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          避免 OOM,高效導(dǎo)出百萬級數(shù)據(jù)的 SpringBoot 實現(xiàn)方案

          共 11961字,需瀏覽 24分鐘

           ·

          2023-04-01 01:10

          大家好,我是小富~

          前言

          動態(tài)數(shù)據(jù)導(dǎo)出是一般項目都會涉及到的功能。它的基本實現(xiàn)邏輯就是從mysql查詢數(shù)據(jù),加載到內(nèi)存,然后從內(nèi)存創(chuàng)建excel或者csv,以流的形式響應(yīng)給前端。

          • 參考:https://grokonez.com/spring-framework/spring-boot/excel-file-download-from-springboot-restapi-apache-poi-mysql。

          SpringBoot下載excel基本都是這么干。

          雖然這是個可行的方案,然而一旦mysql數(shù)據(jù)量太大,達到十萬級,百萬級,千萬級,大規(guī)模數(shù)據(jù)加載到內(nèi)存必然會引起OutofMemoryError。

          要考慮如何避免OOM,一般有兩個方面的思路。

          一方面就是盡量不做唄,先懟產(chǎn)品下面幾個問題?。?/p>

          • 我們?yōu)槭裁匆獙?dǎo)出這么多數(shù)據(jù)呢?誰傻到去看這么大的數(shù)據(jù)啊,這個設(shè)計是不是合理的呢?
          • 怎么做好權(quán)限控制?百萬級數(shù)據(jù)導(dǎo)出你確定不會泄露商業(yè)機密?
          • 如果要導(dǎo)出百萬級數(shù)據(jù),那為什么不直接找大數(shù)據(jù)或者DBA來干呢?然后以郵件形式傳遞不行嗎?
          • 為什么要通過后端的邏輯來實現(xiàn),不考慮時間成本,流量成本嗎?
          • 如果通過分頁導(dǎo)出,每次點擊按鈕只導(dǎo)2萬條,分批導(dǎo)出難道不能滿足業(yè)務(wù)需求嗎?

          如果產(chǎn)品說 “甲方是爸爸,你去和甲方說啊”,“客戶說這個做出來,才考慮付尾款!”,如果客戶的確缺根筋要讓你這樣搞, 那就只能從技術(shù)上考慮如何實現(xiàn)了。

          從技術(shù)上講,為了避免OOM,我們一定要注意一個原則:

          不能將全量數(shù)據(jù)一次性加載到內(nèi)存之中。

          全量加載不可行,那我們的目標就是如何實現(xiàn)數(shù)據(jù)的分批加載了。實事上,Mysql本身支持Stream查詢,我們可以通過Stream流獲取數(shù)據(jù),然后將數(shù)據(jù)逐條刷入到文件中,每次刷入文件后再從內(nèi)存中移除這條數(shù)據(jù),從而避免OOM。

          由于采用了數(shù)據(jù)逐條刷入文件,而且數(shù)據(jù)量達到百萬級,所以文件格式就不要采用excel了,excel2007最大才支持104萬行的數(shù)據(jù)。這里推薦:

          以csv代替excel。

          考慮到當前SpringBoot持久層框架通常為JPA和mybatis,我們可以分別從這兩個框架實現(xiàn)百萬級數(shù)據(jù)導(dǎo)出的方案。

          JPA實現(xiàn)百萬級數(shù)據(jù)導(dǎo)出

          • 具體方案不妨參考:http://knes1.github.io/blog/2015/2015-10-19-streaming-mysql-results-using-java8-streams-and-spring-data.html。

          實現(xiàn)項目對應(yīng):

          • https://github.com/knes1/todo

          核心注解如下,需要加入到具體的Repository之上。方法的返回類型定義成Stream。Integer.MIN_VALUE告訴jdbc driver逐條返回數(shù)據(jù)。

                
                @QueryHints(value?=?@QueryHint(name?=?HINT_FETCH_SIZE,?value?=?""?+?Integer.MIN_VALUE))
          @Query(value?=?"select?t?from?Todo?t")
          Stream<Todo>?streamAll();

