Spring Boot - 批处理服务 Spring Boot - Web Socket Spring Boot - Apache Kafka 您可以创建可执行的JAR文件,并使用Maven或Gradle命令运行Spring Boot应用程序,如下所示 对于Maven,您可以使用下面给出的命令 mvn clean install 在“BUILD SUCCESS”之后,您可以在目标目录下找到JAR文件。 对于Gradle,您可以使用如下所示的命令 gradle clean build 在“BUILD SUCCESSFUL”之后,您可以在build/libs目录下找到JAR文件。 使用此处给出的命令运行JAR文件 java –jar <JARFILE> 现在,应用程序已在Tomcat端口8080上启动,如图所示。 现在,在Web浏览器中点击URL http://localhost:8080/并连接Web套接字并发送问候语并接收消息。 批处理服务是在单个任务中执行多个命令的过程。在本章中,您将学习如何在Spring Boot应用程序中创建批处理服务。 让我们考虑一个示例,我们将CSV文件内容保存到HSQLDB中。 要创建Batch Service程序,我们需要在构建配置文件中添加Spring Boot Starter Batch依赖项和HSQLDB依赖项。 Maven用户可以在pom.xml文件中添加以下依赖项。 <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-batch</artifactId> </dependency> <dependency> <groupId>org.hsqldb</groupId> <artifactId>hsqldb</artifactId> </dependency> Gradle用户可以在build.gradle文件中添加以下依赖项。 compile("org.springframework.boot:spring-boot-starter-batch") compile("org.hsqldb:hsqldb") 现在,在classpath资源 - src / main / resources下添加简单的CSV数据文件,并将文件命名为file.csv,如图所示 - William,John Mike, Sebastian Lawarance, Lime 接下来,为HSQLDB编写一个SQL脚本 - 在classpath资源目录下 - request_fail_hystrix_timeout DROP TABLE USERS IF EXISTS; CREATE TABLE USERS ( user_id BIGINT IDENTITY NOT NULL PRIMARY KEY, first_name VARCHAR(20), last_name VARCHAR(20) ); 为USERS模型创建一个POJO类,如图所示 package com.codingdict.batchservicedemo; public class User { private String lastName; private String firstName; public User() { } public User(String firstName, String lastName) { this.firstName = firstName; this.lastName = lastName; } public void setFirstName(String firstName) { this.firstName = firstName; } public String getFirstName() { return firstName; } public String getLastName() { return lastName; } public void setLastName(String lastName) { this.lastName = lastName; } @Override public String toString() { return "firstName: " + firstName + ", lastName: " + lastName; } } 现在,创建一个中间处理器,在从CSV文件读取数据之后和将数据写入SQL之前执行操作。 package com.codingdict.batchservicedemo; import org.slf4j.Logger; import org.slf4j.LoggerFactory; import org.springframework.batch.item.ItemProcessor; public class UserItemProcessor implements ItemProcessor<User, User> { private static final Logger log = LoggerFactory.getLogger(UserItemProcessor.class); @Override public User process(final User user) throws Exception { final String firstName = user.getFirstName().toUpperCase(); final String lastName = user.getLastName().toUpperCase(); final User transformedPerson = new User(firstName, lastName); log.info("Converting (" + user + ") into (" + transformedPerson + ")"); return transformedPerson; } } 让我们创建一个Batch配置文件,从CSV读取数据并写入SQL文件,如下所示。我们需要在配置类文件中添加@EnableBatchProcessing注释。@EnableBatchProcessing注释用于启用Spring Boot应用程序的批处理操作。 package com.codingdict.batchservicedemo; import javax.sql.DataSource; import org.springframework.batch.core.Job; import org.springframework.batch.core.Step; import org.springframework.batch.core.configuration.annotation.EnableBatchProcessing; import org.springframework.batch.core.configuration.annotation.JobBuilderFactory; import org.springframework.batch.core.configuration.annotation.StepBuilderFactory; import org.springframework.batch.core.launch.support.RunIdIncrementer; import org.springframework.batch.item.database.BeanPropertyItemSqlParameterSourceProvider; import org.springframework.batch.item.database.JdbcBatchItemWriter; import org.springframework.batch.item.file.FlatFileItemReader; import org.springframework.batch.item.file.mapping.BeanWrapperFieldSetMapper; import org.springframework.batch.item.file.mapping.DefaultLineMapper; import org.springframework.batch.item.file.transform.DelimitedLineTokenizer; import