elasticsearch的restful API和Java API

时间 2019-11-09

标签 elasticsearch restful api java 栏目日志分析繁體版

原文原文链接

本人如今使用的是elasticsearch 5.2.1的,服务器IP为192.168.5.182.因此在Java API和jar包中会有所不一样.json

经常使用的restful API以下:服务器

http://192.168.5.182:9200/_cat/health?v 健康检查
http://192.168.5.182:9200/_cat/indices?v 查看索引
PUT http://192.168.5.182:9200/test_index?pretty 添加索引
DELETE http://192.168.5.182:9200/test_index 删除索引
PUT http://192.168.5.182:9200/ecommerce/product/1
BODY {
   "name":"zhonghua yagao",
   "desc":"caoben zhiwu",
   "price":40,
   "producer":"zhonghua producer",
   "tags":["qingxin"]
} 为索引添加数据,ecommerce索引,product type,1 ID
GET http://192.168.5.182:9200/ecommerce/product/1 查询数据
PUT http://192.168.5.182:9200/ecommerce/product/1
BODY {
   "name":"jiaqiangban zhonghua yagao",
   "desc":"caoben zhiwu",
   "price":40,
   "producer":"zhonghua producer",
   "tags":["qingxin"]
} 更新索引数据,方式一,必须带上全部数据
POST http://192.168.5.182:9200/ecommerce/product/1/_update
BODY {
   "doc": {
       "name":"gaolujie yagao"
   }
} 更新索引数据,方式二
DELETE http://192.168.5.182:9200/ecommerce/product/1 删除索引数据
GET http://192.168.5.182:9200/ecommerce/product/_search 搜索全部
GET http://192.168.5.182:9200/ecommerce/product/_search?q=name:yagao&sort=price:desc <query string search>
curl -XGET 'http://192.168.5.182:9200/ecommerce/product/_search' -d'
> {
> "query":{
> "match_all":{}
> }
> }' <query DSL查询>
curl -XGET 'http://192.168.5.182:9200/ecommerce/product/_search' -d'
> {
> "query":{
> "match":{
> "name":"yagao"
> }
> },
> "sort":[
> {"price":"desc"}
> ]
> }' 排序查询
curl -XGET 'http://192.168.5.182:9200/ecommerce/product/_search' -d'
> {
> "query":{
> "match_all":{}
> },
> "from":1,
> "size":1
> }' 分页查询
curl -XGET 'http://192.168.5.182:9200/ecommerce/product/_search' -d'
{
"query":{
"match_all":{}
},
"_source":["name","price"]
}' 只查询指定的字段
curl -XGET 'http://192.168.5.182:9200/ecommerce/product/_search' -d'
{
> "query":{
> "bool":{
> "must":{
> "match":{
> "name":"yagao"
> }
> },
> "filter":{
> "range":{
> "price":{
> "gt":25
> }
> }
> }
> }
> }
> }' 查询yagao的price范围,大于25 <query filter>
curl -XGET 'http://192.168.5.182:9200/ecommerce/product/_search' -d'
> {
> "query":{
> "match":{
> "producer":"yagao producer"
> }
> }
> }' 全文检索<full-text search>
curl -XGET 'http://192.168.5.182:9200/ecommerce/product/_search' -d'
{
"query":{
"match_phrase":{
"producer":"yagao producer"
}
}
}' 短语搜索<phrase search>
curl -XGET 'http://192.168.5.182:9200/ecommerce/product/_search' -d'
> {
> "query":{
> "match":{
> "producer":"producer"
> }
> },
> "highlight":{
> "fields":{
> "producer":{}
> }
> }
> }' 高亮显示<highlight search>
PUT http://192.168.5.182:9200/ecommerce/_mapping/product
BODY {
   "properties":{
       "tags":{
           "type":"text",
           "fielddata":true
       }
   }
} 将文本field的fielddata属性设置为true
curl -XGET 'http://192.168.5.182:9200/ecommerce/product/_search' -d'
> {
> "aggs":{
> "group_by_tags":{
> "terms":{
> "field":"tags"
> }
> }
> }
> }' 对tags聚合,会显示明细
curl -XGET 'http://192.168.5.182:9200/ecommerce/product/_search' -d'
{ "size":0,
"aggs":{
"group_by_tags":{
"terms":{
"field":"tags"
}
}
}
}' 对tags聚合,不显示明细,只显示聚合
curl -XGET 'http://192.168.5.182:9200/ecommerce/product/_search' -d'
> {
> "size":0,
> "query":{
> "match":{
> "name":"yagao"
> }
> },
> "aggs":{
> "group_by_tags":{
> "terms":{
> "field":"tags"
> }
> }
> }
> }' 搜索包含条件的聚合
curl -XGET 'http://192.168.5.182:9200/ecommerce/product/_search' -d'
> {
> "size":0,
> "aggs":{
> "group_by_tags":{
> "terms":{
> "field":"tags"
> },
> "aggs":{
> "avg_price":{
> "avg":{
> "field":"price"
> }
> }
> }
> }
> }
> }' 聚合计算平均值
curl -XGET 'http://192.168.5.182:9200/ecommerce/product/_search' -d'
> {
> "size":0,
> "aggs":{
> "group_by_tags":{
> "terms":{
> "field":"tags",
> "order":{
> "avg_price":"desc"
> }
> },
> "aggs":{
> "avg_price":{
> "avg":{
> "field":"price"
> }
> }
> }
> }
> }
> }' 聚合后降序排序restful

