通过Spring batch的官方文档，学习springbatch, 记录每个实列。
本案例是官方提供的第一个入门实列
官方文档地址
https://spring.io/guides/gs/batch-processing/#scratch
源码地址
https://gitee.com/bseaworkspace/study_java_web/tree/master/springbatchdemobasic
代码结构
业务数据
Typically, your customer or a business analyst supplies a spreadsheet. For this simple example, you can find some made-up data in src/main/resources/sample-data.csv:
比如用户提供了一个需要处理的表格数据。
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Jill,Doe
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Joe,Doe
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Justin,Doe
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Jane,Doe
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John,Doe
这个表格数据 每一行包含了 名和姓 并且用逗号隔开。
接下来，我们需要准备一个sql 用来创建需要的数据表 src/main/resources/schema-all.sql:
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DROP TABLE people IF EXISTS;
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CREATE TABLE people (
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person_id BIGINT IDENTITY NOT NULL PRIMARY KEY,
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first_name VARCHAR(20),
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last_name VARCHAR(20)
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);
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开始代码实现
设置Maven的pom文件
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<?xml version="1.0" encoding="UTF-8"?>
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<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
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xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd">
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<modelVersion>4.0.0</modelVersion>
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<parent>
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<groupId>org.springframework.boot</groupId>
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<artifactId>spring-boot-starter-parent</artifactId>
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<version>2.4.3</version>
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<relativePath/> <!-- lookup parent from repository -->
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</parent>
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<groupId>com.example</groupId>
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<artifactId>batch-processing</artifactId>
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<version>0.0.1-SNAPSHOT</version>
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<name>batch-processing</name>
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<description>Demo project for Spring Boot</description>
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<properties>
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<java.version>1.8</java.version>
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</properties>
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<dependencies>
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<dependency>
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<groupId>org.springframework.boot</groupId>
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<artifactId>spring-boot-starter-batch</artifactId>
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</dependency>
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<dependency>
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<groupId>org.hsqldb</groupId>
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<artifactId>hsqldb</artifactId>
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<scope>runtime</scope>
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</dependency>
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<dependency>
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<groupId>org.springframework.boot</groupId>
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<artifactId>spring-boot-starter-test</artifactId>
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<scope>test</scope>
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</dependency>
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<dependency>
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<groupId>org.springframework.batch</groupId>
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<artifactId>spring-batch-test</artifactId>
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<scope>test</scope>
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</dependency>
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</dependencies>
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<build>
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<plugins>
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<plugin>
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<groupId>org.springframework.boot</groupId>
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<artifactId>spring-boot-maven-plugin</artifactId>
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</plugin>
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</plugins>
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</build>
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</project>
业务实体类
Now that you can see the format of data inputs and outputs, you can write code to represent a row of data, as the following example shows:
用来定义数据的输入和输出的格式，一个实体类的对象，就对于前面表格数据的一行数据。
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package com.xsz.entity;
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public class Person {
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private String lastName;
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private String firstName;
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public Person() {
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}
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public Person(String firstName, String lastName) {
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this.firstName = firstName;
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this.lastName = lastName;
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}
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public void setFirstName(String firstName) {
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this.firstName = firstName;
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}
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public String getFirstName() {
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return firstName;
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}
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public String getLastName() {
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return lastName;
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}
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public void setLastName(String lastName) {
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this.lastName = lastName;
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}
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@Override
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public String toString() {
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return "firstName: " + firstName + ", lastName: " + lastName;
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}
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}
Create an Intermediate Processor 创建中间处理类
A common paradigm in batch processing is to ingest data, transform it, and then pipe it out somewhere else. Here, you need to write a simple transformer that converts the names to uppercase. The following listing
这个中间处理类，主要是把输入对象的姓名属性的值，转换成大写。
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package com.xsz.processor;
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import com.xsz.entity.Person;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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import org.springframework.batch.item.ItemProcessor;
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public class PersonItemProcessor implements ItemProcessor<Person, Person> {
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private static final Logger log = LoggerFactory.getLogger(PersonItemProcessor.class);
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@Override
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public Person process(final Person person) throws Exception {
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final String firstName = person.getFirstName().toUpperCase();
