es使用和常用查询（包含多字段聚合查询，实体类方式保存es）_elasticsearch collapse多个字段

1.导入es相关jar包

   <dependency>
                <groupId>org.springframework.data</groupId>
                <artifactId>spring-data-elasticsearch</artifactId>
                <version>4.2.11</version>
            </dependency>
            <dependency>
                <groupId>org.elasticsearch.client</groupId>
                <artifactId>elasticsearch-rest-high-level-client</artifactId>
                <version>7.12.1</version>
   </dependency>

2.增加es配置

elasticsearch:
  hosts: es-service.xiot-v2.svc.cluster.local:port
  storage-strategy: NONE    #分库规则 按日分 DAY, 按月分 MONTH, 按年分 YEAR, 不分 NONE
  shard: 1      #分片数量

3.读取es相关配置 

@Configuration
public class ElasticSearchConfig extends AbstractElasticsearchConfiguration {
 
    @Value("${elasticsearch.hosts}")
    private String HOST;
 
    @Override
    public RestHighLevelClient elasticsearchClient() {
        final ClientConfiguration clientConfiguration = ClientConfiguration.builder()
                .connectedTo(HOST)
                .build();
        return RestClients.create(clientConfiguration).rest();
    }
}

 4.创建es实体类，与es mapping设计一致

@Data
@Document(indexName = "data",createIndex = false)
public class ESData {
    @Id
    @Field(type = FieldType.Text)
    @JSONField(name = "id")
    private String id;
 
    /**
     *  数据时间点: 相对于 UTC-0 1970-1-1 0 点的毫秒数
     */
    @Field(name="ts",type = FieldType.Long)
    @JSONField(name = "ts")
    private Long ts;
 
    //设备说明
    @Field(name= "signature.type",type = FieldType.Keyword)
    @JSONField(name = "signature.type")
    private String signatureType;
}

 5.创建es结构

1.新建index:data
put http://ip:port/data
 
2.新建mapping
put http://ip:port/data/_mapping
 
 
{
 
	"properties": {
 
 
		"ts": {
			"type": "long"
		},
		"name": {
			"type": "keyword"
		},
		"test": {
			"type": "nested",
			"properties": {
				"voltage": {
					"type": "nested",
					"properties": {
						"avg": {
							"type": "keyword"
						},
						"min": {
							"type": "keyword"
						},
						"max": {
							"type": "keyword"
						}
					}
				}
 
			}
 
		}

 6.创建类继承 ElasticsearchRepository 实现通过api保存实体类ESData到es

public interface ESRepository extends ElasticsearchRepository<ESData, String> {
}

 7.保存实体类ESData到es

//1.注入
 @Autowired
 private ESRepository esRepository;
 
public void insertData(){
 
//2.初始化实体类，插入数据
  ESData  data = new ESData();
 
        ....
 
//3.通过实体类保存es
 esRepository.save(data);
 
}
 
 

 8.es查询 多字段匹配查询，分组查询，分组后聚合

@Service
public class EsSearchService {
    @Autowired
    private RestHighLevelClient client;
 
 
/**
先查询 后分组 再统计
*/
 
 public List<HashMap> searchBills(LocalDateTime begin, LocalDateTime end,String boxName){
        //设置查询es的index
        SearchRequest searchRequest = new SearchRequest("data");
        //2.创建 SearchSourceBuilder条件构造。
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        //若时间未传查询过去七日数据
        Long beginTime = null;
        Long endTime = null;
        if(begin==null){
            beginTime =             
        LocalDateTime.now().plusDays(-7).toInstant(ZoneOffset.ofHours(8)).toEpochMilli();
        }else{
            beginTime = begin.toInstant(ZoneOffset.ofHours(8)).toEpochMilli();
        }
        if(end==null){
            endTime = LocalDateTime.now().toInstant(ZoneOffset.ofHours(8)).toEpochMilli()	;
        }else{
            endTime = end.toInstant(ZoneOffset.ofHours(8)).toEpochMilli();
        }
 
        //相当于and查询
        BoolQueryBuilder boolQuery = QueryBuilders.boolQuery();
        boolQuery.filter(QueryBuilders.rangeQuery("ts").from(beginTime).to(endTime));
        if(StringUtils.isNotEmpty(boxName)){
            boolQuery.must(QueryBuilders.termQuery("boxName",boxName));
        }
        searchSourceBuilder.query(boolQuery);
        //去重
        CollapseBuilder collapseBuilder = new CollapseBuilder("ts");
        searchSourceBuilder.collapse(collapseBuilder);
        //多字段分组
        TermsAggregationBuilder aggregation = AggregationBuilders.terms("aggs_group")
                .script(new Script("doc['f1'] +'#'+doc['f2']+'#'+doc['f3']+'#'+doc['f4']+'#'+doc['f5']"))
                .size(Integer.MAX_VALUE) .order(BucketOrder.aggregation("_key", true));
//sum聚合        aggregation.subAggregation(AggregationBuilders.sum("f6").field("sum1"))
                .subAggregation(AggregationBuilders.sum("f7").field("sum2"));
 
        searchSourceBuilder.aggregation(aggregation);
 
        //3.将 SearchSourceBuilder 添加到 SearchRequest中
        searchRequest.source(searchSourceBuilder);
 
        //4.执行查询
        SearchResponse searchResponse = null;
        try {
            searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
        } catch (IOException e) {
            throw new RuntimeException(e);
        }
        //5.解析查询结果
        System.out.println("花费的时长：" + searchResponse.getTook());
        List<HashMap> result=new ArrayList<>();
        if(RestStatus.OK.equals(searchResponse.status())) {
            // 获取聚合结果
            Aggregations aggregations = searchResponse.getAggregations();
            Terms byAggsAggregation = aggregations.get("aggs_group");
            for(Terms.Bucket buck : byAggsAggregation.getBuckets()) {
                HashMap map=new HashMap();
                String[] arr= buck.getKeyAsString().split("#");
                //取子聚合
                ParsedSum sum1 = buck.getAggregations().get("sum1");
                ParsedSum sum2 = buck.getAggregations().get("sum2");
                map.put("f1",arr[0].replace("[","").replace("]",""));
              
                map.put("sum1",sum1.getValue());
                map.put("sum2",sum2.getValue());
           
 
                result.add(map);
            }
        }
 
        return result;
    }
 
 
}