang實戰ES

一、ES的安裝
- 下載elasticSearch7.7.0
- docker-compose啟動elasticSearch7.7.0
- 安裝中文分詞器IK
- 注意事項
二、ES的簡單的應用
- 查詢
- - 簡單查詢
  - 復合條件查詢
三、ES的在go中實戰專案運用
- 安裝
- 連接
- 查詢索引
- 添加
- 查詢
- 更新
- 洗掉
- 回傳搜索詞高亮處理

一、ES的安裝

下載elasticSearch7.7.0

docker pull elasticsearch:7.7.0 //下拉鏡像
docker images       //查看鏡像

//創建所需檔案
mkdir -p /mydata/elasticsearch/config
mkdir -p /mydata/elasticsearch/data
echo "http.host: 0.0.0.0">>/mydata/elasticsearch/config/elasticsearch.yml

//檔案夾賦權
chmod -R 777 elasticsearch/

//命令啟動
docker run --name elasticsearch -p 9200:9200 \
 -p 9300:9300 \
 -e "discovery.type=single-node" \
 -e ES_JAVA_OPTS="-Xms64m -Xmx128m" \
  -v /mydata/elasticsearch/config/elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.yml \
 -v /mydata/elasticsearch/data:/usr/share/elasticsearch/data \
 -v /mydata/elasticsearch/plugins:/usr/share/elasticsearch/plugins \
 -d elasticsearch:7.7.0
 
 //引數說明
 --name elasticsearch：將容器命名為 elasticsearch
-p 9200:9200：將容器的9200埠映射到宿主機9200埠
-p 9300:9300：將容器的9300埠映射到宿主機9300埠，目的是集群互相通信
-e "discovery.type=single-node"：單例模式
-e ES_JAVA_OPTS="-Xms64m -Xmx128m"：配置記憶體大小
-v /mydata/elasticsearch/config/elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.yml：將組態檔掛載到宿主機
-v /mydata/elasticsearch/data:/usr/share/elasticsearch/data：將資料檔案夾掛載到宿主機
-v /mydata/elasticsearch/plugins:/usr/share/elasticsearch/plugins：將插件目錄掛載到宿主機(需重啟)
-d elasticsearch:7.7.0：后臺運行容器，并回傳容器ID

docker-compose啟動elasticSearch7.7.0

//docker-compose啟動
version: '2'
services:
  elasticsearch:
    container_name: elasticsearch
    image: elasticsearch:7.7.0
    ports:
      - "9200:9200"
    volumes:
      - /mydata/elasticsearch/config/elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.yml
      - /mydata/elasticsearch/data:/usr/share/elasticsearch/data
      - /mydata/elasticsearch/plugins:/usr/share/elasticsearch/plugins
    environment:
      - "ES_JAVA_OPTS=-Xms64m -Xmx128m"
      - "discovery.type=single-node"
      - "COMPOSE_PROJECT_NAME=elasticsearch-server"
    restart: always

//查看容器
docker ps -a

//驗證是否成功
curl http://192.168.0.50:9200/
//回傳資訊

{
  "name" : "550eca5cf3b2",
  "cluster_name" : "elasticsearch",
  "cluster_uuid" : "1mP9IJU3TUy_C2DZMfKGBg",
  "version" : {
    "number" : "7.7.0",
    "build_flavor" : "default",
    "build_type" : "docker",
    "build_hash" : "81a1e9eda8e6183f5237786246f6dced26a10eaf",
    "build_date" : "2020-05-12T02:01:37.602180Z",
    "build_snapshot" : false,
    "lucene_version" : "8.5.1",
    "minimum_wire_compatibility_version" : "6.8.0",
    "minimum_index_compatibility_version" : "6.0.0-beta1"
  },
  "tagline" : "You Know, for Search"
}

//Docker啟動容器自啟
docker update elasticsearch --restart=always

安裝中文分詞器IK

1.在線安裝
//進入容器
docker exec -it elasticsearch /bin/bash

//在線下載并安裝
./bin/elasticsearch-plugin install https://github.com/medcl/elasticsearch-analysis-ik/releases/download/v6.5.4/elasticsearch-analysis-ik-6.5.4.zip

//進入plugins可以看到IK分詞器已經安裝成功
目錄中有analysis-ik安裝成功

2.離線安裝
//將IK分詞器上傳到/tmp目錄中elasticsearch-analysis-ik-6.5.4.zip

//將壓縮包移動到容器里面
docker cp /tmp/elasticsearch-analysis-ik-6.5.4.zip elasticsearch:/usr/share/elasticsearch/plugins

//進入容器
docker exec -it elasticsearch /bin/bash

//創建目錄
mkdir /usr/share/elasticsearch/plugins/ik

//將檔案壓縮包移動到ik中
mv /usr/share/elasticsearch/plugins/elasticsearch-analysis-ik-6.5.4.zip /usr/share/elasticsearch/plugins/ik

