ElasticSearch 集成 Spring 之 ElasticsearchRestTemplate 示例

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ElasticsearchRestTemplate

ElasticsearchRestTemplate 是 spring-data-elasticsearch 项目中的一个类，和其他 spring 项目中的 template 类似。

引入依赖

<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-data-elasticsearch</artifactId>
</dependency>

操作方法

Spring Data ElasticSearch 有下边这几种方法操作 ElasticSearch：

  • ElasticsearchRepository（传统的方法，可以使用）
  • ElasticsearchRestTemplate（推荐使用。基于 RestHighLevelClient）
  • ElasticsearchTemplate（ES7 中废弃，不建议使用。基于 TransportClient）
  • RestHighLevelClient（推荐度低于 ElasticsearchRestTemplate，因为 API 不够高级）
  • TransportClient（ES7 中废弃，不建议使用）

使用 ElasticsearchRest

  1. 参数配置：

    elasticsearch.address=127.0.0.1:9200

  2. 配置引入：

    import org.elasticsearch.client.RestHighLevelClient;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.data.elasticsearch.client.ClientConfiguration;
import org.springframework.data.elasticsearch.client.RestClients;
import org.springframework.data.elasticsearch.core.ElasticsearchRestTemplate;

@Configuration
public class ElasticSearchConfig {

    @Value("${elasticsearch.address}")
    private String elasticSearchAddress;

    @Bean
    RestHighLevelClient elasticsearchClient() {
        final ClientConfiguration configuration = ClientConfiguration.builder()
                .connectedTo(elasticSearchAddress)
                .build();
        RestHighLevelClient client = RestClients.create(configuration).rest();
        return client;
    }

    @Bean
    ElasticsearchRestTemplate elasticsearchTemplate() {
        return new ElasticsearchRestTemplate(elasticsearchClient());
    }
}

    或者：

    @Bean
RestHighLevelClient elasticsearchHighLevelClient() {
    RestHighLevelClient client=new RestHighLevelClient(
            RestClient.builder(
                    new HttpHost("127.0.0.1", 9200, "http")
            )
    );
    return client;
}

  3. 使用：

    @Autowired
ElasticsearchRestTemplate elasticsearchTemplate;

索引示例

创建索引

Map<String, Object> settings = new HashMap<>();
settings.put("index.number_of_replicas", "30");
boolean createResult = elasticsearchTemplate.createIndex(clazz,settings);

刷新 Mapping：

elasticsearchTemplate.putMapping(clazz);
elasticsearchTemplate.refresh(clazz);

虽然可以正常创建索引，但会提示 putMapping 和 refresh 方法过期，此时可以使用：

IndexOperations createResult = elasticsearchTemplate.indexOps(clazz);
boolean create = createResult.create();
boolean putMapping = createResult.putMapping();

删除索引

elasticsearchTemplate.deleteIndex(clazz);

或者：

elasticsearchTemplate.indexOps(clazz).delete();

查看索引是否存在

elasticsearchTemplate.indexExists(indexName);

或者：

elasticsearchTemplate.indexOps(clazz).exists();

获取索引 Mapping

IndexOperations createResult = elasticsearchTemplate.indexOps(clazz);
return createResult.createMapping().toJson();

数据示例

新增数据

List<IndexQuery> queries = new ArrayList<IndexQuery>();
for(Person test:testList) {
    IndexQuery indexQuery = new IndexQueryBuilder().withId(test.getId()).withObject(test).build();
    queries.add(indexQuery);
}
elasticsearchTemplate.bulkIndex(queries, Person.class);

查询数据

GetQuery query = new GetQuery(id);
Person info = elasticsearchTemplate.queryForObject(query, Person.class);

聚合数据

简化版：

NativeSearchQuery query = new NativeSearchQueryBuilder()
        .addAggregation(AggregationBuilders.terms("agg_count").field("module.keyword"))
        .build();

SearchHits<PhishingLog> searchHits = elasticsearchTemplate.search(query, PhishingLog.class);
//取出聚合结果
Aggregations aggregations = searchHits.getAggregations();
Terms terms = (Terms) aggregations.asMap().get("agg_count");

for (Terms.Bucket bucket : terms.getBuckets()) {
    String keyAsString = bucket.getKeyAsString();   // 聚合字段列的值
    long docCount = bucket.getDocCount();           // 聚合字段对应的数量
    System.out.println(keyAsString + " " + docCount);
}

详细版：

需要格外注意类型转换，如 ParsedStringTerms、ParsedLongTerms 等。

// 关键词条件筛选
BoolQueryBuilder bool = new BoolQueryBuilder();
bool.must(QueryBuilders.rangeQuery("@timestamp").from(start.getTime()));
bool.must(QueryBuilders.rangeQuery("@timestamp").to(end.getTime()));

// 分组。terms分组名称、field分组字段、size分组数量
TermsAggregationBuilder aggregationBuilderGroupBy = AggregationBuilders.terms("agg_count").field("module.keyword").size(200);

// 组合查询
NativeSearchQuery searchQuery = new NativeSearchQueryBuilder().addAggregation(aggregationBuilderGroupBy).withQuery(bool).build();

// 查询。实体类上需要有Doucment注解
SearchHits<PhishingLog> searchHits = elasticsearchTemplate.search(searchQuery, PhishingLog.class);

// 解析
Aggregations aggPage = searchHits.getAggregations();
Aggregation aggregation = aggPage.get("agg_count");
// 因为是利用String类型字段来进行的term聚合，所以结果要强转为 ParsedStringTerms 类型
List<? extends Terms.Bucket> buckets = ((ParsedStringTerms) aggregation).getBuckets();
int total = buckets.size();
for (int index = 0; index < total; index++) {
    Terms.Bucket bucket = buckets.get(index);
    ModuleDto dto = new ModuleDto();
    dto.setName(bucket.getKeyAsString());
    if(searchLevel) {
        ParsedStringTerms aggregationsTemp = bucket.getAggregations().get("get_level");
        ParsedLongTerms aggregationsTemp2 = bucket.getAggregations().get("get_time");
        for (Terms.Bucket levelBucket : aggregationsTemp.getBuckets()) {
            if("error".equalsIgnoreCase(levelBucket.getKeyAsString())) {
                // 这个 getDocCount 是每组的数量
                dto.setErrorNum((int)levelBucket.getDocCount());
            }
            if("info".equalsIgnoreCase(levelBucket.getKeyAsString())) {
                dto.setInfoNum((int)levelBucket.getDocCount());
            }
            if("debug".equalsIgnoreCase(levelBucket.getKeyAsString())) {
                dto.setDebugNum((int)levelBucket.getDocCount());
            }
        }
        for (Terms.Bucket levelBucket : aggregationsTemp2.getBuckets()) {
            dto.setUpdateTime(new DateTime(levelBucket.getKeyAsString()).toDate());
        }

    }
    list.add(dto);
}

参考资料

  • https://blog.csdn.net/qq_45071180/article/details/122702830
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