          此外還需要在Stream處理數(shù)據(jù)的方法之上添加@Transactional(readOnly = true),保證事物是只讀的。

          同時需要注入javax.persistence.EntityManager,通過detach從內(nèi)存中移除已經(jīng)使用后的對象。

                
                @RequestMapping(value?=?"/todos.csv",?method?=?RequestMethod.GET)
          @Transactional(readOnly?=?true)
          public?void?exportTodosCSV(HttpServletResponse?response)?{
          ?response.addHeader("Content-Type",?"application/csv");
          ?response.addHeader("Content-Disposition",?"attachment;?filename=todos.csv");
          ?response.setCharacterEncoding("UTF-8");
          ?try(Stream<Todo>?todoStream?=?todoRepository.streamAll())?{
          ??PrintWriter?out?=?response.getWriter();
          ??todoStream.forEach(rethrowConsumer(todo?->?{
          ???String?line?=?todoToCSV(todo);
          ???out.write(line);
          ???out.write("\n");
          ???entityManager.detach(todo);
          ??}));
          ??out.flush();
          ?}?catch?(IOException?e)?{
          ??log.info("Exception?occurred?"?+?e.getMessage(),?e);
          ??throw?new?RuntimeException("Exception?occurred?while?exporting?results",?e);
          ?}
          }

          MyBatis實現(xiàn)百萬級數(shù)據(jù)導(dǎo)出

          MyBatis實現(xiàn)逐條獲取數(shù)據(jù),必須要自定義ResultHandler,然后在mapper.xml文件中,對應(yīng)的select語句中添加fetchSize="-2147483648"。

          f8b19e8c6d994735348b772f7c292fdc.webp

          最后將自定義的ResultHandler傳給SqlSession來執(zhí)行查詢,并將返回的結(jié)果進行處理。

          MyBatis實現(xiàn)百萬級數(shù)據(jù)導(dǎo)出的具體實例

          以下是基于MyBatis Stream導(dǎo)出的完整的工程樣例,我們將通過對比Stream文件導(dǎo)出和傳統(tǒng)方式導(dǎo)出的內(nèi)存占用率的差異,來驗證Stream文件導(dǎo)出的有效性。

          我們先定義一個工具類DownloadProcessor,它內(nèi)部封裝一個HttpServletResponse對象,用來將對象寫入到csv。

                
                public?class?DownloadProcessor?{
          ????private?final?HttpServletResponse?response;
          ?????
          ????public?DownloadProcessor(HttpServletResponse?response)?{
          ????????this.response?=?response;
          ????????String?fileName?=?System.currentTimeMillis()?+?".csv";
          ????????this.response.addHeader("Content-Type",?"application/csv");
          ????????this.response.addHeader("Content-Disposition",?"attachment;?filename="+fileName);
          ????????this.response.setCharacterEncoding("UTF-8");
          ????}
          ?????
          ????public?<E>?void?processData(E?record)?{
          ????????try?{
          ????????????response.getWriter().write(record.toString());?//如果是要寫入csv,需要重寫toString,屬性通過","分割
          ????????????response.getWriter().write("\n");
          ????????}catch?(IOException?e){
          ????????????e.printStackTrace();
          ????????}
          ????}
          }

          然后通過實現(xiàn)org.apache.ibatis.session.ResultHandler,自定義我們的ResultHandler,它用于獲取java對象,然后傳遞給上面的DownloadProcessor處理類進行寫文件操作:

                
                public?class?CustomResultHandler?implements?ResultHandler?{

          ????private?final?DownloadProcessor?downloadProcessor;
          ?????
          ????public?CustomResultHandler(
          ????????????DownloadProcessor?downloadProcessor)
          ?
          {
          ????????super();
          ????????this.downloadProcessor?=?downloadProcessor;
          ????}
          ?????
          ????@Override
          ????public?void?handleResult(ResultContext?resultContext)?{
          ????????Authors?authors?=?(Authors)resultContext.getResultObject();
          ????????downloadProcessor.processData(authors);
          ????}
          }

          實體類:

                
                public?class?Authors?{
          ????private?Integer?id;
          ????private?String?firstName;
          ?????
          ????private?String?lastName;
          ?????
          ????private?String?email;
          ?????
          ????private?Date?birthdate;
          ?????
          ????private?Date?added;
          ?????
          ????public?Integer?getId()?{
          ????????return?id;
          ????}
          ?????
          ????public?void?setId(Integer?id)?{
          ????????this.id?=?id;
          ????}
          ?????
          ????public?String?getFirstName()?{
          ????????return?firstName;
          ????}
          ?????
          ????public?void?setFirstName(String?firstName)?{
          ????????this.firstName?=?firstName?==?null???null?:?firstName.trim();
          ????}
          ?????
          ????public?String?getLastName()?{
          ????????return?lastName;
          ????}
          ?????
          ????public?void?setLastName(String?lastName)?{
          ????????this.lastName?=?lastName?==?null???null?:?lastName.trim();
          ????}
          ?????
          ????public?String?getEmail()?{
          ????????return?email;
          ????}
          ?????
          ????public?void?setEmail(String?email)?{
          ????????this.email?=?email?==?null???null?:?email.trim();
          ????}
          ?????
          ????public?Date?getBirthdate()?{
          ????????return?birthdate;
          ????}
          ?????
          ????public?void?setBirthdate(Date?birthdate)?{
          ????????this.birthdate?=?birthdate;
          ????}
          ?????
          ????public?Date?getAdded()?{
          ????????return?added;
          ????}
          ?????
          ????public?void?setAdded(Date?added)?{
          ????????this.added?=?added;
          ????}
          ?????
          ????@Override
          ????public?String?toString()?{
          ????????return?this.id?+?","?+?this.firstName?+?","?+?this.lastName?+?","?+?this.email?+?","?+?this.birthdate?+?","?+?this.added;
          ????}
          }

