電商系統中的ID是如何生成的

{"type":"doc","content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"strong","attrs":{}}],"text":"分佈式ID","attrs":{}},{"type":"text","text":"， 我們可能都聽過分佈式系統，分佈式，分佈式ID可能比較少，因爲業務，方向以及系統維護的方面出發，現在的互聯網中的項目，多數都需要一個全局且唯一，有增量趨勢的","attrs":{}},{"type":"text","marks":[{"type":"strong","attrs":{}}],"text":"標識","attrs":{}},{"type":"text","text":"。目前用的可能是MySQL的自增主鍵，UUID，時間戳等，但是對於日益增長的消息系統，點評，支付等具體操作，都需要一個穩定，全局唯一，且有明顯自增趨勢的ID作爲唯一標識。","attrs":{}}]},{"type":"heading","attrs":{"align":null,"level":2},"content":[{"type":"text","text":"一個分佈式全局ID的硬性要求","attrs":{}}]},{"type":"image","attrs":{"src":"https://static001.geekbang.org/infoq/4b/4b118ef59c5452302bd7c878898ceee5.png","alt":null,"title":null,"style":[{"key":"width","value":"75%"},{"key":"bordertype","value":"none"}],"href":null,"fromPaste":true,"pastePass":true}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"其中信息安全，可能有的小夥伴不太瞭解，你每次請求獲取的ID（查詢操作），這個如果是遞增，我們就能直觀的判斷出有信息，多少人，這是第多少個等，這屬於敏感信息泄露的範疇， 安全還是很重要的；","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"規則我們確定之後，我們就要求生成這個ID系統的要求，之前是對於生成","attrs":{}},{"type":"text","marks":[{"type":"strong","attrs":{}}],"text":"單個一個ID的要求，","attrs":{}}]},{"type":"heading","attrs":{"align":null,"level":2},"content":[{"type":"text","text":"對ID系統生成的可用性要求","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"因爲是存在於分佈式系統的，那也就是我們比較熟悉的，","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"image","attrs":{"src":"https://static001.geekbang.org/infoq/2e/2e7e40799820797ef1e69611ccd6e3b0.png","alt":null,"title":null,"style":[{"key":"width","value":"75%"},{"key":"bordertype","value":"none"}],"href":null,"fromPaste":true,"pastePass":true}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"strong","attrs":{}}],"text":"高可用","attrs":{}},{"type":"text","text":"：發起一個獲取分佈式ID的請求時，必須保證服務器在99.999%的時候給我創建成功","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"strong","attrs":{}}],"text":"低延遲","attrs":{}},{"type":"text","text":"： 獲取分佈式ID,服務器響應快速，不能有高延遲，會有誤差","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"strong","attrs":{}}],"text":"高併發","attrs":{}},{"type":"text","text":"： 一秒鐘可以獲取10萬左右的ID,而且要成功，服務器要扛得住","attrs":{}}]},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"情景再現：","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"面試中，對於面試者做過的項目，面試官一般會採用聊集羣，QPS等情況驗證，項目的真實性， 其中分佈式ID就屬於具體實現了，一般會問：","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"你們項目是，分佈式微服務，集羣化部署，電商的這個系統中對於訂單，支付等","attrs":{}},{"type":"text","marks":[{"type":"strong","attrs":{}}],"text":"全局ID是如何生成的？","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"雪花算法 snowFlake；","attrs":{}}]},{"type":"heading","attrs":{"align":null,"level":2},"content":[{"type":"text","text":"現在系統常用的ID生成方式：","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"數據庫自增，UUID ，時間戳；Redis集羣","attrs":{}}]},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"(1) 數據庫自增（mysql自增）","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"其中數據庫自增，對於單體系統，後臺系統用的比較多，因爲併發小，使用人數也少，適合於小系統，QPS一般幾十到一百左右的，","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"缺點：對於數據敏感的場景不宜使用， 且支撐不了分佈式場景，自增之後還是會還原爲原來的數值","attrs":{}}]},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"(2) UUID","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"UUID用的是比較普遍的一個ID, 