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首页 / Elasticsearch系列---Java客户端代码Demo

Elasticsearch系列---Java客户端代码Demo

Java架构社区 2020-05-22
211

前言

前面历经33篇内容的讲解，与ES的请求操作都是在Kibana平台上用Restful请求完成的，一直没发布Java或python的客户端代码，Restful才是运用、理解ES核心功能最直接的表达方式，但实际项目中肯定是以Java/python来完成ES请求的发起与数据处理的，前面理解了ES的核心功能，后面Java API的使用将会非常简单，剩余的未覆盖的功能API，自行查阅文档即可。

概要

本篇讲解Elasticsearch的客户端API开发的一些示例，以Java语言为主，介绍一些最常用，最核心的API。

代码示例

引入依赖

我们以maven项目为例，添加项目依赖

<dependency>
	<groupId>org.elasticsearch</groupId>
	<artifactId>elasticsearch</artifactId>
	<version>6.3.1</version>
</dependency>
<dependency>
	<groupId>org.elasticsearch.client</groupId>
	<artifactId>transport</artifactId>
	<version>6.3.1</version>
</dependency>
<dependency>
	<groupId>log4j</groupId>
	<artifactId>log4j</artifactId>
	<version>1.2.17</version>
</dependency>
<dependency>
	<groupId>org.apache.logging.log4j</groupId>
	<artifactId>log4j-core</artifactId>
	<version>2.12.1</version>
</dependency>

建立ES连接

  1. 创建Settings对象，指定集群名称
  2. 创建TransportClient对象，手动指定IP、端口即可
Settings settings = Settings.builder().put("cluster.name", "elasticsearch").build();
		
TransportClient client = new PreBuiltTransportClient(settings).addTransportAddress(new InetSocketTransportAddress(InetAddress.getByName("localhost"), 9300));

如果集群的节点数比较多，为每个node分别指定IP、Port可行性不高，我们可以使用集群节点自动探查的功能，代码如下：

// 将client.transport.sniff设置为true即可打开集群节点自动探查功能
Settings settings = Settings.builder().put("client.transport.sniff", true)..put("cluster.name", "elasticsearch").build();


// 只需要指定一个node就行
TransportClient client = new PreBuiltTransportClient(settings);
transport.addTransportAddress(new TransportAddress(InetAddress.getByName("192.168.17.137"), 9300));


基本CRUD

最基本的CRUD代码，可以当作入门demo来写：

/**
	 * 创建员工信息（创建一个document）
	 * @param client
	 */
	private static void createEmployee(TransportClient client) throws Exception {
		IndexResponse response = client.prepareIndex("company", "employee", "1")
				.setSource(XContentFactory.jsonBuilder()
						.startObject()
							.field("name", "jack")
							.field("age", 27)
							.field("position", "technique")
							.field("country", "china")
							.field("join_date", "2017-01-01")
							.field("salary", 10000)
						.endObject())
				.get();
		System.out.println(response.getResult()); 
	}
	
	/**
	 * 获取员工信息
	 * @param client
	 * @throws Exception
	 */
	private static void getEmployee(TransportClient client) throws Exception {
		GetResponse response = client.prepareGet("company", "employee", "1").get();
		System.out.println(response.getSourceAsString()); 
	}
	
	/**
	 * 修改员工信息
	 * @param client
	 * @throws Exception
	 */
	private static void updateEmployee(TransportClient client) throws Exception {
		UpdateResponse response = client.prepareUpdate("company", "employee", "1") 
				.setDoc(XContentFactory.jsonBuilder()
							.startObject()
								.field("position", "technique manager")
							.endObject())
				.get();
		System.out.println(response.getResult());  
 	}
	
	/**
	 * 删除 员工信息
	 * @param client
	 * @throws Exception
	 */
	private static void deleteEmployee(TransportClient client) throws Exception {
		DeleteResponse response = client.prepareDelete("company", "employee", "1").get();
		System.out.println(response.getResult());  
	}

搜索

我们之前使用Restful的搜索，现在改用java实现，原有的Restful示例如下：

GET /company/employee/_search
{
  "query": {
    "bool": {
      "must": [
        {
          "match": {
            "position": "technique"
          }
        }
      ],
      "filter": {
        "range": {
          "age": {
            "gte": 30,
            "lte": 40
          }
        }
      }
    }
  },
  "from": 0,
  "size": 1
}

