前言
ES在进行普通的查询时，默认只会查询出来10条数据。我们通过设置es中的size可以将最终的查询结果从10增加到10000。如果需要查询数据量大于es的翻页限制或者需要将es的数据进行导出又当如何？
Elasticsearch提供了一种称为"滚动查询"（Scrolling）的机制，用于处理大型数据集的分页查询。滚动查询允许在持续的时间段内保持一个活动的搜索上下文，然后使用滚动ID进行迭代检索结果。滚动查询和关系型数据库中的游标有点类似，因此也叫游标查询
1. 滚动查询的一般步骤
1.1 发起初始搜索请求,返回命中结果和滚动ID
scroll=5m表示每个滚动查询的有效时间为5分钟
POST /your_index/_search?scroll=5m
{
"size": 100, // 每次返回的结果数量
"query": { ... } // 查询条件
}
命中结果：
{
"_scroll_id": "DXF1ZXJ5QW5kRmV0Y2gBAAAAAAAAAD4WYm9laVYtZndUQlNsdDcwakFMNjU1QQ==",
"hits": {
"total": {
"value": 10000,
"relation": "eq"
},
"hits": [ ... ] // 检索到的文档
}
}
示例：
1.2 使用滚动ID检索下一页结果
POST /_search/scroll
{
"scroll": "5m",
"scroll_id": "DXF1ZXJ5QW5kRmV0Y2gBAAAAAAAAAD4WYm9laVYtZndUQlNsdDcwakFMNjU1QQ=="
}
示例：
POST /_search/scroll
{
"scroll": "5m",
"scroll_id": "FGluY2x1ZGVfY29udGV4dF91dWlkDXF1ZXJ5QW5kRmV0Y2gBFDJPRXc0WWdCY1BLWlo1MTk4MmR3AAAAAAAAAXYWcWgwSW5CQUtScEd2T2QtRGtYaWliQQ=="
}
1.4 重复执行直到没有检索结果返回
Elasticsearch将返回下一页结果和一个新的滚动ID。可以根据需要重复这个步骤，直到没有更多结果为止
1.5 清除滚动上下文释放资源
滚动查询结束后，您可以通过发送一个清除滚动上下文的请求来释放资源：文章来源：https://www.toymoban.com/news/detail-511674.html
DELETE /_search/scroll
{
"scroll_id": [
"DXF1ZXJ5QW5kRmV0Y2gBAAAAAAAAAD4WYm9laVYtZndUQlNsdDcwakFMNjU1QQ=="
]
}
以上为滚动查询进行分页检索的基本过程。在每个滚动请求中，都需要提供先前滚动请求返回的滚动ID。这样Elasticsearch才能够维护搜索上下文并返回正确的结果文章来源地址https://www.toymoban.com/news/detail-511674.html
2.Java Elasticsearch客户端执行滚动查询
public static void main(String[] args) {
long start = System.currentTimeMillis();
//构建es HttpHost对象
HttpHost httpHost1 = new HttpHost("192.168.1.1", 9200, "http");
// 滚动时间窗口
long scrollTime = 1L;
// 每次返回的文档数量
int batchSize = 20000;
//索引名
String indexName = "你的索引名称";
try (RestHighLevelClient client = new RestHighLevelClient(RestClient.builder(httpHost1))) {
//构建查询请求
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
searchSourceBuilder.query(QueryBuilders.boolQuery());
searchSourceBuilder.size(batchSize);
//设置查询返回字段
String[] includes = {};
searchSourceBuilder.fetchSource(includes, null);
// 滚动查询请求
SearchRequest searchRequest = new SearchRequest(indexName);
searchRequest.source(searchSourceBuilder);
//设置请求滚动时间窗口时间
searchRequest.scroll(TimeValue.timeValueMinutes(scrollTime));
//执行首次检索
SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
//首次检索返回scrollId，用于下一次的滚动查询
String scrollId = searchResponse.getScrollId();
//获取首次检索命中结果
SearchHit[] searchHits = searchResponse.getHits().getHits();
//计数
int count = 0;
// 处理第一批结果
for (SearchHit hit : searchHits) {
// 处理单个文档
JSONObject dataJson = (JSONObject) JSON.parse(hit.getSourceAsString());
System.out.println("====对首次请求的进行处理，当前计数：" + count++);
}
// 处理滚动结果
while (searchHits != null && searchHits.length > 0) {
SearchScrollRequest scrollRequest = new SearchScrollRequest(scrollId);