//進入目錄
cd /usr/share/elasticsearch/plugins/ik

//解壓
unzip elasticsearch-analysis-ik-6.5.4.zip

//洗掉壓縮包
rm -rf elasticsearch-analysis-ik-6.5.4.zip

//退出并重啟鏡像
exit
docker restart elasticsearch

注意事項

*** 注意安裝中文分詞器版本一定要和ES的版本號對應，不然會報錯，

報錯資訊如下：
Exception in thread "main" java.lang.IllegalArgumentException: Plugin [analysis-ik] was built for Elasticsearch version 7.0.0 but version 7.7.0 is running
at org.elasticsearch.plugins.PluginsService.verifyCompatibility(PluginsService.java:346)
at org.elasticsearch.plugins.InstallPluginCommand.loadPluginInfo(InstallPluginCommand.java:814)
at org.elasticsearch.plugins.InstallPluginCommand.installPlugin(InstallPluginCommand.java:869)
at org.elasticsearch.plugins.InstallPluginCommand.execute(InstallPluginCommand.java:254)
at org.elasticsearch.plugins.InstallPluginCommand.execute(InstallPluginCommand.java:224)
at org.elasticsearch.cli.EnvironmentAwareCommand.execute(EnvironmentAwareCommand.java:86)
at org.elasticsearch.cli.Command.mainWithoutErrorHandling(Command.java:127)
at org.elasticsearch.cli.MultiCommand.execute(MultiCommand.java:91)
at org.elasticsearch.cli.Command.mainWithoutErrorHandling(Command.java:127)
at org.elasticsearch.cli.Command.main(Command.java:90)
at org.elasticsearch.plugins.PluginCli.main(PluginCli.java:47)

查看對應IK版本號:https://github.com/medcl/elasticsearch-analysis-ik/releases

安裝完成重啟ES
docker restart elasticsearch

IK分詞使用
請求地址POST：http://127.0.0.1/_analyze?pretty
{
"analyzer": "ik_smart",
"text": "中華人民共和國國歌"
}
//回傳內容
{
"tokens": [
    {
        "token": "中華人民共和國",
        "start_offset": 0,
        "end_offset": 7,
        "type": "CN_WORD",
        "position": 0
    },
    {
        "token": "國歌",
        "start_offset": 7,
        "end_offset": 9,
        "type": "CN_WORD",
        "position": 1
    }
]
}

ik_max_word：最細粒度的拆分
ik_smart： 最粗粒度的拆分

二、ES的簡單的應用

查詢

簡單查詢

Query Context 處理判斷檔案是否滿足查詢條件以外，ES還會計算一個_score 來標識匹配程度，判斷目標檔案與查詢條件匹配的有多好，常用查詢針對文本型別資料欄位級別的查詢針對結構化資料，如數字，日期，

Post請求 127.0.0.1/book/_search
//模糊查詢
{
    "query":{
        "match":{
            "author":"瓦力"
        }
    }
}
 //準確查詢
{
    "query":{
        "match_parase":{
            "author":"瓦力"
        }
    }
}
 //多欄位的匹配查詢(查詢autor和title包含瓦力的)
{
    "query":{
        "multi_match":{
            "query":"瓦力",
            "fields":["author", "title"]
        }
    }
}
 //查詢瓦力和很好或則是python
{
    "query":{
        "query_string":{
            "query":"(瓦力 AND 很好）OR python",
        }
    }
}
 //查詢瓦力和很好或則是python（在author和title欄位中）
{
    "query":{
        "query_string":{
            "query":"(瓦力 AND 很好）OR python",
             "fields":["author", "title"]
        }
    }
}
//欄位級別的查詢，查詢字數等于1000的圖書
{
    "query":{
        "term":{
            "word_count": 1000
        }
    }
}
//欄位級別的查詢，查詢字數在1000-2000的圖書有哪些,
//now表示現在時間，gte表示大于等于，gt表示大于
{
    "query":{
        "range":{
            "word_count":{
                "gte":1000,
                "lte":2000
            }
        }
    }
}

Filter Context 子條件查詢在查詢程序中，只判斷該檔案是否滿足條件，只有Yes或No 進行資料過濾，會加到快取中，比query要快

//查詢字數在一千字的書籍
{
    "query": {
        "bool": {
            "filter": {
                "term": {
                    "word_count": 1000
                }
            }
        }
    }
}