curl -XGET 'http://192.168.5.182:9200/ecommerce/product/_search' -d'
{
"size":0,
"aggs":{
"group_by_price":{
"range":{
"field":"price",
"ranges":[
{
"from":0,
"to":20
},
{
"from":20,
"to":40
},
{
"from":40,
"to":60
}
]
},
"aggs":{
"group_by_tags":{
"terms":{
"field":"tags"
},
"aggs":{
"average_price":{
"avg":{
"field":"price"
}
}
}
}
}
}
}
}' 按照价格区间分组后再聚合tags平均价格
PUT http://192.168.5.182:9200/company
BODY {
"mappings": {
"employee": {
"properties": {
"age": {
"type": "long"
},
"country": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
},
"fielddata":true
},
"join_date": {
"type": "date"
},
"name": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"position": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"salary": {
"type": "long"
}
}
}
}
} 给country创建正排索引app

在Java API中,咱们须要先找到相应的jar包,maven中的配置以下(开始以前请先执行上面的给country创建正排索引的restful API)curl

<dependency>
   <groupId>org.elasticsearch.client</groupId>
   <artifactId>transport</artifactId>
   <version>5.2.1</version>
</dependency>

5.2.1中只须要配这一个就能够了,固然不一样的版本配置的都不一样,高版本的须要配elasticsearch

<dependency>
   <groupId>org.elasticsearch</groupId>
   <artifactId>elasticsearch</artifactId>
</dependency>

咱们依然在resources文件中作以下配置(注意restful API中使用的是9200端口,而Java API使用的是9300端口)maven

elasticsearch:
  clusterName: aubin-cluster
  clusterNodes: 192.168.5.182:9300

配置类以下ui

@Getter
@Setter
@Configuration
@ConfigurationProperties(prefix = "elasticsearch")
public class ElasticSearchConfig {

   private String clusterName;

   private String clusterNodes;

    /**
     * 使用elasticsearch实现类时才触发
     *
     * @return
     */
   @Bean
   public TransportClient transportClient() {
      // 设置集群名字
      Settings settings = Settings.builder().put("cluster.name", this.clusterName).build();
      TransportClient client = new PreBuiltTransportClient(settings);
      try {
         // 读取的ip列表是以逗号分隔的
         for (String clusterNode : this.clusterNodes.split(",")) {
            String ip = clusterNode.split(":")[0];
            String port = clusterNode.split(":")[1];
            client.addTransportAddress(new InetSocketTransportAddress(InetAddress.getByName(ip), Integer.parseInt(port)));
         }
      } catch (UnknownHostException e) {
         e.printStackTrace();
      }

      return client;
   }
}

在5.2.1中使用的是InetSocketTransportAddress,这是一个具体的类,而在高版本中此处为TransportAddress,这是一个接口.this

咱们作一个数据类url

@Component
public class DataEs {
    @Autowired
    private TransportClient transportClient;