scrollRequest.scroll(TimeValue.timeValueMinutes(scrollTime));
searchResponse = client.scroll(scrollRequest, RequestOptions.DEFAULT);
scrollId = searchResponse.getScrollId();
searchHits = searchResponse.getHits().getHits();
for (SearchHit hit : searchHits) {
JSONObject dataJson = (JSONObject) JSON.parse(hit.getSourceAsString());
System.out.println("====滚动查询，当前计数：" + count++);
}
}
// 清理滚动上下文
ClearScrollRequest clearScrollRequest = new ClearScrollRequest();
clearScrollRequest.addScrollId(scrollId);
ClearScrollResponse clearScrollResponse = client.clearScroll(clearScrollRequest, RequestOptions.DEFAULT);
boolean succeeded = clearScrollResponse.isSucceeded();
long end = System.currentTimeMillis();
System.out.println("共执行时间：" + (end - start) / 1000 + " s");
} catch (Exception e) {
System.out.println("===error==" + e.getMessage());
e.printStackTrace();
}
}
3. SpringDataElasticsearch滚动查询
import org.elasticsearch.action.search .*;
import org.elasticsearch.client .*;
import org.elasticsearch.common.unit .*;
import org.elasticsearch.index.query .*;
import org.elasticsearch.search .*;
import org.elasticsearch.search.builder .*;
import org.springframework.beans.factory.annotation .*;
import org.springframework.data.elasticsearch.core .*;
import org.springframework.data.elasticsearch.core.query .*;
public class ScrollSearchExample {
@Autowired
private ElasticsearchOperations elasticsearchOperations;
public void performScrollSearch() {
String scrollTime = "1m"; // 滚动时间窗口
int batchSize = 100; // 每次返回的文档数量
QueryBuilder queryBuilder = QueryBuilders.matchQuery("field", "value");
NativeSearchQueryBuilder searchQuery = new NativeSearchQueryBuilder();
searchQuery.withQuery(queryBuilder).withPageable(PageRequest.of(0, batchSize)).build();
SearchResponse searchResponse = elasticsearchOperations.startScroll(
scrollTime,
searchQuery,
YourEntityClass.class,
IndexCoordinates.of("your_index")
);
String scrollId = searchResponse.getScrollId();
SearchHits<YourEntityClass> searchHits = searchResponse.getSearchHits();
// 处理第一批结果
for (SearchHit<YourEntityClass> hit : searchHits) {
YourEntityClass entity = hit.getContent();
// 处理单个文档
}
// 处理滚动结果
while (searchHits != null && searchHits.hasSearchHits()) {
searchResponse = elasticsearchOperations.continueScroll(scrollId, scrollTime, YourEntityClass.class);
scrollId = searchResponse.getScrollId();
searchHits = searchResponse.getSearchHits();
for (SearchHit<YourEntityClass> hit : searchHits) {
YourEntityClass entity = hit.getContent();
// 处理单个文档
}
}
// 清理滚动上下文
elasticsearchOperations.clearScroll(scrollId);
}
}
到了这里，关于Elasticsearch“滚动查询“（Scrolling）的机制的与Java使用ES Client 调用滚动查询的文章就介绍完了。如果您还想了解更多内容，请在右上角搜索TOY模板网以前的文章或继续浏览下面的相关文章，希望大家以后多多支持TOY模板网！