因爲全局唯一，但是它存在很多的問題","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"UUID的缺點：","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"strong","attrs":{}}],"text":"無序","attrs":{}},{"type":"text","text":"，且無法預測生成順序，無法有效的呈現遞增趨勢","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"strong","attrs":{}}],"text":"存儲","attrs":{}},{"type":"text","text":"，字段很長，耗費數據庫資源，對於特點環境存在一些問題，","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"優點：只剩下全局唯一了","attrs":{}}]},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"（3）時間戳","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"一般可以使用時間戳加具體的業務ID 來規定，但是用的也比較少","attrs":{}}]},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"（4）基於Redis集羣生成策略","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"因爲Redis特性是基於單線程，所以用它生成ID操作是原子性的，集羣化可以實現，","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"通過設備集羣的增長步長，起始值，就可以","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"比如Redis集羣有五臺機器， 可以初始化爲每臺Redis的值 1，2，3，4，5；步長是5；","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"各個Redis生成的Id爲：","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"A:1,6,11,16,21,...B:2,7,12,17.22,...C:3,8,13,18,23,...D:4,9,14,19,24,...E:5,10,15,20,25,...","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"雖然可以實現，但是配置Redis集羣后， 要實現數據丟失怎麼辦，key的失效時間等等，","attrs":{}},{"type":"text","marks":[{"type":"strong","attrs":{}}],"text":"不是不能做，是殺雞焉用牛刀","attrs":{}},{"type":"text","text":"，對的；","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"然後就到了我們今天的主題：","attrs":{}}]},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"(5)Twitter開源的snowflake;","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"Snowflake（雪花） 是一項服務，用於爲 Twitter 內的對象（推文，直接消息，用戶，集合，列表等）生成唯一的 ID。這些 IDs 是唯一的 64 位無符號整數，它們","attrs":{}},{"type":"text","marks":[{"type":"strong","attrs":{}}],"text":"基於時間","attrs":{}},{"type":"text","text":"，而不是順序的。完整的 ID 由時間戳，工作機器編號和序列號組成。當在 API 中使用 JSON 數據格式時，請務必始終使用 id_str 字段而不是 id，這一點很重要。這是由於處理JSON 的 Javascript 和其他語言計算大整數的方式造成的。如果你遇到 id 和 id_str 似乎不匹配的情況，這是因爲你的環境已經解析了 id 整數，並在處理的過程中仔細分析了這個數字。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"Twitter的分佈式雪花算法SnowFlake,經測試snowflake每秒能夠產生","attrs":{}},{"type":"text","marks":[{"type":"strong","attrs":{}}],"text":"26萬","attrs":{}},{"type":"text","text":"個自增可排序的ID1、twitter的SnowFlake生成ID能夠按照時間有序生成2、SnowFlake算法生成id的結果是一個64bit大小的整數，爲一個Long型（轉換成字符串後長度最多19).3、分佈式系統內不會產生ID碰撞（由datacenter和workerld作區分）並且效率較高。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"分佈式系統中，有一些需要使用全局唯一ID的場景，生成ID的基本要求","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"1.在分佈式的環境下必須全局且唯一。","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"strong","attrs":{}}],"text":"對比","attrs":{}},{"type":"text","text":"2.一般都需要單調遞增，因爲一般唯一ID都會存到數據庫，而Intodb的特性就是將內容存儲在主鍵索引樹上的葉子節點，而且是從左往右，遞增的，所以考慮到數據庫性能，一般生成的id也最好是單調遞增。爲了防止ID衝突可以使用36位的UUID,但是UUID有一些缺點，首先他相對比較長，另外UUID-般是無序的","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"image","attrs":{"src":"https://static001.geekbang.org/infoq/3e/3ea20135e6f12be4ec73326ff50ae2c6.png","alt":null,"title":null,"style":[{"key":"width","value":"75%"},{"key":"bordertype","value":"none"}],"href":null,"fromPaste":true,"pastePass":true}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"image","attrs":{"src":"https://static001.geekbang.org/infoq/71/717d1187ae1d9f10c0bfea63a8719f6d.png","alt":null,"title":null,"style":[{"key":"width","value":"75%"},{"key":"bordertype","value":"none"}],"href":null,"fromPaste":true,"pastePass":true}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"strong","attrs":{}}],"text":"snowflake是中可以用69年是否成立？","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"雪花算法可以高度唯一和可用性時間長：作比較， 41位的1二進制數字，對於十進制來說，是多少呢；十進制的數字是：","attrs":{}},{"type":"text","marks":[{"type":"strong","attrs":{}}],"text":"2199023255551","attrs":{}},{"type":"text","text":"https://tool.lu/hexconvert/ 