elasticsearch的restful API和Java API

本人现在使用的是elasticsearch 5.2.1的,服务器IP为192.168.5.182.所以在Java API和jar包中会有所不同.

常用的restful API如下:

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,必须带上所有数据
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 搜索所有
GET http://192.168.5.182:9200/ecommerce/product/_search?q=name:yagao&sort=price:desc
curl -XGET 'http://192.168.5.182:9200/ecommerce/product/_search' -d'

{
"query":{

 "match_all":{}

}
}'
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
curl -XGET 'http://192.168.5.182:9200/ecommerce/product/_search' -d'
{
"query":{

 "match":{ "producer":"yagao producer" }

}
}' 全文检索

curl -XGET 'http://192.168.5.182:9200/ecommerce/product/_search' -d'
{
"query":{

 "match_phrase":{ "producer":"yagao producer" }

}
}' 短语搜索
curl -XGET 'http://192.168.5.182:9200/ecommerce/product/_search' -d'

{

"query":{ "match":{ "producer":"producer" } }, "highlight":{ "fields":{ "producer":{} } }

}' 高亮显示
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

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建立正排索引

在Java API中,我们需要先找到相应的jar包,maven中的配置如下(开始之前请先执行上面的给country建立正排索引的restful API)

org.elasticsearch.client
transport
5.2.1

5.2.1中只需要配这一个就可以了,当然不同的版本配置的都不同,高版本的需要配

org.elasticsearch
elasticsearch

我们依然在resources文件中做如下配置(注意restful API中使用的是9200端口,而Java API使用的是9300端口)

elasticsearch:
clusterName: aubin-cluster
clusterNodes: 192.168.5.182:9300
配置类如下

@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.

我们做一个数据类

@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 * 然后在每个country分组内,再按照入职年限进行分组 * 最后计算每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(); }

}
在主程序中调用如下(一般我们可以先不执行搜索操作,先注入数据,因为elasticsearch本身有一个秒级写读的问题,如果数据写入,得需要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();

}
}