概述
一、引言
最近一周，被借调到其他部门，赶一个紧急需求，需求内容如下：
PC网页触发一条设备升级记录（下图），后台要定时批量设备更新。这里定时要用到Quartz，批量数据处理要用到SpringBatch，二者结合，可以完成该需求。
由于之前，没有用过SpringBatch，于是上网查了下资料，发现可参考的不是很多，于是只能去慢慢的翻看官方文档。
遇到不少问题，就记录一下吧。
二、代码具体实现
1、pom文件
<dependencies>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
<groupId>org.postgresql</groupId>
<artifactId>postgresql</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-jdbc</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-batch</artifactId>
</dependency>
<dependency>
<groupId>org.projectlombok</groupId>
<artifactId>lombok</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-batch</artifactId>
</dependency>
</dependencies>
2、application.yaml文件
spring:
datasource:
username: thinklink
password: thinklink
url: jdbc:postgresql://172.16.205.54:5432/thinklink
driver-class-name: org.postgresql.Driver
batch:
job:
enabled: false
server:
port: 8073
#upgrade-dispatch-base-url: http://172.16.205.125:8080/api/rpc/dispatch/command/
upgrade-dispatch-base-url: http://172.16.205.211:8080/api/noauth/rpc/dispatch/command/
# 每次批量处理的数据量，默认为5000
batch-size: 5000
3、Service实现类
触发批处理任务的入口，执行一个job
@Service("batchService")
public class BatchServiceImpl implements BatchService {
// 框架自动注入
@Autowired
private JobLauncher jobLauncher;
@Autowired
private Job updateDeviceJob;
/**
* 根据 taskId 创建一个Job
* @param taskId
* @throws Exception
*/
@Override
public void createBatchJob(String taskId) throws Exception {
JobParameters jobParameters = new JobParametersBuilder()
.addString("taskId", taskId)
.addString("uuid", UUID.randomUUID().toString().replace("-",""))
.toJobParameters();
// 传入一个Job任务和任务需要的参数
jobLauncher.run(updateDeviceJob, jobParameters);
}
}
4、SpringBatch配置类
此部分最重要（☆☆☆☆☆）
@Configuration
public class BatchConfiguration {
private static final Logger log = LoggerFactory.getLogger(BatchConfiguration.class);
@Value("${batch-size:5000}")
private int batchSize;
// 框架自动注入
@Autowired
public JobBuilderFactory jobBuilderFactory;
// 框架自动注入
@Autowired
public StepBuilderFactory stepBuilderFactory;
// 数据过滤器，对从数据库读出来的数据，注意进行操作
@Autowired
public TaskItemProcessor taskItemProcessor;
// 接收job参数
public Map<String, JobParameter> parameters;
public Object taskId;
@Autowired
private JdbcTemplate jdbcTemplate;
// 读取数据库操作
@Bean
@StepScope
public JdbcCursorItemReader<DispatchRequest> itemReader(DataSource dataSource) {
String querySql = " SELECT " +
" e. ID AS taskId, " +
" e.user_id AS userId, " +
" e.timing_startup AS startTime, " +
" u.device_id AS deviceId, " +
" d.app_name AS appName, " +
" d.compose_file AS composeFile, " +
" e.failure_retry AS failureRetry, " +
" e.tetry_times AS retryTimes, " +
" e.device_managered AS deviceManagered " +
" FROM " +
" eiot_upgrade_task e " +
" LEFT JOIN eiot_upgrade_device u ON e. ID = u.upgrade_task_id " +
" LEFT JOIN eiot_app_detail d ON e.app_id = d. ID " +
" WHERE " +
" ( " +
" u.device_upgrade_status = 0 " +
" OR u.device_upgrade_status = 2" +
" )" +
" AND e.tetry_times > u.retry_times " +
" AND e. ID = ?";
return new JdbcCursorItemReaderBuilder<DispatchRequest>()
.name("itemReader")
.sql(querySql)
.dataSource(dataSource)
.queryArguments(new Object[]{parameters.get("taskId").getValue()})
.rowMapper(new DispatchRequest.DispatchRequestRowMapper())
.build();
}
// 将结果写回数据库
@Bean
@StepScope
public ItemWriter<ProcessResult> itemWriter() {
return new ItemWriter<ProcessResult>() {
private int updateTaskStatus(DispatchRequest dispatchRequest, int status) {
log.info("update taskId: {}, deviceId: {} to status {}", dispatchRequest.getTaskId(), dispatchRequest.getDeviceId(), status);
Integer retryTimes = jdbcTemplate.queryForObject(
"select retry_times from eiot_upgrade_device where device_id = ? and upgrade_task_id = ?",
new Object[]{ dispatchRequest.getDeviceId(), dispatchRequest.getTaskId()}, Integer.class
);
retryTimes += 1;
int updateCount = jdbcTemplate.update("update eiot_upgrade_device set device_upgrade_status = ?, retry_times = ? " +
