Spring Batch的优缺点

一、开发效率高

Spring Batch提高了开发者的生产力，使得批处理应用程序的开发变得容易和高效。它提供了一组用于定义简单批处理作业的元数据，这些元数据可以轻松地扩展，以支持更复杂的流程。在Spring Batch中，开发者只需要定义作业的输入（Reader）、处理（Processor）和输出（Writer）节点即可，而不需要像原始的Java批处理API那样编写很多模板和模式。另外，Spring Batch 还提供了大量的工具，如JobLauncher和JobOperator ，使得作业的启动和管理变得十分简单。

以下是一个简单的示例，展示如何使用Spring Batch来实现在XML或者数据库中读取人员信息，处理并输出到XML和文本文件当中。代码中包含两个不同的Job，分别读取XML和数据库中的数据并输出到不同的地方。

@Configuration
@EnableBatchProcessing
public class BatchConfiguration {
 
    private final JobBuilderFactory jobBuilderFactory;
    private final StepBuilderFactory stepBuilderFactory;
 
    @Autowired
    public BatchConfiguration(JobBuilderFactory jobBuilderFactory, StepBuilderFactory stepBuilderFactory) {
        this.jobBuilderFactory = jobBuilderFactory;
        this.stepBuilderFactory = stepBuilderFactory;
    }
 
    @Bean
    public ItemReader xmlPersonReader() {
        StaxEventItemReader
    reader = new StaxEventItemReader<>();
        reader.setResource(new ClassPathResource("persons.xml"));
        reader.setFragmentRootElementName("person");
        reader.setUnmarshaller(personUnmarshaller());
 
        return reader;
    }
 
    @Bean
    public Unmarshaller personUnmarshaller() {
        Jaxb2Marshaller marshaller = new Jaxb2Marshaller();
        marshaller.setClassesToBeBound(Person.class);
 
        return marshaller;
    }
 
    @Bean
    public ItemReader
     dbPersonReader(JdbcTemplate jdbcTemplate) {
        JdbcCursorItemReader
      reader = new JdbcCursorItemReader<>();
        reader.setDataSource(jdbcTemplate.getDataSource());
        reader.setSql("select id, first_name, last_name, email, age from person");
        reader.setRowMapper((resultSet, i) -> {
            Person person = new Person();
            person.setId(resultSet.getLong("id"));
            person.setFirstName(resultSet.getString("first_name"));
            person.setLastName(resultSet.getString("last_name"));
            person.setEmail(resultSet.getString("email"));
            person.setAge(resultSet.getInt("age"));
            return person;
        });
 
        return reader;
    }
 
    @Bean
    public ItemWriter
       xmlPersonWriter() {
        StaxEventItemWriter
       
        writer = new StaxEventItemWriter<>(); writer.setResource(new FileSystemResource("persons.xml")); writer.setRootTagName("persons"); writer.setMarshaller(personMarshaller()); writer.setOverwriteOutput(true); return writer; } @Bean public Marshaller personMarshaller() { Jaxb2Marshaller marshaller = new Jaxb2Marshaller(); marshaller.setClassesToBeBound(Person.class); return marshaller; } @Bean public ItemWriter
        
         txtPersonWriter() throws Exception { FlatFileItemWriter
         
          writer = new FlatFileItemWriter<>(); writer.setResource(new FileSystemResource("persons.txt")); writer.setLineAggregator(lineAggregator()); writer.setAppendAllowed(true); writer.setHeaderCallback(writer1 -> { writer1.write("Id\tFirst Name\tLast Name\tEmail\tAge\n"); }); writer.afterPropertiesSet(); return writer; } @Bean public LineAggregator
          
           lineAggregator() { DelimitedLineAggregator
           
            aggregator = new DelimitedLineAggregator<>(); aggregator.setDelimiter("\t"); aggregator.setFieldExtractor(fieldExtractor()); return aggregator; } @Bean public FieldExtractor
            
             fieldExtractor() { BeanWrapperFieldExtractor
             
              extractor = new BeanWrapperFieldExtractor<>(); extractor.setNames(new String[] {"id", "firstName", "lastName", "email", "age"}); return extractor; } @Bean public Step xmlPersonStep(ItemReader
              
               xmlPersonReader, ItemWriter
               
                txtPersonWriter, ItemWriter
                
                 xmlPersonWriter) { return stepBuilderFactory.get("xmlPersonReadingStep") .
                 
                  chunk(10) .reader(xmlPersonReader) .processor(personUpperProcessor()) .writer(txtPersonWriter) .writer(xmlPersonWriter) .build(); } @Bean public Step dbPersonStep(ItemReader
                  
                   dbPersonReader, ItemWriter
                   
                    txtPersonWriter) { return stepBuilderFactory.get("dbPersonReadingStep") .
                    
