Spring Boot整合Spring Batch

Java框架

浏览数:118

2019-5-9

引言

  Spring Batch是处理大量数据操作的一个框架,主要用来读取大量数据,然后进行一定的处理后输出指定的形式。比如我们可以将csv文件中的数据(数据量几百万甚至几千万都是没问题的)批处理插入保存到数据库中,就可以使用该框架,但是不管是数据资料还是网上资料,我看到很少有这样的详细讲解。所以本片博文的主要目的边讲解的同时边实战(其中的代码都是经过实践的)。同样地先从Spring Boot对Batch框架的支持说起,最后一步一步进行代码实践!

一、Spring Boot对Batch框架的支持

1、Spring Batch框架的组成部分

  1)JobRepository:用来注册Job容器,设置数据库相关属性。

  2)JobLauncher:用来启动Job的接口

  3)Job:我们要实际执行的任务,包含一个或多个

  4)Step:即步骤,包括:ItemReader->ItemProcessor->ItemWriter

  5)ItemReader:用来读取数据,做实体类与数据字段之间的映射。比如读取csv文件中的人员数据,之后对应实体person的字段做mapper

  6)ItemProcessor:用来处理数据的接口,同时可以做数据校验(设置校验器,使用JSR-303(hibernate-validator)注解),比如将中文性别男/女,转为M/F。同时校验年龄字段是否符合要求等

  7)ItemWriter:用来输出数据的接口,设置数据库源。编写预处理SQL插入语句

以上七个组成部分,只需要在配置类中逐一注册即可,同时配置类需要开启@EnableBatchProcessing注解

@Configuration
@EnableBatchProcessing // 开启批处理的支持
@Import(DruidDBConfig.class) // 注入datasource
public class CsvBatchConfig {
    
}

2、批处理流程图

如下流程图即可以解释在配置类中为什么需要这么定义,具体请看实战部分的代码。

 

二、实战

1、添加依赖

1)spring batch依赖

<!--  spring batch -->
<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-batch</artifactId>
</dependency>

2)校验器依赖

<!-- hibernate validator -->
<dependency>
    <groupId>org.hibernate</groupId>
    <artifactId>hibernate-validator</artifactId>
    <version>6.0.7.Final</version>
</dependency>

3)mysql+druid依赖

<!-- mysql connector-->
<dependency>
    <groupId>mysql</groupId>
    <artifactId>mysql-connector-java</artifactId>
    <version>5.1.35</version>
</dependency>
<!-- alibaba dataSource -->
<dependency>
    <groupId>com.alibaba</groupId>
    <artifactId>druid</artifactId>
    <version>1.1.12</version>
</dependency>

4)test测试依赖

<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-test</artifactId>
</dependency>

2、application.yml配置

当job发布开始执行任务时,spring batch会自动生成相关的batch开头的表。这些表一开始是不存在的!需要在application配置文件中做相关的设置。

# batch
  batch:
    job:
      # 默认自动执行定义的Job(true),改为false,需要jobLaucher.run执行
      enabled: false
    # spring batch在数据库里面创建默认的数据表,如果不是always则会提示相关表不存在
    initialize-schema: always
    # 设置batch表的前缀
#    table-prefix: csv-batch

3、数据源配置

  datasource:
    username: root
    password: 1234
    url: jdbc:mysql://127.0.0.1:3306/db_base?useSSL=false&serverTimezone=UTC&characterEncoding=utf8
    driver-class-name: com.mysql.jdbc.Driver

注册DBConfig配置类:之后通过import导入batch配置类中

/**
 * @author jian
 * @dete 2019/4/20
 * @description 自定义DataSource
 *
 */
@Configuration
public class DruidDBConfig {

    private Logger logger = LoggerFactory.getLogger(DruidDBConfig.class);

    @Value("${spring.datasource.url}")
    private String dbUrl;

    @Value("${spring.datasource.username}")
    private String username;

    @Value("${spring.datasource.password}")
    private String password;

    @Value("${spring.datasource.driver-class-name}")
    private String driverClassName;

   /* @Value("${spring.datasource.initialSize}")
    private int initialSize;

    @Value("${spring.datasource.minIdle}")
    private int minIdle;

    @Value("${spring.datasource.maxActive}")
    private int maxActive;

    @Value("${spring.datasource.maxWait}")
    private int maxWait;

    @Value("${spring.datasource.timeBetweenEvictionRunsMillis}")
    private int timeBetweenEvictionRunsMillis;

    @Value("${spring.datasource.minEvictableIdleTimeMillis}")
    private int minEvictableIdleTimeMillis;

