在解決es入庫問題上,之前使用過rest方式,經過一段時間的測試發現千萬級別的數據會存在10至上百條數據的丟失問題,
在需要保證數據的准確性的場景下,rest方式並不能保證結果的准確性,因此采用了elasticsearch的BulkProcessor方式來進行數據入庫,
實際上采用es客戶端不同,rest方式采用的是restClient,基於http協議,BulkProcessor使用的是TransportClient,基於Tcp協議。
下面是在spring下具體的實現步驟:
1 定義一個student類,並json序列化
2 json的具體實現
3 構造BulkProcessor
* setBulkActions(1000):每添加1000個request,執行一次bulk操作
* setBulkSize(new ByteSizeValue(5, ByteSizeUnit.MB)):每達到5M的請求size時,執行一次bulk操作
* setFlushInterval(TimeValue.timeValueSeconds(5)):每5s執行一次bulk操作
* setConcurrentRequests(1):默認是1,表示積累bulk requests和發送bulk是異步的,其數值表示發送bulk的並發線程數,設置為0表示二者同步的
*setBackoffPolicy(BackoffPolicy.exponentialBackoff(TimeValue.timeValueMillis(100),3)):當ES由於資源不足發生異常
EsRejectedExecutionException重試策略:默認(50ms, 8),
* 策略算法:start + 10 * ((int) Math.exp(0.8d * (currentlyConsumed)) - 1)
package es; import org.elasticsearch.action.bulk.BackoffPolicy; import org.elasticsearch.action.bulk.BulkProcessor; import org.elasticsearch.action.bulk.BulkRequest; import org.elasticsearch.action.bulk.BulkResponse; import org.elasticsearch.client.Client; import org.elasticsearch.common.settings.Settings; import org.elasticsearch.common.transport.InetSocketTransportAddress; import org.elasticsearch.common.unit.ByteSizeUnit; import org.elasticsearch.common.unit.ByteSizeValue; import org.elasticsearch.common.unit.TimeValue; import org.elasticsearch.transport.client.PreBuiltTransportClient; import org.slf4j.Logger; import org.slf4j.LoggerFactory; import org.springframework.beans.factory.annotation.Autowired; import org.springframework.context.annotation.Bean; import org.springframework.context.annotation.Configuration; import java.net.InetAddress; import java.net.UnknownHostException; @Configuration public class ESConfiguration { public static final Logger logger = LoggerFactory.getLogger(ESConfiguration.class); @Bean public BulkProcessor bulkProcessor() throws UnknownHostException { Settings settings = Settings.builder().put("cluster.name", "elasticsearch").build(); Client client = new PreBuiltTransportClient(settings) .addTransportAddress(new InetSocketTransportAddress(InetAddress.getByName("http://192.168.10.33"), Integer.parseInt("9300"))); return BulkProcessor.builder(client, new BulkProcessor.Listener() { @Override public void beforeBulk(long l, BulkRequest bulkRequest) { } @Override public void afterBulk(long l, BulkRequest bulkRequest, BulkResponse bulkResponse) { } @Override public void afterBulk(long l, BulkRequest bulkRequest, Throwable throwable) { logger.error("{} data bulk failed,reason :{}", bulkRequest.numberOfActions(), throwable); } }).setBulkActions(1000) .setBulkSize(new ByteSizeValue(5, ByteSizeUnit.MB)) .setFlushInterval(TimeValue.timeValueSeconds(5)) .setConcurrentRequests(1) .setBackoffPolicy(BackoffPolicy.exponentialBackoff(TimeValue.timeValueMillis(100), 3)) .build(); } }
4. 入庫代碼實現
package es; import com.fasterxml.jackson.databind.ObjectMapper; import org.elasticsearch.action.bulk.BulkProcessor; import org.elasticsearch.action.index.IndexRequest; import org.slf4j.Logger; import org.slf4j.LoggerFactory; import org.springframework.beans.factory.annotation.Autowired; import org.springframework.stereotype.Repository; @Repository public class StudentInsertDao{ private final Logger logger = LoggerFactory.getLogger(this.getClass()); @Autowired private BulkProcessor bulkProcessor; private ObjectMapper objectMapper = new ObjectMapper(); public void insert(Student student) { String type = student.getAge(); String id = student.getName()+student.getAddr()+student.getAge(); try { byte[] json = objectMapper.writeValueAsBytes(student); bulkProcessor.add(new IndexRequest("students", type, id).source(json)); } catch (Exception e) { logger.error("bulkProcessor failed ,reason:{}",e); } } }
5. 測試代碼
@RunWith(SpringJUnit4ClassRunner.class) @WebAppConfiguration @ContextConfiguration(locations = {"classpath:servlet-context.xml", "classpath:applicationContext.xml"}) public class StudentInsertDaoTest { @Autowired private StudentInsertDao insertDao; @Test public void insert() throws Exception { Student student = new Student(); student.setAge(12); student.setAddr("SH"); student.setName("Jack"); insertDao.insert(student); } }
原文鏈接:https://blog.csdn.net/wslyk606/article/details/79413980