          Mapper接口:

                
                public?interface?AuthorsMapper?{
          ???List<Authors>?selectByExample(AuthorsExample?example);
          ????
          ???List<Authors>?streamByExample(AuthorsExample?example);?//以stream形式從mysql獲取數(shù)據(jù)
          }

          Mapper xml文件核心片段,以下兩條select的唯一差異就是在stream獲取數(shù)據(jù)的方式中多了一條屬性:fetchSize="-2147483648"

                
                <select?id="selectByExample"?parameterType="com.alphathur.mysqlstreamingexport.domain.AuthorsExample"?resultMap="BaseResultMap">
          ????select
          ????<if?test="distinct">
          ??????distinct
          ????</if>
          ????'false'?as?QUERYID,
          ????<include?refid="Base_Column_List"?/>
          ????from?authors
          ????<if?test="_parameter?!=?null">
          ??????<include?refid="Example_Where_Clause"?/>
          ????</if>
          ????<if?test="orderByClause?!=?null">
          ??????order?by?${orderByClause}
          ????</if>
          ??</select>
          ??<select?id="streamByExample"?fetchSize="-2147483648"?parameterType="com.alphathur.mysqlstreamingexport.domain.AuthorsExample"?resultMap="BaseResultMap">
          ????select
          ????<if?test="distinct">
          ??????distinct
          ????</if>
          ????'false'?as?QUERYID,
          ????<include?refid="Base_Column_List"?/>
          ????from?authors
          ????<if?test="_parameter?!=?null">
          ??????<include?refid="Example_Where_Clause"?/>
          ????</if>
          ????<if?test="orderByClause?!=?null">
          ??????order?by?${orderByClause}
          ????</if>
          ??</select>

          獲取數(shù)據(jù)的核心service如下,由于只做個簡單演示,就懶得寫成接口了。其中 streamDownload 方法即為stream取數(shù)據(jù)寫文件的實現(xiàn),它將以很低的內(nèi)存占用從MySQL獲取數(shù)據(jù);此外還提供traditionDownload方法,它是一種傳統(tǒng)的下載方式,批量獲取全部數(shù)據(jù),然后將每個對象寫入文件。

                
                @Service
          public?class?AuthorsService?{
          ????private?final?SqlSessionTemplate?sqlSessionTemplate;
          ????private?final?AuthorsMapper?authorsMapper;

          ????public?AuthorsService(SqlSessionTemplate?sqlSessionTemplate,?AuthorsMapper?authorsMapper)?{
          ????????this.sqlSessionTemplate?=?sqlSessionTemplate;
          ????????this.authorsMapper?=?authorsMapper;
          ????}

          ????/**
          ?????*?stream讀數(shù)據(jù)寫文件方式
          ?????*?@param?httpServletResponse
          ?????*?@throws?IOException
          ?????*/

          ????public?void?streamDownload(HttpServletResponse?httpServletResponse)
          ????????????throws?IOException?
          {
          ????????AuthorsExample?authorsExample?=?new?AuthorsExample();
          ????????authorsExample.createCriteria();
          ????????HashMap<String,?Object>?param?=?new?HashMap<>();
          ????????param.put("oredCriteria",?authorsExample.getOredCriteria());
          ????????param.put("orderByClause",?authorsExample.getOrderByClause());
          ????????CustomResultHandler?customResultHandler?=?new?CustomResultHandler(new?DownloadProcessor?(httpServletResponse));
          ????????sqlSessionTemplate.select(
          ????????????????"com.alphathur.mysqlstreamingexport.mapper.AuthorsMapper.streamByExample",?param,?customResultHandler);
          ????????httpServletResponse.getWriter().flush();
          ????????httpServletResponse.getWriter().close();
          ????}

          ????/**
          ?????*?傳統(tǒng)下載方式
          ?????*?@param?httpServletResponse
          ?????*?@throws?IOException
          ?????*/

