使用scoll滚动搜索

如果一次性要查出来比如10万条数据，那么性能会很差，此时一般会采取用scoll滚动查询，一批一批的查，直到所有数据都查询完处理完

使用scoll滚动搜索，可以先搜索一批数据，然后下次再搜索一批数据，以此类推，直到搜索出全部的数据来

scoll搜索会在第一次搜索的时候，保存一个当时的视图快照，之后只会基于该旧的视图快照提供数据搜索，如果这个期间数据变更，是不会让用户看到的

采用基于_doc进行排序的方式，性能较高

每次发送scroll请求，我们还需要指定一个scoll参数，指定一个时间窗口，每次搜索请求只要在这个时间窗口内能完成就可以了

GET /test_index/test_type/_search?scroll=1m
{
  "query": {
    "match_all": {}
  },
  "sort": [ "_doc" ],
  "size": 3
}

返回结果:

{
  "_scroll_id": "DnF1ZXJ5VGhlbkZldGNoBQAAAAAAACxeFjRvbnNUWVZaVGpHdklqOV9zcFd6MncAAAAAAAAsYBY0b25zVFlWWlRqR3ZJajlfc3BXejJ3AAAAAAAALF8WNG9uc1RZVlpUakd2SWo5X3NwV3oydwAAAAAAACxhFjRvbnNUWVZaVGpHdklqOV9zcFd6MncAAAAAAAAsYhY0b25zVFlWWlRqR3ZJajlfc3BXejJ3",
  "took": 5,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "failed": 0
  },
  "hits": {
    "total": 10,
    "max_score": null,
    "hits": [
      {
        "_index": "test_index",
        "_type": "test_type",
        "_id": "8",
        "_score": null,
        "_source": {
          "test_field": "test client 2"
        },
        "sort": [
          0
        ]
      },
      {
        "_index": "test_index",
        "_type": "test_type",
        "_id": "6",
        "_score": null,
        "_source": {
          "test_field": "tes test"
        },
        "sort": [
          0
        ]
      },
      {
        "_index": "test_index",
        "_type": "test_type",
        "_id": "AVp4RN0bhjxldOOnBxaE",
        "_score": null,
        "_source": {
          "test_content": "my test"
        },
        "sort": [
          0
        ]
      }
    ]
  }
}

获得的结果会有一个scoll_id，下一次再发送scoll请求的时候，必须带上这个scoll_id

GET /_search/scroll
{
    "scroll": "1m", 
    "scroll_id" : "DnF1ZXJ5VGhlbkZldGNoBQAAAAAAACxeFjRvbnNUWVZaVGpHdklqOV9zcFd6MncAAAAAAAAsYBY0b25zVFlWWlRqR3ZJajlfc3BXejJ3AAAAAAAALF8WNG9uc1RZVlpUakd2SWo5X3NwV3oydwAAAAAAACxhFjRvbnNUWVZaVGpHdklqOV9zcFd6MncAAAAAAAAsYhY0b25zVFlWWlRqR3ZJajlfc3BXejJ3"
}

scoll，看起来挺像分页的，但是其实使用场景不一样。分页主要是用来一页一页搜索，给用户看的；scoll主要是用来一批一批检索数据，让系统进行处理的

资料：

Previousfield索引两次来解决字符串排序 Next分词器

Last updated 6 years ago

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{ "_scroll_id": "DnF1ZXJ5VGhlbkZldGNoBQAAAAAAACxeFjRvbnNUWVZaVGpHdklqOV9zcFd6MncAAAAAAAAsYBY0b25zVFlWWlRqR3ZJajlfc3BXejJ3AAAAAAAALF8WNG9uc1RZVlpUakd2SWo5X3NwV3oydwAAAAAAACxhFjRvbnNUWVZaVGpHdklqOV9zcFd6MncAAAAAAAAsYhY0b25zVFlWWlRqR3ZJajlfc3BXejJ3", "took": 5, "timed_out": false, "_shards": { "total": 5, "successful": 5, "failed": 0 }, "hits": { "total": 10, "max_score": null, "hits": [ { "_index": "test_index", "_type": "test_type", "_id": "8", "_score": null, "_source": { "test_field": "test client 2" }, "sort": [ 0 ] }, { "_index": "test_index", "_type": "test_type", "_id": "6", "_score": null, "_source": { "test_field": "tes test" }, "sort": [ 0 ] }, { "_index": "test_index", "_type": "test_type", "_id": "AVp4RN0bhjxldOOnBxaE", "_score": null, "_source": { "test_content": "my test" }, "sort": [ 0 ] } ] } }

GET /_search/scroll { "scroll": "1m", "scroll_id" : "DnF1ZXJ5VGhlbkZldGNoBQAAAAAAACxeFjRvbnNUWVZaVGpHdklqOV9zcFd6MncAAAAAAAAsYBY0b25zVFlWWlRqR3ZJajlfc3BXejJ3AAAAAAAALF8WNG9uc1RZVlpUakd2SWo5X3NwV3oydwAAAAAAACxhFjRvbnNUWVZaVGpHdklqOV9zcFd6MncAAAAAAAAsYhY0b25zVFlWWlRqR3ZJajlfc3BXejJ3" }