                     chunk(10) .reader(dbPersonReader) .processor(personUpperProcessor()) .writer(txtPersonWriter) .build(); } @Bean public Job job(Step dbPersonStep, Step xmlPersonStep) { return jobBuilderFactory.get("personJob") .incrementer(new RunIdIncrementer()) .start(xmlPersonStep) .next(dbPersonStep) .build(); } @Bean public ItemProcessor
                     
                      personUpperProcessor() { return person -> { person.setFirstName(person.getFirstName().toUpperCase()); person.setLastName(person.getLastName().toUpperCase()); person.setEmail(person.getEmail().toUpperCase()); return person; }; } }
                     
                    
                   
                  
                 
                
               
              
             
            
           
          
         
        
       
      
     
    
   
  

二、高性能处理大规模数据

Spring Batch 能够高效处理大规模的数据，其内部实现了优化批处理的算法，可以大大提升批处理的处理速度、效率和吞吐量。在处理大规模数据的过程中，Spring Batch 的每个步骤都是按照一定的要求进行分割的，以便能够并行处理数据，这样才能最大化地利用多核处理器的性能优势。

以下代码展示了如何在Spring Batch中使用多线程并行处理大文件：

@Configuration
@EnableBatchProcessing
public class BatchConfiguration {
 
    private final JobBuilderFactory jobBuilderFactory;
    private final StepBuilderFactory stepBuilderFactory;
 
    @Autowired
    public BatchConfiguration(JobBuilderFactory jobBuilderFactory, StepBuilderFactory stepBuilderFactory) {
        this.jobBuilderFactory = jobBuilderFactory;
        this.stepBuilderFactory = stepBuilderFactory;
    }
 
    @Bean
    public FlatFileItemReader reader() {
        FlatFileItemReader
    reader = new FlatFileItemReader<>();
        reader.setResource(new ClassPathResource("data.txt"));
        reader.setLineMapper(lineMapper());
        return reader;
    }
 
    @Bean
    public LineMapper
     lineMapper() {
        DefaultLineMapper
      lineMapper = new DefaultLineMapper<>();
        DelimitedLineTokenizer tokenizer = new DelimitedLineTokenizer();
        tokenizer.setDelimiter(",");
        tokenizer.setNames(new String[] {"id", "filename", "content"});
        lineMapper.setLineTokenizer(tokenizer);
        lineMapper.setFieldSetMapper(new FileContentFieldSetMapper());
        return lineMapper;
    }
 
    @Bean
    public ItemProcessor
       processor() {
        return fileContent -> {
            fileContent.setContent(fileContent.getContent().toUpperCase());
            return fileContent;
        };
    }
 
    @Bean
    public ItemWriter
       
        writer() { FlatFileItemWriter
        
         writer = new FlatFileItemWriter<>(); writer.setResource(new FileSystemResource("processed-data.txt")); writer.setLineAggregator(new DelimitedLineAggregator
         
          () { { setDelimiter(","); setFieldExtractor(new BeanWrapperFieldExtractor
          
           () { { setNames(new String[] {"id", "filename", "content"}); } }); } }); return writer; } @Bean public Step step1() { return stepBuilderFactory.get("step1") .
           
            chunk(1000) .reader(reader()) .processor(processor()) .writer(writer()) .taskExecutor(taskExecutor()) .build(); } @Bean public TaskExecutor taskExecutor() { ThreadPoolTaskExecutor taskExecutor = new ThreadPoolTaskExecutor(); taskExecutor.setCorePoolSize(10); taskExecutor.setMaxPoolSize(20); taskExecutor.afterPropertiesSet(); return taskExecutor; } @Bean public Job job() { return jobBuilderFactory.get("job") .incrementer(new RunIdIncrementer()) .start(step1()) .build(); } }
           
          
         
        
       
      
     
    
   
  

三、易于维护和测试

Spring Batch提供了许多易于维护和测试的功能。Spring Batch的作业和步骤都是单独的Java类，这使得它们易于定义、修改和测试。此外，Spring Batch 还提供了一系列的工具和类，如 ItemReader、ItemWriter、ItemProcessor 等，方便开发者进行单元测试和集成测试。

以下代码展示如何在Spring Batch的项处理器中使用JUnit进行单元测试：

public class PersonItemProcessorTest {
 
    private ItemProcessor processor = new PersonItemProcessor();
 
    @Test
    public void testProcessor() throws Exception {
        Person person = new Person();
        person.setFirstName("Alice");
        person.setLastName("Smith");
        person.setEmail("alice.smith@example.com");
        person.setAge(30);
 
        PersonDto personDto = processor.process(person);
 
        assertNotNull(personDto);
        assertEquals("ALICE SMITH", personDto.getName());
        assertEquals("alice.smith@example.com", personDto.getEmail());
    }
}

  

四、缺点

Spring Batch的主要缺点是其学习曲线较长，需要一定的时间去学习和了解其核心概念及其用法。另外，一些高级功能，如调度和监控等，需要进行一定的配置和设置，需要开发者有一定的经验才能轻松理解和使用。