Spring Boot 4 Microservices & REST APIs · 课时

读取器、处理器和写入器

构建面向数据块的批处理流程

读取器、处理器和写入器 是 CoddyKit 上的免费 Spring Boot 4 Microservices & REST APIs 课时。这是第 3 节课，共 4 节。你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。这是 Spring Boot 4 Microservices & REST APIs 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 Spring Boot 4 Microservices & REST APIs 课程共包含 4 节课。

本课时的部分内容尚未翻译，以英文显示。

The read-process-write triad

A chunk step has three collaborators:

ItemReader - supplies items one at a time
ItemProcessor - transforms or filters an item
ItemWriter - persists a chunk of items

ItemReader interface

ItemReader.read() returns the next item, or null when the input is exhausted. Spring Batch keeps calling it until it returns null.

public interface ItemReader<T> {
    T read() throws Exception;
}

FlatFileItemReader

For CSV files, FlatFileItemReader reads lines and maps them to objects via a line mapper.

@Bean
public FlatFileItemReader<Person> reader() {
    return new FlatFileItemReaderBuilder<Person>()
            .name("personReader")
            .resource(new ClassPathResource("people.csv"))
            .delimited()
            .names("firstName", "lastName")
            .targetType(Person.class)
            .build();
}

JdbcCursorItemReader

To read from a database, use JdbcCursorItemReader or JdbcPagingItemReader. Paging is preferred for very large result sets to avoid holding a long cursor.

@Bean
public JdbcCursorItemReader<Person> dbReader(DataSource ds) {
    return new JdbcCursorItemReaderBuilder<Person>()
            .name("dbReader")
            .dataSource(ds)
            .sql("SELECT first_name, last_name FROM people")
            .rowMapper(new PersonRowMapper())
            .build();
}

ItemProcessor interface

ItemProcessor transforms an input item into an output item. The input and output types can differ.

public interface ItemProcessor<I, O> {
    O process(I item) throws Exception;
}

Writing a processor

Here a processor uppercases names. Returning a transformed object is the common case.

public class UpperCaseProcessor implements ItemProcessor<Person, Person> {
    @Override
    public Person process(Person p) {
        return new Person(p.getFirstName().toUpperCase(),
                          p.getLastName().toUpperCase());
    }
}

Filtering with the processor

If a processor returns null, the item is filtered out and never reaches the writer. This is how you skip records based on business rules.

public Person process(Person p) {
    if (p.getLastName().isBlank()) {
        return null; // drop this record
    }
    return p;
}

ItemWriter interface

ItemWriter receives a chunk of items at once, not single items. This lets it batch the write into one efficient operation.

public interface ItemWriter<T> {
    void write(Chunk<? extends T> chunk) throws Exception;
}

JdbcBatchItemWriter

JdbcBatchItemWriter performs a batched SQL insert/update for the whole chunk, which is far faster than row-by-row writes.

@Bean
public JdbcBatchItemWriter<Person> writer(DataSource ds) {
    return new JdbcBatchItemWriterBuilder<Person>()
            .dataSource(ds)
            .sql("INSERT INTO people (first_name, last_name) VALUES (:firstName, :lastName)")
            .beanMapped()
            .build();
}

Wiring them into a step

The step ties the triad together with a chunk size. Items flow reader -> processor -> writer in chunks.

return new StepBuilder("step1", repo)
        .<Person, Person>chunk(50, tx)
        .reader(reader())
        .processor(new UpperCaseProcessor())
        .writer(writer(ds))
        .build();

Custom readers and writers

You can implement the interfaces directly for custom sources (a REST API, a queue). Spring also offers ItemStream so your component can save and restore its position for restarts.

Quick Check

Verify your understanding of the triad.

Recap

You assembled a chunk pipeline:

ItemReader.read() returns items until null
ItemProcessor transforms; returning null filters
ItemWriter writes a whole Chunk at once
The step binds all three with a chunk size

常见问题解答

「读取器、处理器和写入器」课时是免费的吗？

是的 — 「读取器、处理器和写入器」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 Spring Boot 4 Microservices & REST APIs 课程的其余内容，请升级到 CoddyKit PRO。 Spring Boot 4 Microservices & REST APIs 课程共包含 4 节课。

「读取器、处理器和写入器」这节课中我会学到什么？

构建面向数据块的批处理流程你通过在浏览器中直接运行的动手代码来练习 Spring Boot 4 Microservices & REST APIs，全天候 AI 导师会在你学习这节课的过程中回答你的问题。

学习 Spring Boot 4 Microservices & REST APIs 需要有经验吗？

无需任何先前经验。CoddyKit 上的 Spring Boot 4 Microservices & REST APIs 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。这是第 3 节课，共 4 节。

「读取器、处理器和写入器」课时需要多长时间？

大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。

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