分享Spring Batch的介绍

2020年9月23日 22:24:21java教程评论799 views阅读模式

这篇文章主要给大家介绍了Spring Batch入门的相关资料，文中介绍的非常详细，对大家具有一定的参考学习价值，需要的朋友们下面跟着小编一起来学习学习吧。

SpringBatch介绍：

SpringBatch 是一个大数据量的并行处理框架。通常用于数据的离线迁移，和数据处理，⽀持事务、并发、流程、监控、纵向和横向扩展，提供统⼀的接⼝管理和任务管理;SpringBatch是SpringSource和埃森哲为了统一业界并行处理标准为广大开发者提供方便开发的一套框架。

官方地址：github.com/spring-projects/spring-batch

SpringBatch 本身提供了重试，异常处理，跳过，重启、任务处理统计，资源管理等特性，这些特性开发者看重他的主要原因;
SpringBatch 是一个轻量级的批处理框架;
SpringBatch 结构分层，业务与处理策略、结构分离;
任务的运行的实例状态，执行数据，参数都会落地到数据库;

快速入门

pom.xml 添加

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

创建BatchConfig(可以是其他类名)

@Configuration
@EnableBatchProcessing
public class BatchConfig {
 // tag::readerwriterprocessor[]
 @Bean
 public FlatFileItemReader<Person> flatFileItemReader() {
  FlatFileItemReader<Person> reader = new FlatFileItemReader<>();
  reader.setResource(new ClassPathResource("sample-data.csv"));
  FixedLengthTokenizer fixedLengthTokenizer = new FixedLengthTokenizer();
  reader.setLineMapper(new DefaultLineMapper<Person>() {{
   setLineTokenizer(new DelimitedLineTokenizer() {{
    setNames(new String[]{"firstName", "lastName"});
   }});
   setFieldSetMapper(new BeanWrapperFieldSetMapper<Person>() {{
    setTargetType(Person.class);
   }});
  }});
  return reader;
 }
 @Bean
 public JdbcPagingItemReader<Person> jdbcPagingItemReader(DataSource dataSource) {
  JdbcPagingItemReader<Person> reader = new JdbcPagingItemReader<>();
  reader.setDataSource(dataSource);
  reader.setFetchSize(100);
  reader.setQueryProvider(new MySqlPagingQueryProvider() {{
   setSelectClause("SELECT person_id,first_name,last_name");
   setFromClause("from people");
   setWhereClause("last_name=:lastName");
   setSortKeys(new HashMap<String, Order>() {{
    put("person_id", Order.ASCENDING);
   }});
  }});
  reader.setParameterValues(new HashMap<String, Object>() {{
   put("lastName", "DOE");
  }});
  reader.setRowMapper(new BeanPropertyRowMapper<>(Person.class));
  return reader;
 }
 @Bean
 public JdbcBatchItemWriter<Person> jdbcBatchItemWriter(DataSource dataSource) {
  JdbcBatchItemWriter<Person> writer = new JdbcBatchItemWriter<>();
  writer.setItemSqlParameterSourceProvider(new BeanPropertyItemSqlParameterSourceProvider<>());
  writer.setSql("INSERT INTO people (first_name, last_name) VALUES (:firstName, :lastName)");
  writer.setDataSource(dataSource);
  return writer;
 }
 /*@Bean
 public FlatFileItemWriter<Person> flatFileItemWriter(DataSource dataSource) {
  FlatFileItemWriter<Person> writer = new FlatFileItemWriter<>();
  writer.setAppendAllowed(true);
  writer.setEncoding("UTF-8");
//  writer.set(dataSource);
  return writer;
 }*/
 // end::readerwriterprocessor[]
 // tag::jobstep[]
 @Bean
 public Job importUserJob(JobBuilderFactory jobBuilderFactory, JobCompletionNotificationListener listener, Step step) {
  return jobBuilderFactory.get("importUserJob")
    .incrementer(new RunIdIncrementer())
    .listener(listener)
    .start(step)
    .build();
 }
 @Bean
 public Step step1(StepBuilderFactory stepBuilderFactory, PersonItemProcessor processor, ItemWriter jdbcBatchItemWriter, ItemReader flatFileItemReader) {
  /*CompositeItemProcessor compositeItemProcessor = new CompositeItemProcessor();
  compositeItemProcessor.setDelegates(Lists.newArrayList(processor, processor));*/
  return stepBuilderFactory.get("step1")
    .<Person, Person>chunk(10)
    .reader(flatFileItemReader)
    .processor(processor)
    .writer(jdbcBatchItemWriter)
    .build();
 }
 // end::jobstep[]
}

Spring Batch的分层架构