等同于这样的Java代码：

SearchResponse response = client.prepareSearch("company")
        .setTypes("employee")
        .setQuery(QueryBuilders.termQuery("position", "technique"))                 // Query
        .setPostFilter(QueryBuilders.rangeQuery("age").from(30).to(40))     // Filter
        .setFrom(0).setSize(60)
        .get();

聚合查询

聚合查询稍微麻烦一些，请求的封装和响应报文的解析，都是根据实际返回的结构来做的，例如下面的查询：

需求：

  1. 按照country国家来进行分组
  2. 在每个country分组内，再按照入职年限进行分组
  3. 最后计算每个分组内的平均薪资

Restful的请求如下：

GET /company/employee/_search
{
  "size": 0,
  "aggs": {
    "group_by_country": {
      "terms": {
        "field": "country"
      },
      "aggs": {
        "group_by_join_date": {
          "date_histogram": {
            "field": "join_date",
            "interval": "year"
          },
          "aggs": {
            "avg_salary": {
              "avg": {
                "field": "salary"
              }
            }
          }
        }
      }
    }
  }
}

用Java编写的请求如下：

SearchResponse sr = node.client().prepareSearch()
    .addAggregation(
        AggregationBuilders.terms("by_country").field("country")
        .subAggregation(AggregationBuilders.dateHistogram("by_year")
            .field("dateOfBirth")
            .dateHistogramInterval(DateHistogramInterval.YEAR)
            .subAggregation(AggregationBuilders.avg("avg_children").field("children"))
        )
    )
    .execute().actionGet();

对响应的处理，则需要一层一层获取数据：

Map<String, Aggregation> aggrMap = searchResponse.getAggregations().asMap();
	StringTerms groupByCountry = (StringTerms) aggrMap.get("group_by_country");
	Iterator<Bucket> groupByCountryBucketIterator = groupByCountry.getBuckets().iterator();
	
	while(groupByCountryBucketIterator.hasNext()) {
		Bucket groupByCountryBucket = groupByCountryBucketIterator.next();
		
		System.out.println(groupByCountryBucket.getKey() + "\t" + groupByCountryBucket.getDocCount()); 
		
		Histogram groupByJoinDate = (Histogram) groupByCountryBucket.getAggregations().asMap().get("group_by_join_date"); 
		Iterator<org.elasticsearch.search.aggregations.bucket.histogram.Histogram.Bucket> groupByJoinDateBucketIterator = groupByJoinDate.getBuckets().iterator();
		 
		while(groupByJoinDateBucketIterator.hasNext()) {
			org.elasticsearch.search.aggregations.bucket.histogram.Histogram.Bucket groupByJoinDateBucket = groupByJoinDateBucketIterator.next();
			
			System.out.println(groupByJoinDateBucket.getKey() + "\t" + groupByJoinDateBucket.getDocCount()); 
			
			Avg avgSalary = (Avg) groupByJoinDateBucket.getAggregations().asMap().get("avg_salary");
			System.out.println(avgSalary.getValue()); 
		}
	}
	
	client.close();
}

upsert请求

private static void upsert(TransportClient transport) {
	try {
		IndexRequest index = new IndexRequest("book_shop", "books", "2").source(
				XContentFactory.jsonBuilder().startObject()
						.field("name", "mysql从入门到删库跑路")
						.field("tags", "mysql")
						.field("price", 32.8)
						.endObject());


		UpdateRequest update = new UpdateRequest("book_shop", "books", "2")
				.doc(XContentFactory.jsonBuilder()
						.startObject().field("price", 31.8)
						.endObject())
				.upsert(index);
		UpdateResponse response = transport.update(update).get();
		System.out.println(response.getVersion());
	} catch (IOException e) {
		e.printStackTrace();
	} catch (InterruptedException e) {
		e.printStackTrace();
	} catch (ExecutionException e) {
		e.printStackTrace();
	}
}

mget请求

public static void mget(TransportClient transport) {
	MultiGetResponse res = transport.prepareMultiGet()
			.add("book_shop", "books", "1")
			.add("book_shop", "books", "2")
			.get();
	for (MultiGetItemResponse item : res.getResponses()) {
		System.out.println(item.getResponse());
	}
}

bulk请求

public static void bulk(TransportClient transport) {
	try {
	BulkRequestBuilder bulk = transport.prepareBulk();
	bulk.add(transport.prepareIndex("book_shop", "books", "3").setSource(
			XContentFactory.jsonBuilder().startObject()
					.field("name", "设计模式从入门到拷贝代码")
					.field("tags", "设计模式")
					.field("price", 55.9)
					.endObject()));
		bulk.add(transport.prepareIndex("book_shop", "books", "4").setSource(
				XContentFactory.jsonBuilder().startObject()
						.field("name", "架构设计从入门到google搜索")
						.field("tags", "架构设计")
						.field("price", 68.9)
						.endObject()));
		bulk.add(transport.prepareUpdate("book_shop", "books", "1").setDoc((XContentFactory.jsonBuilder()
				.startObject().field("price", 32.8)
				.endObject())));


