作者：刘晓国
在上一篇文章 “Elasticsearch：运用 scroll 接口对大量数据实现更好的分页”，我们讲述了如何运用 scroll 接口来对大量数据来进行有效地分页。在那篇文章中，我们讲述了两种方法：
1.from 加上 size 的方法来进行分页
2.运用 scroll 接口来进行分页
对于大量的数据而言，我们尽量避免使用 from+size 这种方法。这里的原因是 index.max_result_window 的默认值是 10K，也就是说 from+size 的最大值是1万。搜索请求占用堆内存和时间与 from+size 成比例，这限制了内存。假如你想 hit 从 990 到 1000，那么每个 shard 至少需要 1000 个文档：
为了避免过度使得我们的 cluster 繁忙，通常 Scroll 接口被推荐作为深层次的 scrolling，但是因为维护 scroll 上下文也是非常昂贵的，所以这种方法不推荐作为实时用户请求。search_after 参数通过提供实时 cursor 来解决此问题。 我们的想法是使用上一页的结果来帮助检索下一页。
我们先输入如下的文档到 twitter 索引中：
POST _bulk { "index" : { "_index" : "twitter", "_id": 1} } {"user":"双榆树-张三", "DOB":"1980-01-01", "message":"今儿天气不错啊，出去转转去","uid":2,"age":20,"city":"北京","province":"北京","country":"中国","address":"中国北京市海淀区","location":{"lat":"39.970718","lon":"116.325747"}} { "index" : { "_index" : "twitter", "_id": 2 }} {"user":"东城区-老刘", "DOB":"1981-01-01", "message":"出发，下一站云南！","uid":3,"age":30,"city":"北京","province":"北京","country":"中国","address":"中国北京市东城区台基厂三条3号","location":{"lat":"39.904313","lon":"116.412754"}} { "index" : { "_index" : "twitter", "_id": 3} } {"user":"东城区-李四", "DOB":"1982-01-01", "message":"happy birthday!","uid":4,"age":30,"city":"北京","province":"北京","country":"中国","address":"中国北京市东城区","location":{"lat":"39.893801","lon":"116.408986"}} { "index" : { "_index" : "twitter", "_id": 4} } {"user":"朝阳区-老贾","DOB":"1983-01-01", "message":"123,gogogo","uid":5,"age":35,"city":"北京","province":"北京","country":"中国","address":"中国北京市朝阳区建国门","location":{"lat":"39.718256","lon":"116.367910"}} { "index" : { "_index" : "twitter", "_id": 5} } {"user":"朝阳区-老王","DOB":"1984-01-01", "message":"Happy BirthDay My Friend!","uid":6,"age":50,"city":"北京","province":"北京","country":"中国","address":"中国北京市朝阳区国贸","location":{"lat":"39.918256","lon":"116.467910"}} { "index" : { "_index" : "twitter", "_id": 6} } {"user":"虹桥-老吴", "DOB":"1985-01-01", "message":"好友来了都今天我生日，好友来了,什么 birthday happy 就成!","uid":7,"age":90,"city":"上海","province":"上海","country":"中国","address":"中国上海市闵行区","location":{"lat":"31.175927","lon":"121.383328"}}
这里共有6个文档。假设检索第一页的查询如下所示：
GET twitter/_search { "size": 2, "query": { "match": { "city": "北京" } }, "sort": [ { "DOB": { "order": "asc" } }, { "user.keyword": { "order": "asc" } } ] }
显示的结果为：
{ "took" : 29, "timed_out" : false, "_shards" : { "total" : 1, "successful" : 1, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : { "value" : 5, "relation" : "eq" }, "max_score" : null, "hits" : [ { "_index" : "twitter", "_type" : "_doc", "_id" : "1", "_score" : null, "_source" : { "user" : "双榆树-张三", "DOB" : "1980-01-01", "message" : "今儿天气不错啊，出去转转去", "uid" : 2, "age" : 20, "city" : "北京", "province" : "北京", "country" : "中国", "address" : "中国北京市海淀区", "location" : { "lat" : "39.970718", "lon" : "116.325747" } }, "sort" : [ 315532800000, "双榆树-张三" ] }, { "_index" : "twitter", "_type" : "_doc", "_id" : "2", "_score" : null, "_source" : { "user" : "东城区-老刘", "DOB" : "1981-01-01", "message" : "出发，下一站云南！", "uid" : 3, "age" : 30, "city" : "北京", "province" : "北京", "country" : "中国", "address" : "中国北京市东城区台基厂三条3号", "location" : { "lat" : "39.904313", "lon" : "116.412754" } }, "sort" : [ 347155200000, "东城区-老刘" ] } ] } }
上述请求的结果包括每个文档的 sort 值数组。 这些 sort 值可以与 search_after 参数一起使用，以开始返回在这个结果列表之后的任何文档。 例如，我们可以使用上一个文档的 sort 值并将其传递给 search_after 以检索下一页结果：
GET twitter/_search { "size": 2, "query": { "match": { "city": "北京" } }, "search_after": [ 347155200000, "东城区-老刘" ], "sort": [ { "DOB": { "order": "asc" } }, { "user.keyword": { "order": "asc" } } ] }
在这里在 search_after 中，我们把上一个搜索结果的 sort 值放进来。 显示的结果为：
{ "took" : 47, "timed_out" : false, "_shards" : { "total" : 1, "successful" : 1, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : { "value" : 5, "relation" : "eq" }, "max_score" : null, "hits" : [ { "_index" : "twitter", "_type" : "_doc", "_id" : "3", "_score" : null, "_source" : { "user" : "东城区-李四", "DOB" : "1982-01-01", "message" : "happy birthday!", "uid" : 4, "age" : 30, "city" : "北京", "province" : "北京", "country" : "中国", "address" : "中国北京市东城区", "location" : { "lat" : "39.893801", "lon" : "116.408986" } }, "sort" : [ 378691200000, "东城区-李四" ] }, { "_index" : "twitter", "_type" : "_doc", "_id" : "4", "_score" : null, "_source" : { "user" : "朝阳区-老贾", "DOB" : "1983-01-01", "message" : "123,gogogo", "uid" : 5, "age" : 35, "city" : "北京", "province" : "北京", "country" : "中国", "address" : "中国北京市朝阳区建国门", "location" : { "lat" : "39.718256", "lon" : "116.367910" } }, "sort" : [ 410227200000, "朝阳区-老贾" ] } ] } }
注意：当我们使用 search_after 时，from 值必须设置为 0 或者 -1。
search_after 不是*跳转到随机页面而是并行 scroll 多个查询的解决方案。 它与 scroll API 非常相似，但与它不同，search_after 参数是无状态的，它始终针对最新版本的搜索器进行解析。 因此，排序顺序可能会在步行期间发生变化，具体取决于索引的更新和删除。