    @Value("${spring.datasource.validationQuery}")
    private String validationQuery;

    @Value("${spring.datasource.testWhileIdle}")
    private boolean testWhileIdle;

    @Value("${spring.datasource.testOnBorrow}")
    private boolean testOnBorrow;

    @Value("${spring.datasource.testOnReturn}")
    private boolean testOnReturn;

    @Value("${spring.datasource.poolPreparedStatements}")
    private boolean poolPreparedStatements;

    @Value("${spring.datasource.maxPoolPreparedStatementPerConnectionSize}")
    private int maxPoolPreparedStatementPerConnectionSize;

    @Value("${spring.datasource.filters}")
    private String filters;

    @Value("{spring.datasource.connectionProperties}")
    private String connectionProperties;*/

    @Bean
    @Primary  // 被注入的优先级最高
    public DataSource dataSource() {
        DruidDataSource dataSource = new DruidDataSource();
        logger.info("-------->dataSource[url="+dbUrl+" ,username="+username+"]");
        dataSource.setUrl(dbUrl);
        dataSource.setUsername(username);
        dataSource.setPassword(password);
        dataSource.setDriverClassName(driverClassName);

        /*  //configuration
        datasource.setInitialSize(initialSize);
        datasource.setMinIdle(minIdle);
        datasource.setMaxActive(maxActive);
        datasource.setMaxWait(maxWait);
        datasource.setTimeBetweenEvictionRunsMillis(timeBetweenEvictionRunsMillis);
        datasource.setMinEvictableIdleTimeMillis(minEvictableIdleTimeMillis);
        datasource.setValidationQuery(validationQuery);
        datasource.setTestWhileIdle(testWhileIdle);
        datasource.setTestOnBorrow(testOnBorrow);
        datasource.setTestOnReturn(testOnReturn);
        datasource.setPoolPreparedStatements(poolPreparedStatements);
        datasource.setMaxPoolPreparedStatementPerConnectionSize(maxPoolPreparedStatementPerConnectionSize);
        try {
            datasource.setFilters(filters);
        } catch (SQLException e) {
            logger.error("druid configuration initialization filter", e);
        }
        datasource.setConnectionProperties(connectionProperties);*/

        return dataSource;
    }

    @Bean
    public ServletRegistrationBean druidServletRegistrationBean() {
        ServletRegistrationBean servletRegistrationBean = new ServletRegistrationBean();
        servletRegistrationBean.setServlet(new StatViewServlet());
        servletRegistrationBean.addUrlMappings("/druid/*");
        return servletRegistrationBean;
    }

    /**
     * 注册DruidFilter拦截
     *
     * @return
     */
    @Bean
    public FilterRegistrationBean duridFilterRegistrationBean() {
        FilterRegistrationBean filterRegistrationBean = new FilterRegistrationBean();
        filterRegistrationBean.setFilter(new WebStatFilter());
        Map<String, String> initParams = new HashMap<String, String>();
        //设置忽略请求
        initParams.put("exclusions", "*.js,*.gif,*.jpg,*.bmp,*.png,*.css,*.ico,/druid/*");
        filterRegistrationBean.setInitParameters(initParams);
        filterRegistrationBean.addUrlPatterns("/*");
        return filterRegistrationBean;
    }
}

4、编写batch配置类

在配置类中,注册Spring Batch的各个组成部分即可,其中部分说明已在代码中注释.

/**
 *
 * @author jian
 * @date 2019/4/28
 * @description spring batch cvs文件批处理配置需要注入Spring Batch以下组成部分
 * spring batch组成:
 * 1)JobRepository 注册job的容器
 * 2)JonLauncher 用来启动job的接口
 * 3)Job 实际执行的任务,包含一个或多个Step
 * 4)Step Step步骤包括ItemReader、ItemProcessor和ItemWrite
 * 5)ItemReader 读取数据的接口
 * 6)ItemProcessor 处理数据的接口
 * 7)ItemWrite 输出数据的接口
 *
 *
 */
@Configuration
@EnableBatchProcessing // 开启批处理的支持
@Import(DruidDBConfig.class) // 注入datasource
public class CsvBatchConfig {
    private Logger logger = LoggerFactory.getLogger(CsvBatchConfig.class);