復合條件查詢

//POST 127.0.0.1/_search
//全文查詢，但是給出的評分不是一樣的
{
    "query": {
        "match": {
            "title": "ElasticSeach"
        }
    }
}
//固定評分查詢，結果評分全部是1，不支持match
{
    "query": {
        "constant_score": {
            "filter": {
                "match": {
                    "title": "ElasticSearch"
                }
            },
            "boost": 2  //指定分數查詢，
        }
    }
}
//must必須查詢條件
{
    "query": {
        bool": {
            "should": [
            {
                "match": {
                    "author": "瓦力"
                }
            },
            {
                "match":{
                    "title": "ElasticSearch"
                }
            }
            ],
            "filter": [
                {
                    "term":{
                        "word_count": 1000
                    }
                }
            ]
            }
        }
    }
}
//must_not.不滿足條件，篩選處作者沒有瓦力的條件
{
    "query": {
        "must_not": {
            "term": {
                "author": "瓦力"
            }
        }
    }
}

三、ES的在go中實戰專案運用

安裝

1.根據版本安裝依賴（注意go mod 安裝和直接安裝方法不一樣，下面是go mod 安裝）
"github.com/olivere/elastic/v7"

連接

//連接客戶端
client, err := elastic.NewClient(elastic.SetURL(esUrl), elastic.SetSniff(false))
if err != nil {
	// Handle error
	fmt.Println("出錯了")
	panic(err)
}
// Ping the Elasticsearch server to get e.g. the version number
// ping通服務端，并獲得服務端的es版本,本實體的es版本為version 7.6.1
info, code, err := client.Ping(esUrl).Do(ctx)
if err != nil {
	// Handle error
	panic(err)
}
fmt.Println("開始列印版本號")
fmt.Printf("Elasticsearch returned with code>: %d and version %s\n", code, info.Version.Number)
// 獲取版本號的直接API
esVersion, err := client.ElasticsearchVersion(esUrl)
if err != nil {
	panic(err)
}
fmt.Printf("es的版本為%s\n", esVersion)

查詢索引

//連接客戶端
client, err := elastic.NewClient(elastic.SetURL(esUrl), elastic.SetSniff(false))
if err != nil {
	// Handle error
	fmt.Println("出錯了")
	panic(err)
}
// Ping the Elasticsearch server to get e.g. the version number
// ping通服務端，并獲得服務端的es版本,本實體的es版本為version 7.6.1
info, code, err := client.Ping(esUrl).Do(ctx)
if err != nil {
	// Handle error
	panic(err)
}
fmt.Println("開始列印版本號")
fmt.Printf("Elasticsearch returned with code>: %d and version %s\n", code, info.Version.Number)
// 獲取版本號的直接API
esVersion, err := client.ElasticsearchVersion(esUrl)
if err != nil {
	panic(err)
}
fmt.Printf("es的版本為%s\n", esVersion)

添加

//連接客戶端
client, err := elastic.NewClient(elastic.SetURL(esUrl), elastic.SetSniff(false))
if err != nil {
	// Handle error
	fmt.Println("出錯了")
	panic(err)
}
// Ping the Elasticsearch server to get e.g. the version number
// ping通服務端，并獲得服務端的es版本,本實體的es版本為version 7.6.1
info, code, err := client.Ping(esUrl).Do(ctx)
if err != nil {
	// Handle error
	panic(err)
}
fmt.Println("開始列印版本號")
fmt.Printf("Elasticsearch returned with code>: %d and version %s\n", code, info.Version.Number)
// 獲取版本號的直接API
esVersion, err := client.ElasticsearchVersion(esUrl)
if err != nil {
	panic(err)
}
fmt.Printf("es的版本為%s\n", esVersion)

查詢

5.查詢
get1, err := client.Get().Index("user").Id("1").Do(ctx)
if err != nil{
	panic(err)
}
if get1.Found{
	fmt.Printf("Got document %s in version %d from index %s, type %s\n", get1.Id, get1.Version, get1.Index, get1.Type)
}

//將保存的內容保存到磁盤
_, err = client.Flush().Index("user").Do(ctx)
if err != nil {
	panic(err)
}

