SpringCloud分布式搜索引擎、数据聚合、ES和MQ的结合使用、ES集群的问题

目录

数据聚合

聚合的分类

​编辑 DSL实现Bucket聚合

​编辑

 DSL实现Metrics聚合​编辑

RestAPI实现聚合

 对接前端接口​编辑

 自定义分词器​编辑

Completion suggester查询

Completion suggester查询

酒店数据自动补全

实现酒店搜索框界面输入框的自动补全

 数据同步问题分析​编辑

同步问题分析

数据同步问题分析

数据问题分析

利用 MQ实现mysql与elasticearch数据同步

ES集群机构

ES集群的节点角色

ES集群的脑裂

ES集群的分布式存储

ES集群的分布式存储

ES集群的分布式查询

ES集群的故障转移

数据聚合

聚合的分类

 DSL实现Bucket聚合

#聚合功能
GET /hotel/_search
{
  "size": 0,
  "aggs": {
    "brandAgg": {
      "terms": {
        "field": "brand",
        "size": 20
    
      }
    }
  }
}

#聚合功能,自定义排序规则
GET /hotel/_search
{
  "size": 0,
  "aggs": {
    "brandAgg": {
      "terms": {
        "field": "brand",
        "size": 20,
        "order": {
          "_count": "asc"
        }
      }
    }
  }
}

#聚合功能，限定聚合范围
GET /hotel/_search
{
  "query": {
    "range": {
      "price": {
        "lte": 200
      }
    }
  }, 
  "size": 0,
  "aggs": {
    "brandAgg": {
      "terms": {
        "field": "brand",
        "size": 20
    
      }
    }
  }
}

 DSL实现Metrics聚合

嵌套聚合metric
GET /hotel/_search
{
  "size": 0,
  "aggs": {
    "brandAgg": {
      "terms": {
        "field": "brand",
        "size": 20,
        "order": {
          "scoreAgg.avg": "desc"
        }
      },
      "aggs": {
        "scoreAgg": {
          "stats": {
            "field": "score"
          }
        }
      }
    }
  }
}

RestAPI实现聚合

@Override
    public Map<String, List<String>> filters() {
        try {
            //1.准备Request
            SearchRequest request = new SearchRequest("hotel");
            //2.准备DSL
            //2.1设置size
            request.source().size(0);
            //2.2 聚合
            buildAggregation(request);
            //3.发出请求
            SearchResponse response = client.search(request, RequestOptions.DEFAULT);

            //4.解析结果
            Map<String, List<String>> result = new HashMap<>();
            Aggregations aggregations = response.getAggregations();
            //TODO 根据品牌名称，获取品牌结果
            List<String> brandList = getAggByName(aggregations,"brandAgg");
            result.put("brand",brandList);

            //TODO 根据品牌名称，获取品牌结果
            List<String> cityList = getAggByName(aggregations,"cityAgg");
            result.put("city",cityList);

            //TODO 根据品牌名称，获取品牌结果
            List<String> starList = getAggByName(aggregations,"starAgg");
            result.put("starName",starList);

            return result;
        }
        catch (IOException e) {
            throw new RuntimeException(e);
        }
    }

    private List<String> getAggByName(Aggregations aggregations,String aggName) {
        //4.1根据聚合名称获取聚合结果
        Terms brandTerms = aggregations.get(aggName);
        //4.2获取buckets
        List<? extends Terms.Bucket> buckets = brandTerms.getBuckets();
        //4.3遍历
        List<String> brandList = new ArrayList<>();
        for ( Terms.Bucket bucket : buckets ) {
            String key = bucket.getKeyAsString();
//            System.out.println(key);
            brandList.add(key);

        }
        return brandList;
    }

 对接前端接口

POST /_analyze
{
  "text": ["如家酒店还不错"],
  "analyzer": "pinyin"
  
}

 自定义分词器

POST /test2/_analyze
{
  "text": ["如家酒店还不错"],
  "analyzer": "my_analyzer"
  
}

// 自定义拼音分词器
PUT /test2
{
  "settings": {
    "analysis": {
      "analyzer": { 
        "my_analyzer": { 
          "tokenizer": "ik_max_word",
          "filter": "py"
        }
      },
      "filter": {
        "py": { 
          "type": "pinyin",
          "keep_full_pinyin": false,
          "keep_joined_full_pinyin": true,
          "keep_original": true,
          "limit_first_letter_length": 16,
          "remove_duplicated_term": true,
          "none_chinese_pinyin_tokenize": false
        }
      }
    }
  },
  "mappings": {
    "properties": {
      "name":{
        "type": "text",
        "analyzer": "my_analyzer"
      }
    }
  }
}

Completion suggester查询

Completion suggester查询

// 自动补全的索引库
PUT test
{
  "mappings": {
    "properties": {
      "title":{
        "type": "completion"
      }
    }
  }
}
// 示例数据
POST test/_doc
{
  "title": ["Sony", "WH-1000XM3"]
}
POST test/_doc
{
  "title": ["SK-II", "PITERA"]
}
POST test/_doc
{
  "title": ["Nintendo", "switch"]
}

// 自动补全查询
POST /test/_search
{
  "suggest": {
    "title_suggest": {
      "text": "s", // 关键字
      "completion": {
        "field": "title", // 补全字段
        "skip_duplicates": true, // 跳过重复的
        "size": 10 // 获取前10条结果
      }
    }
  }
}