進制轉換的工具箱","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"我做了個demo來證明:","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"image","attrs":{"src":"https://static001.geekbang.org/infoq/9a/9abafc897eb6a12c250166899897e402.png","alt":null,"title":null,"style":[{"key":"width","value":"75%"},{"key":"bordertype","value":"none"}],"href":null,"fromPaste":true,"pastePass":true}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"其中主要設置的是 10位的工作進程位；-","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"一般分爲數據中心和機器位","attrs":{}}]},{"type":"heading","attrs":{"align":null,"level":2},"content":[{"type":"text","text":"生成snowFlake的ID","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"我們以springboot的項目來構建這個snowFlake的ID生成，","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"依賴：","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"codeblock","attrs":{"lang":"text"},"content":[{"type":"text","text":" \n \n cn.hutool\n hutool-captcha\n 5.6.0\n \n","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"這裏我們表示的是Java代碼庫中，hutool的類庫，調用已經封裝好的IdUtil就好","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"codeblock","attrs":{"lang":"text"},"content":[{"type":"text","text":"package com.generate;\n\nimport cn.hutool.core.lang.Snowflake;\nimport cn.hutool.core.net.NetUtil;\nimport cn.hutool.core.util.IdUtil;\nimport lombok.extern.slf4j.Slf4j;\nimport org.springframework.stereotype.Component;\n\nimport javax.annotation.PostConstruct;\n\n\n/**\n * 生成全局ID\n * 雪花算法Tiwwer\n */\n\n@Component\n@Slf4j\npublic class SnowFlakeUtil {\n\n //主要配置工作位十位，其中5位是機器位（節點或者是具體哪臺機器），5位數數據中心\n\n private Long workerID = 0L;\n\n private Long datecenter = 1L;\n\n private Snowflake snowflake = IdUtil.createSnowflake(workerID, datecenter);\n\n @PostConstruct\n private void init() {\n\n try {\n //當前機器的IP\n workerID = NetUtil.ipv4ToLong(NetUtil.getLocalhostStr());\n log.info(\"當前機器的workerID{}\", workerID);\n } catch (Exception e) {\n log.warn(\"獲取機器ID失敗\", e);\n workerID = Long.valueOf(NetUtil.getLocalhost().hashCode());\n log.info(\"當前機器workID\", workerID);\n }\n\n\n }\n\n //簡單版本\n public synchronized Long createSnowFlakeID() {\n //生成的ID加鎖synchronized\n return snowflake.nextId();\n\n }\n\n //全局版本的\n public synchronized long showFlakeID(long workId, long datacenterID) {\n Snowflake snowflake = IdUtil.createSnowflake(workerID, datecenter);\n return snowflake.nextId();\n }\n\n\n public static void main(String[] args) {\n System.out.println(new SnowFlakeUtil().createSnowFlakeID());\n// 1401136955063926784\n }\n\n\n}\n","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"這裏是簡單的一個版本，與真實項目中有差異，差異主要是體現在參數配置中，","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"雖然雪花算法可以生成，唯一且自增的ID ,但是它也存在問題，是關於時間戳的；","attrs":{}}]},{"type":"heading","attrs":{"align":null,"level":2},"content":[{"type":"text","text":"總結：","attrs":{}}]},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"優點：","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"​ 1.不依賴與第三方系統（MySQL，Redis等），穩定性，生成ID的性能非常高","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"​ 2.毫秒數在高位，自增序列在低位，整個ID 都是有趨勢遞增的；","attrs":{}}]},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"缺點：","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"依賴於機器時鐘，也就是對錶時間，如果機器回撥，會導致重複ID生成；","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"這種情況一般會發生在分佈式環境中，每臺機器上的時鐘不可能完全同步，有時候會出現不是全局遞增的情況","attrs":{}}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"但是對於中小公司，此缺點可以忽略， 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