    /**
     * 添加原始数据
     * @throws IOException
     */
    @PostConstruct
    private void init() throws IOException {
        transportClient.prepareIndex("company","employee","1").setSource(XContentFactory.jsonBuilder().startObject()
                .field("name","jack")
                .field("age",27)
                .field("position","technique software")
                .field("country","China")
                .field("join_date","2018-01-01")
                .field("salary",10000)
                .endObject()).get();
        transportClient.prepareIndex("company","employee","2").setSource(XContentFactory.jsonBuilder().startObject()
                .field("name","marry")
                .field("age",35)
                .field("position","technique manager")
                .field("country","China")
                .field("join_date","2018-01-01")
                .field("salary",12000)
                .endObject()).get();
        transportClient.prepareIndex("company","employee","3").setSource(XContentFactory.jsonBuilder().startObject()
                .field("name","tom")
                .field("age",32)
                .field("position","senior technique software")
                .field("country","China")
                .field("join_date","2017-01-01")
                .field("salary",11000)
                .endObject()).get();
        transportClient.prepareIndex("company","employee","4").setSource(XContentFactory.jsonBuilder().startObject()
                .field("name","jen")
                .field("age",25)
                .field("position","junior finance")
                .field("country","USA")
                .field("join_date","2017-01-01")
                .field("salary",7000)
                .endObject()).get();
        transportClient.prepareIndex("company","employee","5").setSource(XContentFactory.jsonBuilder().startObject()
                .field("name","mike")
                .field("age",37)
                .field("position","finance manager")
                .field("country","USA")
                .field("join_date","2016-01-01")
                .field("salary",15000)
                .endObject()).get();
    }

    /**
     * 员工搜索应用程序
     * 搜索职位中包含technique的员工
     * 同时要求age在30到40岁之间
     * 分页查询,查找第一页
     */
    public void executeSearch() {
        SearchResponse searchResponse = transportClient.prepareSearch("company")
                .setTypes("employee")
                .setQuery(QueryBuilders.matchQuery("position", "technique"))
                .setPostFilter(QueryBuilders.rangeQuery("age").from(30).to(40))
                .setFrom(0).setSize(1)
                .get();
        SearchHit[] hits = searchResponse.getHits().getHits();
        for (int i = 0;i < hits.length;i++) {
            System.out.println(hits[i].getSourceAsString());
        }
    }

    /**
     * 员工聚合分析应用程序
     * 首先按照country国家来进行分组
     * 而后在每一个country分组内,再按照入职年限进行分组
     * 最后计算每一个分组内的平均薪资
     */
    public void executeAggregation() {
        SearchResponse searchResponse = transportClient.prepareSearch("company")
                .addAggregation(AggregationBuilders.terms("group_by_country").field("country")
                .subAggregation(AggregationBuilders.dateHistogram("group_by_join_date")
                .field("join_date").dateHistogramInterval(DateHistogramInterval.YEAR)
                .subAggregation(AggregationBuilders.avg("avg_salary").field("salary"))))
                .execute().actionGet();
        Map<String,Aggregation> aggrMap = searchResponse.getAggregations().asMap();
        StringTerms groupByCountry = (StringTerms) aggrMap.get("group_by_country");
        Iterator<StringTerms.Bucket> groupByCountryBucketIterator = groupByCountry.getBuckets().iterator();
        while (groupByCountryBucketIterator.hasNext()) {
            StringTerms.Bucket groupByCountryBucket = groupByCountryBucketIterator.next();
            System.out.println(groupByCountryBucket.getKey() + ":" + groupByCountryBucket.getDocCount());
            Histogram groupByJoinDate = (Histogram) groupByCountryBucket.getAggregations().asMap().get("group_by_join_date");
            Iterator<? extends Histogram.Bucket> groupByJoinDateIterator = groupByJoinDate.getBuckets().iterator();
            while (groupByJoinDateIterator.hasNext()) {
                Histogram.Bucket groupByJoinDateBucket = groupByJoinDateIterator.next();
                System.out.println(groupByJoinDateBucket.getKey() + ":" + groupByJoinDateBucket.getDocCount());
                Avg avg = (Avg) groupByJoinDateBucket.getAggregations().asMap().get("avg_salary");
                System.out.println(avg.getValue());
            }
        }
    }
    public void close() {
        transportClient.close();
    }
}

在主程序中调用以下(通常咱们能够先不执行搜索操做,先注入数据,由于elasticsearch自己有一个秒级写读的问题,若是数据写入,得须要1秒的时间才能读取出来)

@SpringBootApplication
public class EsApplication {
   public static void main(String[] args) {
      ApplicationContext applicationContext = SpringApplication.run(EsApplication.class, args);
      DataEs dataEs = (DataEs) applicationContext.getBean(DataEs.class);
      dataEs.executeSearch();
      dataEs.executeAggregation();
      dataEs.close();
   }
}

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