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final String lastName = person.getLastName().toUpperCase();
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final Person transformedPerson = new Person(firstName, lastName);
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log.info("Converting (" + person + ") into (" + transformedPerson + ")");
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return transformedPerson;
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}
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}
Put Together a Batch Job 创建批处理job
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@Configuration 放在java类上面，表示这个是配置类，代替xml文件 -
@EnableBatchProcessing
@EnableBatchProcessing
这个注解的作用，和spring 家庭中的@Enable* 系列注解功能很类似。顾名思义，就是让我们可以运行Spring Batch。在配置类上打上这个注解，spring 会自动 帮我们生成一系列与spring batch 运行有关的bean，并交给spring容器管理，而当我们需要这些beans时，只需要用一个@autowired就可以实现注入了。
自动生成的bean及名称如下：
JobRepository - bean name "jobRepository"
JobLauncher - bean name "jobLauncher"
JobRegistry - bean name "jobRegistry"
PlatformTransactionManager - bean name "transactionManager"
JobBuilderFactory - bean name "jobBuilders"
StepBuilderFactory - bean name "stepBuilders"@EnableBatchProcessing 背后所调用的接口是BatchConfigurer
我们可以改变@EnableBatchProcessing 给我们的对象。
比如，我们想让返回的jobRepository用上我们自定义的数据源，想让元数据的表前缀变成SPRING_BATCH_，而不是默认的BATCH_前缀，@EnableBatchProcessing 提供了让我们覆写的接口。
The first chunk of code defines the input, processor, and output. 一个chunk 需要配置对应的 输入，中间处理，输出
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reader()creates anItemReader. It looks for a file calledsample-data.csvand parses each line item with enough information to turn it into aPerson. reader()方法里面定义了数据输入的规则，读取csv的文件内容，每行对应一个person对象 -
processor()creates an instance of thePersonItemProcessorthat you defined earlier, meant to convert the data to upper case. 把reader读到jvm里面的person对象属性值变成大写。 -
writer(DataSource)creates anItemWriter. This one is aimed at a JDBC destination and automatically gets a copy of the dataSource created by@EnableBatchProcessing. It includes the SQL statement needed to insert a singlePerson, driven by Java bean properties.
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package com.xsz.config;
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import com.xsz.entity.Person;
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import com.xsz.processor.PersonItemProcessor;
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import org.springframework.batch.core.Job;
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import org.springframework.batch.core.Step;
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import org.springframework.batch.core.configuration.annotation.EnableBatchProcessing;
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import org.springframework.batch.core.configuration.annotation.JobBuilderFactory;
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import org.springframework.batch.core.configuration.annotation.StepBuilderFactory;
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import org.springframework.batch.core.launch.support.RunIdIncrementer;
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import org.springframework.batch.item.database.BeanPropertyItemSqlParameterSourceProvider;
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import org.springframework.batch.item.database.JdbcBatchItemWriter;
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import org.springframework.batch.item.database.builder.JdbcBatchItemWriterBuilder;
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import org.springframework.batch.item.file.FlatFileItemReader;
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import org.springframework.batch.item.file.builder.FlatFileItemReaderBuilder;
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import org.springframework.batch.item.file.mapping.BeanWrapperFieldSetMapper;
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import org.springframework.beans.factory.annotation.Autowired;
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import org.springframework.context.annotation.Bean;
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import org.springframework.context.annotation.Configuration;
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import org.springframework.core.io.ClassPathResource;
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import javax.sql.DataSource;
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@Configuration
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@EnableBatchProcessing
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public class BatchConfiguration {
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@Autowired
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public JobBuilderFactory jobBuilderFactory;
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@Autowired
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public StepBuilderFactory stepBuilderFactory;
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// ...
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@Bean
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public FlatFileItemReader<Person> reader() {
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return new FlatFileItemReaderBuilder<Person>()
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.name("personItemReader")
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.resource(new ClassPathResource("sample-data.csv"))
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.delimited()
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.names(new String[]{"firstName", "lastName"})
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.fieldSetMapper(new BeanWrapperFieldSetMapper<Person>() {{
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setTargetType(Person.class);
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}})
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.build();
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}
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@Bean
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public PersonItemProcessor processor() {
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return new PersonItemProcessor();
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}
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@Bean
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public JdbcBatchItemWriter<Person> writer(DataSource dataSource) {
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return new JdbcBatchItemWriterBuilder<Person>()
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.itemSqlParameterSourceProvider(new BeanPropertyItemSqlParameterSourceProvider<>())
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.sql("INSERT INTO people (first_name, last_name) VALUES (:firstName, :lastName)")
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.dataSource(dataSource)
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.build();
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}
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@Bean
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public Job importUserJob(JobCompletionNotificationListener listener, Step step1) {
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return jobBuilderFactory.get("importUserJob")
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.incrementer(new RunIdIncrementer())
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.listener(listener)
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.flow(step1)
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.end()
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.build();
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}
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@Bean
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public Step step1(JdbcBatchItemWriter<Person> writer) {
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return stepBuilderFactory.get("step1")
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.<Person, Person> chunk(10)
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.reader(reader())
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.processor(processor())
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.writer(writer)
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.build();
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}
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}
文章来源: blog.csdn.net，作者：bseayin，版权归原作者所有，如需转载，请联系作者。
原文链接：blog.csdn.net/h356363/article/details/115024776