"where device_id = ? and upgrade_task_id = ?", status, retryTimes, dispatchRequest.getDeviceId(), dispatchRequest.getTaskId());
if (updateCount <= 0) {
log.warn("no task updated");
} else {
log.info("count of {} task updated", updateCount);
}
// 最后一次重试
if (status == STATUS_DISPATCH_FAILED && retryTimes == dispatchRequest.getRetryTimes()) {
log.info("the last retry of {} failed, inc deviceManagered", dispatchRequest.getTaskId());
return 1;
} else {
return 0;
}
}
@Override
@Transactional
public void write(List<? extends ProcessResult> list) throws Exception {
Map taskMap = jdbcTemplate.queryForMap(
"select device_managered, device_count, task_status from eiot_upgrade_task where id = ?",
list.get(0).getDispatchRequest().getTaskId() // 我们认定一个批量里面，taskId都是一样的
);
int deviceManagered = (int)taskMap.get("device_managered");
Integer deviceCount = (Integer) taskMap.get("device_count");
if (deviceCount == null) {
log.warn("deviceCount of task {} is null", list.get(0).getDispatchRequest().getTaskId());
}
int taskStatus = (int)taskMap.get("task_status");
for (ProcessResult result: list) {
deviceManagered += updateTaskStatus(result.getDispatchRequest(), result.getStatus());
}
if (deviceCount != null && deviceManagered == deviceCount) {
taskStatus = 2; //任务状态 0:待升级，1:升级中，2:已完成
}
jdbcTemplate.update("update eiot_upgrade_task set device_managered = ?, task_status = ? " +
"where id = ?", deviceManagered, taskStatus, list.get(0).getDispatchRequest().getTaskId());
}
};
}
/**
* 定义一个下发更新的 job
* @return
*/
@Bean
public Job updateDeviceJob(Step updateDeviceStep) {
return jobBuilderFactory.get(UUID.randomUUID().toString().replace("-", ""))
.listener(new JobListener()) // 设置Job的监听器
.flow(updateDeviceStep)// 执行下发更新的Step
.end()
.build();
}
/**
* 定义一个下发更新的 step
* @return
*/
@Bean
public Step updateDeviceStep(JdbcCursorItemReader<DispatchRequest> itemReader,ItemWriter<ProcessResult> itemWriter) {
return stepBuilderFactory.get(UUID.randomUUID().toString().replace("-", ""))
.<DispatchRequest, ProcessResult> chunk(batchSize)
.reader(itemReader) //根据taskId从数据库读取更新设备信息
.processor(taskItemProcessor) // 每条更新信息，执行下发更新接口
.writer(itemWriter)
.build();
}
// job 监听器
public class JobListener implements JobExecutionListener {
@Override
public void beforeJob(JobExecution jobExecution) {
log.info(jobExecution.getJobInstance().getJobName() + " before... ");
parameters = jobExecution.getJobParameters().getParameters();
taskId = parameters.get("taskId").getValue();
log.info("job param taskId : " + parameters.get("taskId"));
}
@Override
public void afterJob(JobExecution jobExecution) {
log.info(jobExecution.getJobInstance().getJobName() + " after... ");
// 当所有job执行完之后，查询设备更新状态，如果有失败，则要定时重新执行job
String sql = " SELECT " +
" count(*) " +
" FROM " +
" eiot_upgrade_device d " +
" LEFT JOIN eiot_upgrade_task u ON d.upgrade_task_id = u. ID " +
" WHERE " +
" u. ID = ? " +
" AND d.retry_times < u.tetry_times " +
" AND ( " +
" d.device_upgrade_status = 0 " +
" OR d.device_upgrade_status = 2 " +
" ) ";
// 获取更新失败的设备个数
Integer count = jdbcTemplate.queryForObject(sql, new Object[]{taskId}, Integer.class);
log.info("update device failure count : " + count);
// 下面是使用Quartz触发定时任务
// 获取任务时间,单位秒
// String time = jdbcTemplate.queryForObject(sql, new Object[]{taskId}, Integer.class);
// 此处方便测试，应该从数据库中取taskId对应的重试间隔，单位秒
Integer millSecond = 10;
if(count != null && count > 0){
String jobName = "UpgradeTask_" + taskId;
String reTaskId = taskId.toString();
Map<String,Object> params = new HashMap<>();
params.put("jobName",jobName);
params.put("taskId",reTaskId);
if (QuartzManager.checkNameNotExist(jobName))
{
QuartzManager.scheduleRunOnceJob(jobName, RunOnceJobLogic.class,params,millSecond);
}
}
}
}
}
5、Processor，处理每条数据
可以在此对数据进行过滤操作
@Component("taskItemProcessor")
public class TaskItemProcessor implements ItemProcessor<DispatchRequest, ProcessResult> {
public static final int STATUS_DISPATCH_FAILED = 2;
public static final int STATUS_DISPATCH_SUCC = 1;
private static final Logger log = LoggerFactory.getLogger(TaskItemProcessor.class);
