java 63 lines · 9 steps

How a chunk-based CSV import job works in Spring

A Spring Batch job reads customers from CSV, cleans each record, and writes them to the database in fault-tolerant chunks.

Explained by highlit

Spring Intermediate batch-processing etl csv-parsing fault-tolerance chunking

1@Configuration
2@EnableBatchProcessing
3public class CustomerImportJobConfig {
4 
  @Bean
  public FlatFileItemReader<CustomerCsvRecord> customerReader() {
      return new FlatFileItemReaderBuilder<CustomerCsvRecord>()
              .name("customerReader")
              .resource(new ClassPathResource("customers.csv"))
              .linesToSkip(1)
              .delimited()
              .names("externalId", "firstName", "lastName", "email", "signupDate")
              .fieldSetMapper(fieldSet -> new CustomerCsvRecord(
                      fieldSet.readString("externalId"),
                      fieldSet.readString("firstName"),
                      fieldSet.readString("lastName"),
                      fieldSet.readString("email"),
                      fieldSet.readDate("signupDate", "yyyy-MM-dd")))
              .build();
  }
21 
  @Bean
  public ItemProcessor<CustomerCsvRecord, Customer> customerProcessor() {
      return record -> {
          if (record.email() == null || record.email().isBlank()) {
              return null;
          }
          Customer customer = new Customer();
          customer.setExternalId(record.externalId());
          customer.setName(record.firstName().trim() + " " + record.lastName().trim());
          customer.setEmail(record.email().toLowerCase());
          customer.setSignupDate(record.signupDate());
          return customer;
      };
  }
36 
  @Bean
  public JdbcBatchItemWriter<Customer> customerWriter(DataSource dataSource) {
      return new JdbcBatchItemWriterBuilder<Customer>()
              .dataSource(dataSource)
              .sql("INSERT INTO customers (external_id, name, email, signup_date) "
                      + "VALUES (:externalId, :name, :email, :signupDate)")
              .beanMapped()
              .build();
  }
46 
  @Bean
  public Step importCustomersStep(JobRepository jobRepository,
                                   PlatformTransactionManager txManager,
                                   FlatFileItemReader<CustomerCsvRecord> customerReader,
                                   ItemProcessor<CustomerCsvRecord, Customer> customerProcessor,
                                   JdbcBatchItemWriter<Customer> customerWriter) {
      return new StepBuilder("importCustomersStep", jobRepository)
              .<CustomerCsvRecord, Customer>chunk(200, txManager)
              .reader(customerReader)
              .processor(customerProcessor)
              .writer(customerWriter)
              .faultTolerant()
              .skip(FlatFileParseException.class)
              .skipLimit(25)
              .build();
  }
63}

01 / 01

STEP 01

Walkthrough

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Three takeaways

1Spring Batch's reader-processor-writer triad cleanly separates parsing, transformation, and persistence into swappable beans.
2Chunk-oriented steps commit work in fixed-size batches inside a transaction, balancing throughput against memory and rollback scope.
3A processor returning null filters an item out, and fault tolerance lets bad rows be skipped without aborting the whole job.

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