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                ??碼云GVP開源項目 12k star Uniapp+ElementUI 功能強大 支持多語言、二開方便! 廣告
                ##掃描和滾屏 `scan(掃描)`搜索類型是和`scroll(滾屏)`API一起使用來從Elasticsearch里高效地取回巨大數量的結果而不需要付出深分頁的代價。 ___scroll(滾屏)___ 一個滾屏搜索允許我們做一個初始階段搜索并且持續批量從Elasticsearch里拉取結果直到沒有結果剩下。這有點像傳統數據庫里的_cursors(游標)_。 滾屏搜索會及時制作快照。這個快照不會包含任何在初始階段搜索請求后對index做的修改。它通過將舊的數據文件保存在手邊,所以可以保護index的樣子看起來像搜索開始時的樣子。 ___scan(掃描)___ 深度分頁代價最高的部分是對結果的全局排序,但如果禁用排序,就能以很低的代價獲得全部返回結果。為達成這個目的,可以采用`scan(掃描)`搜索模式。掃描模式讓Elasticsearch不排序,只要分片里還有結果可以返回,就返回一批結果。 為了使用_scan-and-scroll(掃描和滾屏)_,需要執行一個搜索請求,將`search_type` 設置成`scan`,并且傳遞一個`scroll`參數來告訴Elasticsearch滾屏應該持續多長時間。 ``` js GET /old_index/_search?search_type=scan&scroll=1m (1) { "query": { "match_all": {}}, "size": 1000 } ``` (1)保持滾屏開啟1分鐘。 這個請求的應答沒有包含任何命中的結果,但是包含了一個Base-64編碼的`_scroll_id(滾屏id)`字符串。現在我們可以將`_scroll_id` 傳遞給`_search/scroll`末端來獲取第一批結果: ``` js GET /_search/scroll?scroll=1m (1) c2Nhbjs1OzExODpRNV9aY1VyUVM4U0NMd2pjWlJ3YWlBOzExOTpRNV9aY1VyUVM4U0 <2> NMd2pjWlJ3YWlBOzExNjpRNV9aY1VyUVM4U0NMd2pjWlJ3YWlBOzExNzpRNV9aY1Vy UVM4U0NMd2pjWlJ3YWlBOzEyMDpRNV9aY1VyUVM4U0NMd2pjWlJ3YWlBOzE7dG90YW xfaGl0czoxOw== ``` -------------------------------------------------- (1) 保持滾屏開啟另一分鐘。 (2) `_scroll_id` 可以在body或者URL里傳遞,也可以被當做查詢參數傳遞。 注意,要再次指定`?scroll=1m`。滾屏的終止時間會在我們每次執行滾屏請求時刷新,所以他只需要給我們足夠的時間來處理當前批次的結果而不是所有的匹配查詢的document。 這個滾屏請求的應答包含了第一批次的結果。雖然指定了一個1000的`size` ,但是獲得了更多的document。當掃描時,`size`被應用到每一個分片上,所以我們在每個批次里最多或獲得`size * number_of_primary_shards(size*主分片數)`個document。 > ####注意: > 滾屏請求也會返回一個_新_的`_scroll_id`。每次做下一個滾屏請求時,必須傳遞前一次請求返回的`_scroll_id`。 如果沒有更多的命中結果返回,就處理完了所有的命中匹配的document。 > ####提示: > 一些[Elasticsearch官方客戶端](http://www.elasticsearch.org/guide)提供_掃描和滾屏_的小助手。小助手提供了一個對這個功能的簡單封裝。 <!-- [[scan-scroll]] === scan and scroll The `scan` search type and the `scroll` API((("scroll API", "scan and scroll"))) are used together to retrieve large numbers of documents from Elasticsearch efficiently, without paying the penalty of deep pagination. `scroll`:: + -- A _scrolled search_ allows us to((("scrolled search"))) do an initial search and to keep pulling batches of results from Elasticsearch until there are no more results left. It's a bit like a _cursor_ in ((("cursors")))a traditional database. A scrolled search takes a snapshot in time. It doesn't see any changes that are made to the index after the initial search request has been made. It does this by keeping the old data files around, so that it can preserve its ``view'' on what the index looked like at the time it started. -- `scan`:: The costly part of deep pagination is the global sorting of results, but if we disable sorting, then we can return all documents quite cheaply. To do this, we use the `scan` search type.((("scan search type"))) Scan instructs Elasticsearch to do no sorting, but to just return the next batch of results from every shard that still has results to return. To use _scan-and-scroll_, we execute a search((("scan-and-scroll"))) request setting `search_type` to((("search_type", "scan and scroll"))) `scan`, and passing a `scroll` parameter telling Elasticsearch how long it should keep the scroll open: [source,js] -------------------------------------------------- GET /old_index/_search?search_type=scan&scroll=1m <1> { "query": { "match_all": {}}, "size": 1000 } -------------------------------------------------- <1> Keep the scroll open for 1 minute. The response to this request doesn't include any hits, but does include a `_scroll_id`, which is a long Base-64 encoded((("scroll_id"))) string. Now we can pass the `_scroll_id` to the `_search/scroll` endpoint to retrieve the first batch of results: [source,js] -------------------------------------------------- GET /_search/scroll?scroll=1m <1> c2Nhbjs1OzExODpRNV9aY1VyUVM4U0NMd2pjWlJ3YWlBOzExOTpRNV9aY1VyUVM4U0 <2> NMd2pjWlJ3YWlBOzExNjpRNV9aY1VyUVM4U0NMd2pjWlJ3YWlBOzExNzpRNV9aY1Vy UVM4U0NMd2pjWlJ3YWlBOzEyMDpRNV9aY1VyUVM4U0NMd2pjWlJ3YWlBOzE7dG90YW xfaGl0czoxOw== -------------------------------------------------- <1> Keep the scroll open for another minute. <2> The `_scroll_id` can be passed in the body, in the URL, or as a query parameter. Note that we again specify `?scroll=1m`. The scroll expiry time is refreshed every time we run a scroll request, so it needs to give us only enough time to process the current batch of results, not all of the documents that match the query. The response to this scroll request includes the first batch of results. Although we specified a `size` of 1,000, we get back many more documents.((("size parameter", "in scanning"))) When scanning, the `size` is applied to each shard, so you will get back a maximum of `size * number_of_primary_shards` documents in each batch. NOTE: The scroll request also returns a _new_ `_scroll_id`. Every time we make the next scroll request, we must pass the `_scroll_id` returned by the _previous_ scroll request. When no more hits are returned, we have processed all matching documents. TIP: Some of the http://www.elasticsearch.org/guide[official Elasticsearch clients] provide _scan-and-scroll_ helpers that provide an easy wrapper around this functionality.((("clients", "providing scan-and-scroll helpers"))) -->
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