@Value("${upgrade-dispatch-base-url:http://localhost/api/v2/rpc/dispatch/command/}")
private String dispatchUrl;
@Autowired
JdbcTemplate jdbcTemplate;
/**
* 在这里，执行 下发更新指令 的操作
* @param dispatchRequest
* @return
* @throws Exception
*/
@Override
public ProcessResult process(final DispatchRequest dispatchRequest) {
// 调用接口，下发指令
String url = dispatchUrl + dispatchRequest.getDeviceId()+"/"+dispatchRequest.getUserId();
log.info("request url:" + url);
RestTemplate restTemplate = new RestTemplate();
HttpHeaders headers = new HttpHeaders();
headers.setContentType(MediaType.APPLICATION_JSON_UTF8);
MultiValueMap<String, String> params = new LinkedMultiValueMap<String, String>();
JSONObject jsonOuter = new JSONObject();
JSONObject jsonInner = new JSONObject();
try {
jsonInner.put("jobId",dispatchRequest.getTaskId());
jsonInner.put("name",dispatchRequest.getName());
jsonInner.put("composeFile", Base64Util.bytesToBase64Str(dispatchRequest.getComposeFile()));
jsonInner.put("policy",new JSONObject().put("startTime",dispatchRequest.getPolicy()));
jsonInner.put("timestamp",dispatchRequest.getTimestamp());
jsonOuter.put("method","updateApp");
jsonOuter.put("params",jsonInner);
} catch (JSONException e) {
log.info("JSON convert Exception :" + e);
}catch (IOException e) {
log.info("Base64Util bytesToBase64Str :" + e);
}
log.info("request body json :" + jsonOuter);
HttpEntity<String> requestEntity = new HttpEntity<String>(jsonOuter.toString(),headers);
int status;
try {
ResponseEntity<String> response = restTemplate.postForEntity(url,requestEntity,String.class);
log.info("response :" + response);
if (response.getStatusCode() == HttpStatus.OK) {
status = STATUS_DISPATCH_SUCC;
} else {
status = STATUS_DISPATCH_FAILED;
}
}catch (Exception e){
status = STATUS_DISPATCH_FAILED;
}
return new ProcessResult(dispatchRequest, status);
}
}
6、封装数据库返回数据的实体Bean
注意静态内部类
public class DispatchRequest {
private String taskId;
private String deviceId;
private String userId;
private String name;
private byte[] composeFile;
private String policy;
private String timestamp;
private String md5;
private int failureRetry;
private int retryTimes;
private int deviceManagered;
// 省略构造函数，setter/getter/tostring方法
//......
public static class DispatchRequestRowMapper implements RowMapper<DispatchRequest> {
@Override
public DispatchRequest mapRow(ResultSet resultSet, int i) throws SQLException {
DispatchRequest dispatchRequest = new DispatchRequest();
dispatchRequest.setTaskId(resultSet.getString("taskId"));
dispatchRequest.setUserId(resultSet.getString("userId"));
dispatchRequest.setPolicy(resultSet.getString("startTime"));
dispatchRequest.setDeviceId(resultSet.getString("deviceId"));
dispatchRequest.setName(resultSet.getString("appName"));
dispatchRequest.setComposeFile(resultSet.getBytes("composeFile"));
dispatchRequest.setTimestamp(DateUtil.DateToString(new Date()));
dispatchRequest.setRetryTimes(resultSet.getInt("retryTimes"));
dispatchRequest.setFailureRetry(resultSet.getInt("failureRetry"));
dispatchRequest.setDeviceManagered(resultSet.getInt("deviceManagered"));
return dispatchRequest;
}
}
}
7、启动类上要加上注解
@SpringBootApplication
@EnableBatchProcessing
public class Application {
public static void main(String[] args) {
SpringApplication.run(Application.class, args);
}
}
三、小结一下
其实SpringBatch并没有想象中那么好用，当从数据库中每次取5000条数据后，进入processor中是逐条处理的，这个时候不能不行操作，等5000条数据处理完之后，再一次性执行ItemWriter方法。
在使用的过程中，最坑的地方是ItemReader和ItemWriter这两个地方，如何执行自定义的Sql，参考文中代码就行。至于Quartz定时功能，很简单，只要定时创建SpringBatch里面的Job，让这个job启动就好了，此处就不在给出了，贴的代码太多了。由于公司一些原因，代码不能放到GitHub上。
spring-batch与quartz集成过程中遇到的问题
问题
启动时报Exception
Driver's Blob representation is of an unsupported type: weblogic.jdbc.wrapper.Blob_oracle_sql_BLOB
原因
quartz的driverDelegateClass配置的是OracleDelegate，应用运行在weblogic上
解决
driverDelegateClass对应配置改为
org.quartz.impl.jdbcjobstore.oracle.weblogic.WebLogicOracleDelegate
以上为个人经验，希望能给大家一个参考，也希望大家多多支持靠谱客。
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