Spring Batch入門教程篇

更新時間：2017年06月09日 11:20:37 作者：翟永超

這篇文章主要給大家介紹了Spring Batch入門的相關資料，文中介紹的非常詳細，對大家具有一定的參考學習價值，需要的朋友們下面跟著小編一起來學習學習吧。

SpringBatch介紹：

SpringBatch 是一個大數(shù)據(jù)量的并行處理框架。通常用于數(shù)據(jù)的離線遷移，和數(shù)據(jù)處理，⽀持事務、并發(fā)、流程、監(jiān)控、縱向和橫向擴展，提供統(tǒng)⼀的接⼝管理和任務管理;SpringBatch是SpringSource和埃森哲為了統(tǒng)一業(yè)界并行處理標準為廣大開發(fā)者提供方便開發(fā)的一套框架。

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

SpringBatch 本身提供了重試，異常處理，跳過，重啟、任務處理統(tǒng)計，資源管理等特性，這些特性開發(fā)者看重他的主要原因;
SpringBatch 是一個輕量級的批處理框架;
SpringBatch 結構分層，業(yè)務與處理策略、結構分離;
任務的運行的實例狀態(tài)，執(zhí)行數(shù)據(jù)，參數(shù)都會落地到數(shù)據(jù)庫;

快速入門

pom.xml 添加

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

創(chuàng)建BatchConfig(可以是其他類名)

@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的分層架構