1.測試數據準備

首先，我們創建一個名為 blog_posts 的索引，并插入一些測試數據：

PUT /blog_posts
{"mappings": {"properties": {"title": { "type": "text" },"content": { "type": "text" },"author": { "type": "keyword" },"views": { "type": "integer" },"publish_date": { "type": "date" },"tags": { "type": "keyword" }}}
}

POST /blog_posts/_bulk
{"index":{}}
{"title":"Elasticsearch Basics","content":"Learn the basics of Elasticsearch and how to perform simple queries.","author":"John Doe","views":1500,"publish_date":"2023-01-15","tags":["search","database"]}
{"index":{}}
{"title":"Advanced Search Techniques","content":"Explore advanced search techniques in Elasticsearch including aggregations and filters.","author":"Jane Smith","views":3200,"publish_date":"2023-02-20","tags":["search","advanced"]}
{"index":{}}
{"title":"Data Analytics with ELK","content":"How to use the ELK stack for data analytics and visualization.","author":"John Doe","views":2800,"publish_date":"2023-03-10","tags":["analytics","elk"]}
{"index":{}}
{"title":"Elasticsearch Performance Tuning","content":"Tips and tricks for optimizing Elasticsearch performance in production environments.","author":"Mike Johnson","views":4200,"publish_date":"2023-04-05","tags":["performance","optimization"]}
{"index":{}}
{"title":"Kibana Dashboard Guide","content":"Creating effective dashboards in Kibana for monitoring and analysis.","author":"Jane Smith","views":1900,"publish_date":"2023-05-12","tags":["kibana","visualization"]}

2.排序功能

能排序的字段都具備正排索引，單 text 類型字段是不可以排序的。如果要使 text 字段支持排序、聚合，則需要開啟 fielddata。

sort 是和 query 平級的，并不會被 query 包含。

2.1 簡單字段排序

GET /blog_posts/_search
{"query": {"match_all": {}},"sort": [{"views": {"order": "desc"}}]
}

2.2 多字段排序

GET /blog_posts/_search
{"query": {"match_all": {}},"sort": [{"author": {"order": "asc"}},{"views": {"order": "desc"}}]
}

2.3 日期排序

GET /blog_posts/_search
{"query": {"match_all": {}},"sort": [{"publish_date": {"order": "desc"}}]
}

3.分頁功能

Elasticsearch 支持對查詢結果進行分頁處理，允許用戶逐步獲取和瀏覽大量數據。

在編寫查詢語句時，可通過再請求體中添加 from 和 size 字段實現分頁。from 表示結果集的起始位置，而 size 表示每頁返回的文檔數量。

如果將 from 設置為 $11$，size 設置為 $5$，則返回的是第 $10$ ~ $14$ 條數據（默認從第 $0$ 條開始）。

3.1 基礎分頁

GET /blog_posts/_search
{"query": {"match_all": {}},"from": 0,"size": 2,"sort": [{"publish_date": {"order": "desc"}}]
}

3.2 深度分頁（不推薦大數據量使用）

深度分頁 指的是在 Elasticsearch 中查詢結果集 非常靠后的頁碼（例如第 $1000$ 頁，每頁 $10$ 條數據，即 from=10000）。它通常表現為使用 from + size 參數組合來獲取遠端的分頁數據。

? 不推薦的詳細原因可參考我的另一篇博客：《【Elasticsearch】深度分頁及其替代方案》。

當然，我們這里測試的數據沒有那么多。

GET /blog_posts/_search
{"query": {"match_all": {}},"from": 3,"size": 2
}

3.3 使用 search_after 進行高效分頁

首先獲取第一頁：

GET /blog_posts/_search
{"query": {"match_all": {}},"size": 2,"sort": [{"views": {"order": "desc"}},{"_id": {"order": "asc"}}]
}

然后使用最后一個結果的排序值獲取下一頁：

GET /blog_posts/_search
{"query": {"match_all": {}},"size": 2,"search_after": [3200, "上一頁最后一個文檔的ID"],"sort": [{"views": {"order": "desc"}},{"_id": {"order": "asc"}}]
}

4.綜合示例：高亮+排序+分頁

GET /blog_posts/_search
{"query": {"multi_match": {"query": "search","fields": ["title", "content"]}},"highlight": {"fields": {"title": {},"content": {"fragment_size": 100,"number_of_fragments": 2}}},"sort": [{"views": {"order": "desc"}}],"from": 0,"size": 3
}

5.實踐建議

功能	實踐建議
高亮	對于大文本字段，限制 fragment_size 和 number_of_fragments 以提高性能。 考慮使用 require_field_match: true 來只高亮查詢中指定的字段。
排序	對于文本字段排序，使用 .keyword 子字段或設置 fielddata: true。 避免對未索引或分析的字段進行排序。 對于分頁場景，使用包含唯一值的排序條件（如 _id）。
分頁	避免深度分頁（超過 $1000$ 條記錄）)，使用 search_after 代替。 對于無限滾動等場景，優先考慮 search_after 而不是 from/size。 考慮使用滾動 API（Scroll API）對于大數據量導出場景。