org.springframework.beans.factory.annotation.Autowired; import org.springframework.context.annotation.Bean; import org.springframework.context.annotation.Configuration; import org.springframework.core.io.ClassPathResource; @Configuration @EnableBatchProcessing public class BatchConfiguration { @Autowired public JobBuilderFactory jobBuilderFactory; @Autowired public StepBuilderFactory stepBuilderFactory; @Autowired public DataSource dataSource; @Bean public FlatFileItemReader<User> reader() { FlatFileItemReader<User> reader = new FlatFileItemReader<User>(); reader.setResource(new ClassPathResource("file.csv")); reader.setLineMapper(new DefaultLineMapper<User>() { { setLineTokenizer(new DelimitedLineTokenizer() { { setNames(new String[] { "firstName", "lastName" }); } }); setFieldSetMapper(new BeanWrapperFieldSetMapper<User>() { { setTargetType(User.class); } }); } }); return reader; } @Bean public UserItemProcessor processor() { return new UserItemProcessor(); } @Bean public JdbcBatchItemWriter<User> writer() { JdbcBatchItemWriter<User> writer = new JdbcBatchItemWriter<User>(); writer.setItemSqlParameterSourceProvider(new BeanPropertyItemSqlParameterSourceProvider<User>()); writer.setSql("INSERT INTO USERS (first_name, last_name) VALUES (:firstName, :lastName)"); writer.setDataSource(dataSource); return writer; } @Bean public Job importUserJob(JobCompletionNotificationListener listener) { return jobBuilderFactory.get("importUserJob").incrementer( new RunIdIncrementer()).listener(listener).flow(step1()).end().build(); } @Bean public Step step1() { return stepBuilderFactory.get("step1").<User, User>chunk(10).reader(reader()).processor(processor()).writer(writer()).build(); } } 该读取器()方法用来读取从CSV文件和写入器()方法中的数据是用来写数据到SQL。 接下来,我们将编写一个Job Completion Notification Listener类 - 用于在Job完成后通知。 package com.codingdict.batchservicedemo; import java.sql.ResultSet; import java.sql.SQLException; import java.util.List; import org.slf4j.Logger; import org.slf4j.LoggerFactory; import org.springframework.batch.core.BatchStatus; import org.springframework.batch.core.JobExecution; import org.springframework.batch.core.listener.JobExecutionListenerSupport; import org.springframework.beans.factory.annotation.Autowired; import org.springframework.jdbc.core.JdbcTemplate; import org.springframework.jdbc.core.RowMapper; import org.springframework.stereotype.Component; @Component public class JobCompletionNotificationListener extends JobExecutionListenerSupport { private static final Logger log = LoggerFactory.getLogger(JobCompletionNotificationListener.class); private final JdbcTemplate jdbcTemplate; @Autowired public JobCompletionNotificationListener(JdbcTemplate jdbcTemplate) { this.jdbcTemplate = jdbcTemplate; } @Override public void afterJob(JobExecution jobExecution) { if (jobExecution.getStatus() == BatchStatus.COMPLETED) { log.info("!!! JOB FINISHED !! It's time to verify the results!!"); List<User> results = jdbcTemplate.query( "SELECT first_name, last_name FROM USERS", new RowMapper<User>() { @Override public User mapRow(ResultSet rs, int row) throws SQLException { return new User(rs.getString(1), rs.getString(2)); } }); for (User person : results) { log.info("Found <" + person + "> in the database."); } } } } 现在,创建一个可执行的JAR文件,并使用以下Maven或Gradle命令运行Spring Boot应用程序。 对于Maven,使用如下所示的命令 mvn clean install 在“BUILD SUCCESS”之后,您可以在目标目录下找到JAR文件。 对于Gradle,您可以使用如下所示的命令 gradle clean build 在“BUILD SUCCESSFUL”之后,您可以在build / libs目录下找到JAR文件。 使用此处给出的命令运行JAR文件 java –jar <JARFILE> 您可以在控制台窗口中看到输出,如图所示 Spring Boot - Web Socket Spring Boot - Apache Kafka