    /**
     * ItemReader定义:读取文件数据+entirty映射
     * @return
     */
    @Bean
    public ItemReader<Person> reader(){
        // 使用FlatFileItemReader去读cvs文件,一行即一条数据
        FlatFileItemReader<Person> reader = new FlatFileItemReader<>();
        // 设置文件处在路径
        reader.setResource(new ClassPathResource("person.csv"));
        // entity与csv数据做映射
        reader.setLineMapper(new DefaultLineMapper<Person>() {
            {
                setLineTokenizer(new DelimitedLineTokenizer() {
                    {
                        setNames(new String[]{"id", "name", "age", "gender"});
                    }
                });
                setFieldSetMapper(new BeanWrapperFieldSetMapper<Person>() {
                    {
                        setTargetType(Person.class);
                    }
                });
            }
        });
        return reader;
    }


    /**
     * 注册ItemProcessor: 处理数据+校验数据
     * @return
     */
    @Bean
    public ItemProcessor<Person, Person> processor(){
        CvsItemProcessor cvsItemProcessor = new CvsItemProcessor();
        // 设置校验器
        cvsItemProcessor.setValidator(csvBeanValidator());
        return cvsItemProcessor;
    }

    /**
     * 注册校验器
     * @return
     */
    @Bean
    public CsvBeanValidator csvBeanValidator(){
        return new CsvBeanValidator<Person>();
    }

    /**
     * ItemWriter定义:指定datasource,设置批量插入sql语句,写入数据库
     * @param dataSource
     * @return
     */
    @Bean
    public ItemWriter<Person> writer(DataSource dataSource){
        // 使用jdbcBcatchItemWrite写数据到数据库中
        JdbcBatchItemWriter<Person> writer = new JdbcBatchItemWriter<>();
        // 设置有参数的sql语句
        writer.setItemSqlParameterSourceProvider(new BeanPropertyItemSqlParameterSourceProvider<Person>());
        String sql = "insert into person values(:id,:name,:age,:gender)";
        writer.setSql(sql);
        writer.setDataSource(dataSource);
        return writer;
    }

    /**
     * JobRepository定义:设置数据库,注册Job容器
     * @param dataSource
     * @param transactionManager
     * @return
     * @throws Exception
     */
    @Bean
    public JobRepository cvsJobRepository(DataSource dataSource, PlatformTransactionManager transactionManager) throws Exception{
        JobRepositoryFactoryBean jobRepositoryFactoryBean = new JobRepositoryFactoryBean();
        jobRepositoryFactoryBean.setDatabaseType("mysql");
        jobRepositoryFactoryBean.setTransactionManager(transactionManager);
        jobRepositoryFactoryBean.setDataSource(dataSource);
        return jobRepositoryFactoryBean.getObject();
    }

    /**
     * jobLauncher定义:
     * @param dataSource
     * @param transactionManager
     * @return
     * @throws Exception
     */
    @Bean
    public SimpleJobLauncher csvJobLauncher(DataSource dataSource, PlatformTransactionManager transactionManager) throws Exception{
        SimpleJobLauncher jobLauncher = new SimpleJobLauncher();
        // 设置jobRepository
        jobLauncher.setJobRepository(cvsJobRepository(dataSource, transactionManager));
        return jobLauncher;
    }

    /**
     * 定义job
     * @param jobs
     * @param step
     * @return
     */
    @Bean
    public Job importJob(JobBuilderFactory jobs, Step step){
        return jobs.get("importCsvJob")
                .incrementer(new RunIdIncrementer())
                .flow(step)
                .end()
                .listener(csvJobListener())
                .build();
    }

    /**
     * 注册job监听器
     * @return
     */
    @Bean
    public CsvJobListener csvJobListener(){
        return new CsvJobListener();
    }


    /**
     * step定义:步骤包括ItemReader->ItemProcessor->ItemWriter 即读取数据->处理校验数据->写入数据
     * @param stepBuilderFactory
     * @param reader
     * @param writer
     * @param processor
     * @return
     */
    @Bean
    public Step step(StepBuilderFactory stepBuilderFactory, ItemReader<Person> reader,
                     ItemWriter<Person> writer, ItemProcessor<Person, Person> processor){
        return stepBuilderFactory
                .get("step")
                .<Person, Person>chunk(65000) // Chunk的机制(即每次读取一条数据,再处理一条数据,累积到一定数量后再一次性交给writer进行写入操作)
                .reader(reader)
                .processor(processor)
                .writer(writer)
                .build();

    }
}

5、定义处理器

只需要实现ItemProcessor接口,重写process方法,输入的参数是从ItemReader读取到的数据,返回的数据给ItemWriter

/**
 * @author jian
 * @date 2019/4/28
 * @description
 * CSV文件数据处理及校验
 * 只需要实现ItemProcessor接口,重写process方法,输入的参数是从ItemReader读取到的数据,返回的数据给ItemWriter
 */
public class CvsItemProcessor extends ValidatingItemProcessor<Person> {
    private Logger logger = LoggerFactory.getLogger(CvsItemProcessor.class);

