在使用Eleasticsearch进行索引维护的过程中，如果你的应用场景需要频繁的大批量的索引写入，再使用上篇中提到的维护方法的话显然效率是低下的，此时推荐使用bulkIndex来提升效率。批写入数据块的大小取决于你的数据集及集群的配置。
下面我们以Spring Boot结合Elasticsearch创建一个示例项目
application.properties配置
#elasticsearch config
spring.data.elasticsearch.cluster-name:elasticsearch
spring.data.elasticsearch.cluster-nodes:192.168.1.105:9300
#application config
server.port=8080
spring.application.name=esp-app
我们需要定义域的实体和一个Spring data的基本的CRUD支持库类。用id注释定义标识符字段，如果你没有指定ID字段，Elasticsearch不能索引你的文件。同时需要指定索引名称类型，@Document注解也有助于我们设置分片和副本数量。
@Data
@Document(indexName = "carIndex", type = "carType", shards = 1, replicas = 0)
public class Car implements Serializable {
/**
* serialVersionUID:
* @since JDK 1.6
*/
private static final long serialVersionUID = 1L;
@Id
private Long id;
private String brand;
private String model;
private BigDecimal amount;
public Car(Long id, String brand, String model, BigDecimal amount) {
this.id = id;
this.brand = brand;
this.model = model;
this.amount = amount;
}
}
接着定义一个IndexService并使用bulk请求来处理索引，操作前首先要判断索引是否存在，以免出现异常。为了更好的掌握Java API，这里采用了不同于上篇中ElasticSearchRepository的ElasticSearchTemplate工具集，相对来讲功能更加丰富。
@Service
public class IndexerService {
private static final String CAR_INDEX_NAME = "car_index";
private static final String CAR_INDEX_TYPE = "car_type";
@Autowired
ElasticsearchTemplate elasticsearchTemplate;
public long bulkIndex() throws Exception {
int counter = 0;
try {
//判断索引是否存在
if (!elasticsearchTemplate.indexExists(CAR_INDEX_NAME)) {
elasticsearchTemplate.createIndex(CAR_INDEX_NAME);
}
Gson gson = new Gson();
List queries = new ArrayList();
List cars = assembleTestData();
for (Car car : cars) {
IndexQuery indexQuery = new IndexQuery();
indexQuery.setId(car.getId().toString());
indexQuery.setSource(gson.toJson(car));
indexQuery.setIndexName(CAR_INDEX_NAME);
indexQuery.setType(CAR_INDEX_TYPE);
queries.add(indexQuery);
//分批提交索引
if (counter % 500 == 0) {
elasticsearchTemplate.bulkIndex(queries);
queries.clear();
System.out.println("bulkIndex counter : " + counter);
}
counter++;
}
//不足批的索引最后不要忘记提交
if (queries.size() > 0) {
elasticsearchTemplate.bulkIndex(queries);
}
elasticsearchTemplate.refresh(CAR_INDEX_NAME);
System.out.println("bulkIndex completed.");
} catch (Exception e) {
System.out.println("IndexerService.bulkIndex e;" + e.getMessage());
throw e;
}
return -1;
}
private List assembleTestData() {
List cars = new ArrayList();
//随机生成10000个索引，以便下一次批量写入
for (int i = 0; i < 10000; i++) {
cars.add(new Car(RandomUtils.nextLong(1, 11111), RandomStringUtils.randomAscii(20), RandomStringUtils.randomAlphabetic(15), BigDecimal.valueOf(78000)));
}
return cars;
}
}
再下面的工作就比较简单了，可以编写一个RestController接受请求来测试或者CommandLineRunner，在系统启动时就加载上面的方法。
@SpringBootApplication
@RestController
public class ESPApplicatoin {
public static void main(String[] args) {
SpringApplication.run(ESPApplicatoin.class, args);
}
@Autowired
IndexerService indexService;
@RequestMapping(value = "bulkIndex",method = RequestMethod.POST)
public void bulkIndex(){
try {
indexService.bulkIndex();
} catch (Exception e) {
e.printStackTrace();
}
}
}
CommandLineRunner方法类：
@Component
public class AppLoader implements CommandLineRunner {
@Autowired
IndexerService indexerService;
@Override
public void run(String... strings) throws Exception {
indexerService.bulkIndex();
}
}
结束后，就可在通过地址http://localhost:9200/car_index/_search/来查看索引到底有无生效。注：要特别关注版本的兼容问题，如果用Es 5+的话，显然不能采用Spring Data Elasticsearch的方式。
Spring Boot
Version (x)
Spring Data Elasticsearch Version (y)Elasticsearch Version (z)
x <= 1.3.5y <= 1.3.4z <= 1.7.2*
x >= 1.4.x2.0.0 <=y < 5.0.0**2.0.0 <= z < 5.0.0**
(*) - require manual change in your project pom file (solution 2.)
(**) - Next big ES release with breaking changes
案例地址:https://github.com/backkoms/spring-boot-elasticsearch
扩展阅读：
Spring Boot + Elasticsearch 实现索引的日常维护
基于SpringCloud的Microservices架构实战案例-序篇
Nginx+Lua+MySQL/Redis实现高性能动态网页展现
Nginx+Lua+Redis实现高性能缓存数据读取