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参考：https://grokonez.com/spring-framework/spring-boot/excel-file-download-from-springboot-restapi-apache-poi-mysql。虽然这是个可行的方案，然而一旦mysql数据量太大，达到十万级，百万级，千万级，大规模数据加载到内存必然会引起OutofMemoryError。要考虑如何避免OOM，一般有两个方面的思路。
5.如果通过分页导出，每次点击按钮只导2万条，分批导出难道不能满足业务需求吗？
@QueryHints(value = @QueryHint(name = HINT_FETCH_SIZE, value = "" + Integer.MIN_VALUE)) @Query(value = "select t from Todo t") Stream<Todo> streamAll();此外还需要在Stream处理数据的方法之上添加@Transactional(readOnly = true)，保证事物是只读的。同时需要注入javax.persistence.EntityManager，通过detach从内存中移除已经使用后的对象。
@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);
}
}
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()); //如果是要写入csv,需要重写toString,属性通过","分割
response.getWriter().write("\n");
}catch (IOException e){
e.printStackTrace();
}
}
}
然后通过实现org.apache.ibatis.session.ResultHandler，自定义我们的ResultHandler，它用于获取java对象，然后传递给上面的DownloadProcessor处理类进行写文件操作：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);
}
}
实体类：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形式从mysql获取数据
}
Mapper xml文件核心片段，以下两条select的唯一差异就是在stream获取数据的方式中多了一条属性： 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>
获取数据的核心service如下，由于只做个简单演示，就懒得写成接口了。其中 streamDownload 方法即为stream取数据写文件的实现，它将以很低的内存占用从MySQL获取数据；此外还提供traditionDownload方法，它是一种传统的下载方式，批量获取全部数据，然后将每个对象写入文件。@Service
public class AuthorsService {
private final SqlSessionTemplate sqlSessionTemplate;
private final AuthorsMapper authorsMapper;
public AuthorsService(SqlSessionTemplate sqlSessionTemplate, AuthorsMapper authorsMapper) {
this.sqlSessionTemplate = sqlSessionTemplate;
this.authorsMapper = authorsMapper;
}
/**
* 堆代码 duidaima.com
* stream读数据写文件方式
* @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();
}
/**
* 传统下载方式
* @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();
}
}
下载的入口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);
}
}
实体类对应的表结构创建语句：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;这里有个问题：如何短时间内创建大批量测试数据到MySQL呢？方式是使用存储过程 + 大杀器 select insert 语句！