    @Override
    public Person process(Person item) throws ValidationException {
        // 执行super.process()才能调用自定义的校验器
        logger.info("processor start validating...");
        super.process(item);

        // 数据处理,比如将中文性别设置为M/F
        if ("男".equals(item.getGender())) {
            item.setGender("M");
        } else {
            item.setGender("F");
        }
        logger.info("processor end validating...");
        return item;
    }
}

6、定义校验器

定义校验器:使用JSR-303(hibernate-validator)注解,来校验ItemReader读取到的数据是否满足要求。如不满足则不会进行接下来的批处理任务。

/**
 *
 * @author jian
 * @date 2019/4/28
 * @param <T>
 * @description 定义校验器:使用JSR-303(hibernate-validator)注解,来校验ItemReader读取到的数据是否满足要求。
 */

public class CsvBeanValidator<T> implements Validator<T>, InitializingBean {

    private javax.validation.Validator validator;


    /**
     * 进行JSR-303的Validator的初始化
     * @throws Exception
     */
    @Override
    public void afterPropertiesSet() throws Exception {
        ValidatorFactory validatorFactory = Validation.buildDefaultValidatorFactory();
        validator = validatorFactory.usingContext().getValidator();
    }

    /**
     * 使用validator方法检验数据
     * @param value
     * @throws ValidationException
     */
    @Override
    public void validate(T value) throws ValidationException {
        Set<ConstraintViolation<T>> constraintViolations = validator.validate(value);
        if (constraintViolations.size() > 0) {
            StringBuilder message = new StringBuilder();
            for (ConstraintViolation<T> constraintViolation: constraintViolations) {
                message.append(constraintViolation.getMessage() + "\n");
            }
            throw new ValidationException(message.toString());
        }
    }
}

7、定义监听器:

监听Job执行情况,则定义一个类实现JobExecutorListener,并定义Job的Bean上绑定该监听器

/**
 * @author jian
 * @date 2019/4/28
 * @description
 * 监听Job执行情况,则定义一个类实现JobExecutorListener,并定义Job的Bean上绑定该监听器
 */
public class CsvJobListener implements JobExecutionListener {

    private Logger logger = LoggerFactory.getLogger(CsvJobListener.class);
    private long startTime;
    private long endTime;

    @Override
    public void beforeJob(JobExecution jobExecution) {
        startTime = System.currentTimeMillis();
        logger.info("job process start...");
    }

    @Override
    public void afterJob(JobExecution jobExecution) {
        endTime = System.currentTimeMillis();
        logger.info("job process end...");
        logger.info("elapsed time: " + (endTime - startTime) + "ms");
    }
}

三、测试

1、person.csv文件

csv文件时以逗号为分隔的数据表示字段,回车表示一行(条)数据记录

1,Zhangsan,21,男
2,Lisi,22,女
3,Wangwu,23,男
4,Zhaoliu,24,男
5,Zhouqi,25,女

放在resources下,在ItemReader中读取的该路径即可

2、person实体

person.csv中的字段与之对应,并在该实体中可以添加校验注解,如@Size表示该字段的长度范围,如果超过规定。则会被校验检测到,批处理将不会进行!

public class Person implements Serializable {
    private final long serialVersionUID = 1L;

    private String id;
    @Size(min = 2, max = 8)
    private String name;
    private int age;
    private String gender;

    public String getId() {
        return id;
    }

    public void setId(String id) {
        this.id = id;
    }

    public String getName() {
        return name;
    }

    public void setName(String name) {
        this.name = name;
    }

    public int getAge() {
        return age;
    }

    public void setAge(int age) {
        this.age = age;
    }

    public String getGender() {
        return gender;
    }

    public void setGender(String gender) {
        this.gender = gender;
    }

    @Override
    public String toString() {
        return "Person{" +
                "id='" + id + '\'' +
                ", name='" + name + '\'' +
                ", age=" + age +
                ", gender='" + gender + '\'' +
                '}';
    }
}

3、数据表

CREATE TABLE `person` (
  `id` int(11) NOT NULL,
  `name` varchar(10) DEFAULT NULL,
  `age` int(11) DEFAULT NULL,
  `gender` varchar(2) NOT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=latin1

一开始表是没有数据的

4、测试类

需要注入发布器,与job任务。同时可以使用后置参数灵活处理,最后调用JobLauncher.run方法执行批处理任务

@RunWith(SpringRunner.class)
@SpringBootTest
public class BatchTest {

    @Autowired
    SimpleJobLauncher jobLauncher;