酒店数据自动补全

#酒店数据索引库
GET /hotel/_mapping
DELETE /hotel
#酒店数据索引库
PUT /hotel
{
  "settings": {
    "analysis": {
      "analyzer": {
        "text_anlyzer": {
          "tokenizer": "ik_max_word",
          "filter": "py"
        },
        "completion_analyzer": {
          "tokenizer": "keyword",
          "filter": "py"
        }
      },
      "filter": {
        "py": {
          "type": "pinyin",
          "keep_full_pinyin": false,
          "keep_joined_full_pinyin": true,
          "keep_original": true,
          "limit_first_letter_length": 16,
          "remove_duplicated_term": true,
          "none_chinese_pinyin_tokenize": false
        }
      }
    }
  },
  "mappings": {
    "properties": {
      "id":{
        "type": "keyword"
      },
      "name":{
        "type": "text",
        "analyzer": "text_anlyzer",
        "search_analyzer": "ik_smart",
        "copy_to": "all"
      },
      "address":{
        "type": "keyword",
        "index": false
      },
      "price":{
        "type": "integer"
      },
      "score":{
        "type": "integer"
      },
      "brand":{
        "type": "keyword",
        "copy_to": "all"
      },
      "city":{
        "type": "keyword"
      },
      "starName":{
        "type": "keyword"
      },
      "business":{
        "type": "keyword",
        "copy_to": "all"
      },
      "location":{
        "type": "geo_point"
      },
      "pic":{
        "type": "keyword",
        "index": false
      },
      "all":{
        "type": "text",
        "analyzer": "text_anlyzer",
        "search_analyzer": "ik_smart"
      },
      "suggestion":{
          "type": "completion",
          "analyzer": "completion_analyzer"
      }
    }
  }
}

GET /hotel/_search
{
  "query": {
    "match_all": {}
  }
}

GET /hotel/_search
{
  "suggest": {
    "suggestions": {
      "text":"sd",
      "completion":{
        "field":"suggestion",
        "skip_duplicates": true, 
        "size": 10 
      }
    }
  }
}

RestAPI实现自动补全

@Test
    void testSuggest() throws IOException {
        //1、准备Request
        SearchRequest request = new SearchRequest("hotel");
        //2.准备DSL
        request.source().suggest(new SuggestBuilder().addSuggestion(
                "suggestions",
                SuggestBuilders.completionSuggestion("suggestion")
                .prefix("hz")
                .skipDuplicates(true)
                .size(10)
        ));
        //3、发起请求
        SearchResponse response = client.search(request, RequestOptions.DEFAULT);

        //4、解析结果
        Suggest suggest = response.getSuggest();
        //4.1根据补全查询名称，获取补全结果
         CompletionSuggestion suggestions = suggest.getSuggestion("suggestions");
        ///4.2获取options
         List<CompletionSuggestion.Entry.Option> options = suggestions.getOptions();
        //4.3遍历
        for ( CompletionSuggestion.Entry.Option option : options ) {
            String text = option.getText().toString();
            System.out.println("text = " + text);
        }
    }

实现酒店搜索框界面输入框的自动补全

 数据同步问题分析

同步问题分析

数据同步问题分析

数据问题分析

利用 MQ实现mysql与elasticearch数据同步

@Configuration
public class MqConfig {
    @Bean
    public TopicExchange topicExchange(){
        return new TopicExchange(MqConstants.HOTEL_EXCHANGE,true,false);
    }

    @Bean
    public Queue insertQueue(){
        return new Queue(MqConstants.HOTEL_INSERT_QUEUE,true);
    }

    @Bean
    public Queue deleteQueue(){
        return new Queue(MqConstants.HOTEL_DELETE_QUEUE,true);
    }

    @Bean
    public Binding insertQueueBinding(){
        return BindingBuilder.bind(insertQueue()).to(topicExchange()).with(MqConstants.HOTEL_INSERT_KEY);
    }

    @Bean
    public Binding deleteQueueBinding(){
        return BindingBuilder.bind(deleteQueue()).to(topicExchange()).with(MqConstants.HOTEL_DELETE_KEY);
    }

}

@Component
public class HotelListener {
    @Autowired
    private IHotelService hotelService;
    /**
     * 监听酒店新增或修改的业务
     * @param id 酒店id
     */
    @RabbitListener(queues = MqConstants.HOTEL_INSERT_QUEUE)
    public void listenHotelInsertOrUpdate(Long id){

        hotelService.insertById(id);
    }

    /**
     * 监听酒店删除业务
     * @param id 酒店id
     */
    @RabbitListener(queues = MqConstants.HOTEL_DELETE_QUEUE)
    public void listenHotelDelete(Long id){
        hotelService.deleteById(id);
    }
}

   @PutMapping()
    public void updateById(@RequestBody Hotel hotel){
        if (hotel.getId() == null) {
            throw new InvalidParameterException("id不能为空");
        }
        hotelService.updateById(hotel);
        rabbitTemplate.convertAndSend(
                MqConstants.HOTEL_EXCHANGE,
                MqConstants.HOTEL_INSERT_KEY,
                hotel.getId());
    }

    @DeleteMapping("/{id}")
    public void deleteById(@PathVariable("id") Long id) {
        hotelService.removeById(id);
        rabbitTemplate.convertAndSend(
                MqConstants.HOTEL_EXCHANGE,
                MqConstants.HOTEL_DELETE_KEY,
                id);
    }

ES集群机构

ES集群的节点角色

ES集群的分布式查询

ES集群的脑裂

ES集群的分布式存储

ES集群的分布式存储

ES集群的分布式查询

ES集群的故障转移

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