// 按"term"搜索Search with a term query
termQuery := elastic.NewTermQuery("name", "mike")
searchResult, err := client.Search().
	Index("user").   // 搜索的索引"user"
	Query(termQuery).   // specify the query
	Sort("age", true). //按欄位"age"排序，升序排列
	From(0).Size(10).   // 分頁，單頁顯示10條
	Pretty(true).       // pretty print request and response JSON以json的形式回傳資訊
	Do(ctx)             // 執行
if err != nil {
	// Handle error
	panic(err)
}
fmt.Printf("Query took %d milliseconds\n", searchResult.TookInMillis)// 按"term"搜索Search with a term query
termQuery := elastic.NewTermQuery("name", "mike")
searchResult, err := client.Search().
	Index("user").   // 搜索的索引"user"
	Query(termQuery).   // specify the query
	Sort("age", true). //按欄位"age"排序，升序排列
	From(0).Size(10).   // 分頁，單頁顯示10條
	Pretty(true).       // pretty print request and response JSON以json的形式回傳資訊
	Do(ctx)             // 執行
if err != nil {
	// Handle error
	panic(err)
}
fmt.Printf("Query took %d milliseconds\n", searchResult.TookInMillis)
var user User
//Each是一個簡便函式，此函式忽略了錯誤輸出
for _, item1 := range searchResult.Each(reflect.TypeOf(user)) {
	if u, ok := item1.(User); ok {
		fmt.Printf("Person by %s,age:%d,married:%t,Sex:%s\n", u.Name, u.Age, u.Married,u.Sex) //Person by bob,age:23,married:false,Sex:male
	}
// 搜索檔案方法2
// 使用hits，獲得更詳細的輸出結果
if searchResult.Hits.TotalHits.Value >0{
	fmt.Printf("找到的資料總數是 %d \n", searchResult.Hits.TotalHits.Value)
	for _,hits := range searchResult.Hits.Hits{
		u :=User{}
		err := json.Unmarshal([]byte(hits.Source), &u)
		if err != nil{
			fmt.Println("反序列化失敗",err)
		}
		fmt.Printf("User by %s,age:%d,married:%t,Sex:%s\n", u.Name, u.Age, u.Married,u.Sex)
	}
}else {
	fmt.Println("沒有搜到用戶")
}

更新

// 更新檔案 update
update, err := client.Update().Index("user").Id("1").
	Script(elastic.NewScriptInline("ctx._source.age += params.num").Lang("painless").Param("num", 1)).
	//Upsert(map[string]interface{}{"created": "2020-06-17"}). // 插入未初始化的欄位value
	Do(ctx)
if err != nil {
	// Handle error
	panic(err)
}
fmt.Printf("New version of user %q is now %d\n", update.Id, update.Version)

 // 更新方法2
update,err := client.Update().Index("user").Id("1").
	Script(elastic.NewScriptInline("ctx._source.created=params.date").Lang("painless").Param("date","2020-06-17")).
	Do(ctx)
termQuery := elastic.NewTermQuery("name", "bob")
update,err = client.UpdateByQuery("user").Query(termQuery).
	Script(elastic.NewScriptInline("ctx._source.age += params.num").Lang("painless").Param("num", 1)).
	Do(ctx)
if err != nil{
	panic(err)
}
fmt.Printf("New version of user %q is now %d\n", update.Id, update.Version)
fmt.Println(update)

洗掉

//洗掉檔案
termQuery := elastic.NewTermQuery("name", "mike")
_, err = client.DeleteByQuery().Index("user"). // search in index "user"
	Query(termQuery). // specify the query
	Do(ctx)
if err != nil {
	// Handle error
	panic(err)
}

回傳搜索詞高亮處理

func QueryHeight(search dto.SearchActileDto,client *elastic.Client) (hightmap []bo.SearchActileBo,err error){
	var data []bo.SearchActileBo
	textFild:=elastic.NewHighlighterField("content")
	//idFild:=elastic.NewHighlighterField("id")
	//fild.PreTags("<em>")
	//fild.PostTags("</em>")
	titleFild:=elastic.NewHighlighterField("title")
	titleFild.FragmentSize(350)
	higthFild :=elastic.NewHighlight()
	higthFild.Fields(titleFild)
	higthFild.Fields(textFild)
	//higthFild.Fields(idFild)
	//兩個里面必須有
	//query :=elastic.NewBoolQuery().Must(elastic.NewMatchPhraseQuery("title","css"),elastic.NewMatchPhraseQuery("text","css"))
	query :=elastic.NewBoolQuery().Should(elastic.NewMatchPhraseQuery("title",search.SearchWord),elastic.NewMatchPhraseQuery("content",search.SearchWord))
	res, err := client.Search("article").Query(query).Highlight(higthFild).Size(int(search.Size)).From(int((search.Current - 1) * search.Size)).Do(context.Background())
	if err != nil {
		return nil,err
	}
	//fmt.Println(res.Hits.Hits)
	for _, hit := range res.Hits.Hits {
		aa :=hit.Highlight
		var search bo.SearchActileBo
		search.ContentId = hit.Id
		var qq dto.Article
		json.Unmarshal(hit.Source,&qq)
		search.CreatTime = fmt.Sprintf("%v",qq.CreateTime)
		search.CreateID = qq.CreateBy
		if aa["title"] == nil{
			search.Title=qq.Title
		}else{
			search.Title=aa["title"][0]
		}
		if aa["content"] == nil{
			search.Content=qq.Content
		}else{
			search.Content = aa["content"][0]
		}
		data = append(data, search)
	}
	return data,nil
}

歡迎私信我交流更多ES用法

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