一、scroll说明和使用场景
scroll的使用场景：大数据量的检索和操作
scroll顾名思义，就是游标的意思，核心的应用场景就是遍历 elasticsearch中的数据；
通常我们遍历数据采用的是分页，elastcisearch还支持from size的方式进行分页查询，使用 from and size 的深度分页，比如说 ?size=10&from=10000，因为 100,000 排序的结果必须从每个分片上取出并重新排序最后返回 10 条。这个过程需要对每个请求页重新进行提取+排序，效率很低，消耗很大，所以默认的最大可分页的数据是10000，超过10000是不建议的；
使用
通过在url末尾带上scroll=1m表示开启一个游标，1m表示游标的有效期为1分钟
POST /record/_search?scroll=1m
{
"from": 0,
"size": 20
}
返回结果中会把scroll的id带上，再次查询的时候，直接用scroll id查询即可
POST /_search/scroll
{
"scroll" : "1m",
"scroll_id" : "FGluY2x1ZGVfY29udGV4dF91dWlkDnF1ZXJ5VGhlbkZldGNoAhZuYmpMbVpwWFRUMnNFMUFFSHlSMHB3AAAAAALBy_0WUWxrNTRTaWNUcy1sOHQ0VUo5dzF6dxZoemFkZTlMeFQ4MmoyOW5SUG8ybE53AAAAAAN6ip8WMmk5TWZlQ21RQnFsNURwaXRzSGhCdw=="
}
二、基于ElasticsearchRestTemplate的实现
这里我们定义了一个template如下，主要作用就是实现一个基于scroll的数据遍历模板，屏蔽开启scroll 以及 scroll遍历所有数据，通过Consumer<T>钩子函数进行数据处理
import lombok.extern.slf4j.Slf4j;
import org.elasticsearch.index.query.BoolQueryBuilder;
import org.elasticsearch.index.query.QueryBuilders;
import org.springframework.data.domain.PageRequest;
import org.springframework.data.elasticsearch.core.ElasticsearchRestTemplate;
import org.springframework.data.elasticsearch.core.SearchHit;
import org.springframework.data.elasticsearch.core.SearchScrollHits;
import org.springframework.data.elasticsearch.core.mapping.IndexCoordinates;
import org.springframework.data.elasticsearch.core.query.NativeSearchQueryBuilder;
import java.util.List;
import java.util.concurrent.*;
/**
* scrollTemplate 模板，用于遍历整个Index的数据
* @author xiuzhu
* @Date 2023/7/28 13:12
*/
@Slf4j
public class ElasticSearchScrollTemplate<T> {
ExecutorService executorService = new ThreadPoolExecutor(1, 4,
30,TimeUnit.SECONDS,
new LinkedBlockingQueue<Runnable>(5),
Executors.defaultThreadFactory(),
new ThreadPoolExecutor.CallerRunsPolicy()
);
ElasticsearchRestTemplate elasticSearchRestTemplate;
Class<T> cls;
String indexName;
public ElasticSearchScrollTemplate(
ElasticsearchRestTemplate template,
Class<T> cls,
String indexName
) {
this.elasticSearchRestTemplate = template;
this.cls = cls;
this.indexName = indexName;
}
@FunctionalInterface
public interface Consumer<T> {
public void accept(List<T> objects);
}
public void execute(Consumer<T> consumer) {
//构建查询条件
NativeSearchQueryBuilder query = new NativeSearchQueryBuilder();
BoolQueryBuilder queryBuilder = QueryBuilders.boolQuery();
query.withPageable(PageRequest.of(0, 300));
query.withQuery(queryBuilder);
//保留0.5分钟
long scrollTimeInMillis = 30*1000;
IndexCoordinates recordIndex = IndexCoordinates.of(indexName);
SearchScrollHits<T> hits = elasticSearchRestTemplate.searchScrollStart(scrollTimeInMillis, query.build(), cls, recordIndex);
// scrollId
String scrollId = hits.getScrollId();
List<T> recordEntityList = hits.stream().map(SearchHit::getContent).toList();
long total = 0L;
log.info("================ began scroll index={} ====================", indexName);
executorService.submit(()->{
consumer.accept(recordEntityList);
});
total = total + recordEntityList.size();
log.info("================ has scroll index={} total={} ====================", indexName, total);
while (!hits.isEmpty()) {
hits = elasticSearchRestTemplate.searchScrollContinue(scrollId, scrollTimeInMillis, cls, recordIndex);
List<T> entities = hits.stream().map(SearchHit::getContent).toList();
executorService.submit(()->{
consumer.accept(entities);
});
total = total + entities.size();
try {
//给系统留GC时间，不然容易内存溢出
Thread.sleep(300);
} catch (InterruptedException e) {
log.error("sleep error", e);
}
log.info("================ has scroll index={} total={} ====================", indexName, total);
}
log.info("================ end scroll index={} ====================", indexName);
}
}
使用参考：
@Resource(name = "elasticSearchRestTemplate")
ElasticsearchRestTemplate elasticsearchRestTemplate;
new ElasticSearchScrollTemplate<>(
elasticsearchRestTemplate,
RecordEntity.class,
"record")
).execute((entities)->{
entities.forEach(item->{
//这里进行数据的处理，比如修改数据
recordEntityService.save(item);
log.info("tag update success record={} api={}", item.getId());
});
});
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