		BulkResponse bulkRes = bulk.get();
		if (bulkRes.hasFailures()) {
			System.out.println("Error...");
		}
	} catch (IOException e) {
		e.printStackTrace();
	}
}

scorll请求

public static void scorll(TransportClient client) {
	SearchResponse bookShop = client.prepareSearch("book_shop").setScroll(new TimeValue(60000)).setSize(1).get();


	int batchCnt = 0;
	do {
	    // 循环读取scrollid信息，直到结果为空
		for(SearchHit hit: bookShop.getHits().getHits()) {
			System.out.println("batchCnt:" + ++batchCnt);
			System.out.println(hit.getSourceAsString());
		}
		bookShop = client.prepareSearchScroll(bookShop.getScrollId()).setScroll(new TimeValue(60000)).execute().actionGet();
	} while (bookShop.getHits().getHits().length != 0);
}


搜索模板

public static void searchTemplates(TransportClient client) {
	Map<String,Object> params = new HashMap<>(10);
	params.put("from",0);
	params.put("size",10);
	params.put("tags","java");


	SearchTemplateResponse str = new SearchTemplateRequestBuilder(client)
			.setScript("page_query_by_tags")
			.setScriptType(ScriptType.STORED)
			.setScriptParams(params)
			.setRequest(new SearchRequest())
			.get();


	for(SearchHit hit:str.getResponse().getHits().getHits()) {
		System.out.println(hit.getSourceAsString());
	}
}

多条件组合查询

public static void otherSearch(TransportClient client) {
	SearchResponse response1 = client.prepareSearch("book_shop").setQuery(QueryBuilders.termQuery("tags", "java")).get();
	SearchResponse response2 = client.prepareSearch("book_shop").setQuery(QueryBuilders.multiMatchQuery("32.8", "price","tags")).get();
	SearchResponse response3 = client.prepareSearch("book_shop").setQuery(QueryBuilders.commonTermsQuery("name", "入门")).get();
	SearchResponse response4 = client.prepareSearch("book_shop").setQuery(QueryBuilders.prefixQuery("name", "java")).get();


	System.out.println(response1.getHits().getHits()[0].getSourceAsString());
	System.out.println(response2.getHits().getHits()[0].getSourceAsString());
	System.out.println(response3.getHits().getHits()[0].getSourceAsString());
	System.out.println(response4.getHits().getHits()[0].getSourceAsString());


	// 多个条件组合
	SearchResponse response5 = client.prepareSearch("book_shop").setQuery(QueryBuilders.boolQuery()
			.must(QueryBuilders.termQuery("tags", "java"))
			.mustNot(QueryBuilders.matchQuery("name", "跑路"))
			.should(QueryBuilders.matchQuery("name", "入门"))
			.filter(QueryBuilders.rangeQuery("price").gte(23).lte(55))).get();


	System.out.println(response5.getHits().getHits()[0].getSourceAsString());
}

地理位置查询

public static void geo(TransportClient client) {
	GeoBoundingBoxQueryBuilder query1 = QueryBuilders.geoBoundingBoxQuery("location").setCorners(23, 112, 21, 114);


	List<GeoPoint> points = new ArrayList<>();
	points.add(new GeoPoint(23,115));
	points.add(new GeoPoint(25,113));
	points.add(new GeoPoint(21,112));
	GeoPolygonQueryBuilder query2 = QueryBuilders.geoPolygonQuery("location",points);


	GeoDistanceQueryBuilder query3 = QueryBuilders.geoDistanceQuery("location").point(22.523375, 113.911231).distance(500, DistanceUnit.METERS);




	SearchResponse response = client.prepareSearch("location").setQuery(query3).get();
	for(SearchHit hit:response.getHits().getHits()) {
		System.out.println(hit.getSourceAsString());
	}
}

小结

上述的那些案例demo，快速浏览一下即可，如果已经在开发ES相关的项目，还是多参考官方的API文档：https://www.elastic.co/guide/en/elasticsearch/client/java-api/6.3/index.html。上面有很详尽的API说明和使用Demo


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