    @Autowired
    Job importJob;

    @Test
    public void test() throws Exception{
        // 后置参数:使用JobParameters中绑定参数
        JobParameters jobParameters = new JobParametersBuilder().addLong("time", System.currentTimeMillis())
                .toJobParameters();
        jobLauncher.run(importJob, jobParameters);
    }
}

5、测试结果

....
2019-05-09 15:23:39.576 INFO 18296 --- [ main] com.lijian.test.BatchTest : Started BatchTest in 6.214 seconds (JVM running for 7.185) 2019-05-09 15:23:39.939 INFO 18296 --- [ main] o.s.b.c.l.support.SimpleJobLauncher : Job: [FlowJob: [name=importCsvJob]] launched with the following parameters: [{time=1557386619763}] 2019-05-09 15:23:39.982 INFO 18296 --- [ main] com.lijian.config.batch.CsvJobListener : job process start... 2019-05-09 15:23:40.048 INFO 18296 --- [ main] o.s.batch.core.job.SimpleStepHandler : Executing step: [step] 2019-05-09 15:23:40.214 INFO 18296 --- [ main] c.lijian.config.batch.CvsItemProcessor : processor start validating... 2019-05-09 15:23:40.282 INFO 18296 --- [ main] c.lijian.config.batch.CvsItemProcessor : processor end validating... 2019-05-09 15:23:40.283 INFO 18296 --- [ main] c.lijian.config.batch.CvsItemProcessor : processor start validating... 2019-05-09 15:23:40.283 INFO 18296 --- [ main] c.lijian.config.batch.CvsItemProcessor : processor end validating... 2019-05-09 15:23:40.283 INFO 18296 --- [ main] c.lijian.config.batch.CvsItemProcessor : processor start validating... 2019-05-09 15:23:40.283 INFO 18296 --- [ main] c.lijian.config.batch.CvsItemProcessor : processor end validating... 2019-05-09 15:23:40.283 INFO 18296 --- [ main] c.lijian.config.batch.CvsItemProcessor : processor start validating... 2019-05-09 15:23:40.283 INFO 18296 --- [ main] c.lijian.config.batch.CvsItemProcessor : processor end validating... 2019-05-09 15:23:40.283 INFO 18296 --- [ main] c.lijian.config.batch.CvsItemProcessor : processor start validating... 2019-05-09 15:23:40.284 INFO 18296 --- [ main] c.lijian.config.batch.CvsItemProcessor : processor end validating... 2019-05-09 15:23:40.525 INFO 18296 --- [ main] com.lijian.config.batch.CsvJobListener : job process end... 2019-05-09 15:23:40.526 INFO 18296 --- [ main] com.lijian.config.batch.CsvJobListener : elapsed time: 543ms 2019-05-09 15:23:40.548 INFO 18296 --- [ main] o.s.b.c.l.support.SimpleJobLauncher : Job: [FlowJob: [name=importCsvJob]] completed with the following parameters: [{time=1557386619763}] and the following status: [COMPLETED] 2019-05-09 15:23:40.564 INFO 18296 --- [ Thread-5] com.alibaba.druid.pool.DruidDataSource : {dataSource-1} closed

查看表中数据: select * from person; 

若继续插入数据,并且测试校验器是否生效,则将person.csv更改为如下内容:

6,springbatch,24,男
7,springboot,23,女

由于实体类中JSR校验注解对name长度范围进行了检验,即添加了 @Size(min=2, max=8) 的注解。故会报错显示校验不通过,批处理将不会进行。

...
Started BatchTest in 5.494 seconds (JVM running for 6.41)
2019-05-09 15:30:02.147  INFO 20368 --- [           main] o.s.b.c.l.support.SimpleJobLauncher      : Job: [FlowJob: [name=importCsvJob]] launched with the following parameters: [{time=1557387001499}]
2019-05-09 15:30:02.247  INFO 20368 --- [           main] com.lijian.config.batch.CsvJobListener   : job process start...
2019-05-09 15:30:02.503  INFO 20368 --- [           main] o.s.batch.core.job.SimpleStepHandler     : Executing step: [step]
2019-05-09 15:30:02.683  INFO 20368 --- [           main] c.lijian.config.batch.CvsItemProcessor   : processor start validating...
2019-05-09 15:30:02.761 ERROR 20368 --- [           main] o.s.batch.core.step.AbstractStep         : Encountered an error executing step step in job importCsvJob

org.springframework.batch.item.validator.ValidationException: size must be between 2 and 8
...

 

作者:JJian