          ????public?void?traditionDownload(HttpServletResponse?httpServletResponse)
          ????????????throws?IOException?
          {
          ????????AuthorsExample?authorsExample?=?new?AuthorsExample();
          ????????authorsExample.createCriteria();
          ????????List<Authors>?authors?=?authorsMapper.selectByExample?(authorsExample);
          ????????DownloadProcessor?downloadProcessor?=?new?DownloadProcessor?(httpServletResponse);
          ????????authors.forEach?(downloadProcessor::processData);
          ????????httpServletResponse.getWriter().flush();
          ????????httpServletResponse.getWriter().close();
          ????}
          }

          下載的入口controller:

                
                @RestController
          @RequestMapping("download")
          public?class?HelloController?{
          ????private?final?AuthorsService?authorsService;

          ????public?HelloController(AuthorsService?authorsService)?{
          ????????this.authorsService?=?authorsService;
          ????}

          ????@GetMapping("streamDownload")
          ????public?void?streamDownload(HttpServletResponse?response)
          ????????????throws?IOException?
          {
          ????????authorsService.streamDownload(response);
          ????}

          ????@GetMapping("traditionDownload")
          ????public?void?traditionDownload(HttpServletResponse?response)
          ????????????throws?IOException?
          {
          ????????authorsService.traditionDownload?(response);
          ????}
          }???

          實體類對應(yīng)的表結(jié)構(gòu)創(chuàng)建語句:

                
                CREATE?TABLE?`authors`?(
          ??`id`?int(11)?NOT?NULL?AUTO_INCREMENT,
          ??`first_name`?varchar(50)?CHARACTER?SET?utf8?COLLATE?utf8_unicode_ci?NOT?NULL,
          ??`last_name`?varchar(50)?CHARACTER?SET?utf8?COLLATE?utf8_unicode_ci?NOT?NULL,
          ??`email`?varchar(100)?CHARACTER?SET?utf8?COLLATE?utf8_unicode_ci?NOT?NULL,
          ??`birthdate`?date?NOT?NULL,
          ??`added`?timestamp?NOT?NULL?DEFAULT?CURRENT_TIMESTAMP,
          ??PRIMARY?KEY?(`id`)
          )?ENGINE=InnoDB?AUTO_INCREMENT=10095?DEFAULT?CHARSET=utf8?COLLATE=utf8_unicode_ci;

          這里有個問題:如何短時間內(nèi)創(chuàng)建大批量測試數(shù)據(jù)到MySQL呢?一種方式是使用存儲過程 + 大殺器 select insert 語句!不太懂?

          沒關(guān)系,且看我另一篇文章 MySQL如何生成大批量測試數(shù)據(jù) 你就會明白了。如果你懶得看,我這里已經(jīng)將生成的270多萬條測試數(shù)據(jù)上傳到網(wǎng)盤,你直接下載然后通過navicat導(dǎo)入就好了。

          • 鏈接:https://pan.baidu.com/s/1hqnWU2JKlL4Tb9nWtJl4sw
          • 提取碼:nrp0

          有了測試數(shù)據(jù),我們就可以直接測試了。先啟動項目,然后打開jdk bin目錄下的 jconsole.exe

          首先我們測試傳統(tǒng)方式下載文件的內(nèi)存占用,直接瀏覽器訪問:http://localhost:8080/download/traditionDownload。

          可以看出,下載開始前內(nèi)存占用大概為幾十M,下載開始后內(nèi)存占用急速上升,峰值達到接近2.5G,即使是下載完成,堆內(nèi)存也維持一個較高的占用,這實在是太可怕了,如果生產(chǎn)環(huán)境敢這么搞,不出意外肯定內(nèi)存溢出。

          0a96a16b675e34c34b53b65dfd6d0731.webp

          接著我們測試stream方式文件下載的內(nèi)存占用,瀏覽器訪問:http://localhost:8080/download/streamDownload,當下載開始后,內(nèi)存占用也會有一個明顯的上升,但是峰值才到500M。對比于上面的方式,內(nèi)存占用率足足降低了80%!怎么樣,興奮了嗎!

          90e42bf29abfb1a9869419006a7a74ff.webp

          我們再通過記事本打開下載后的兩個文件,發(fā)現(xiàn)內(nèi)容沒有缺斤少兩,都是2727127行,完美!

          感謝閱讀,希望對你有所幫助?:)? 來源:

          blog.csdn.net/haohao_ding/article/details/123164771

              

          我是小富,下期見~

          ··········? END? ··············

                  

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