SpringBatch主要是一个轻量级的大数据量的并行处理(批处理)的框架。
作用和Hadoop很相似，不过Hadoop是基于重量级的分布式环境(处理巨量数据)，而SpringBatch是基于轻量的应用框架(处理中小数据)。
这里使用SpringBatch做了一个能跑的最简单例子，进行描述SpringBatch的基本作用。
如果需要进行深入学习，请详细参考阅读 https://docs.spring.io/spring-batch/4.0.x/reference/html/index.html ；英文不好的同学，请和我一样右键(翻译成中文查看)。
简单的技术栈 : SpringBoot + SpringBatch + JPA ， 完整demo的项目地址 : https://github.com/EalenXie/springboot-batch
1 . 新建项目springboot-batch，基本的pom.xml依赖 :
<?xml version="1.0" encoding="UTF-8"?> <project xmlns="http://maven.apache.org/POM/4.0.0"xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd"><modelVersion>4.0.0</modelVersion><groupId>name.ealen</groupId><artifactId>springboot-batch</artifactId><version>1.0</version><parent><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-parent</artifactId><version>2.0.1.RELEASE</version></parent><dependencies><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-batch</artifactId></dependency><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-data-jpa</artifactId></dependency><dependency><groupId>mysql</groupId><artifactId>mysql-connector-java</artifactId><scope>runtime</scope></dependency></dependencies> </project>
2 . 你需要在数据库中建立springbatch的相关元数据表，所以你需要在数据库中执行如下来自官方元数据模式的脚本。
-- do not edit this file -- BATCH JOB 实例表 包含与aJobInstance相关的所有信息 -- JOB ID由batch_job_seq分配 -- JOB 名称,与spring配置一致 -- JOB KEY 对job参数的MD5编码,正因为有这个字段的存在，同一个job如果第一次运行成功，第二次再运行会抛出JobInstanceAlreadyCompleteException异常。 CREATE TABLE BATCH_JOB_INSTANCE (JOB_INSTANCE_ID BIGINT NOT NULL PRIMARY KEY ,VERSION BIGINT ,JOB_NAME VARCHAR(100) NOT NULL,JOB_KEY VARCHAR(32) NOT NULL,constraint JOB_INST_UN unique (JOB_NAME, JOB_KEY) ) ENGINE=InnoDB; -- 该BATCH_JOB_EXECUTION表包含与该JobExecution对象相关的所有信息 CREATE TABLE BATCH_JOB_EXECUTION (JOB_EXECUTION_ID BIGINT NOT NULL PRIMARY KEY ,VERSION BIGINT ,JOB_INSTANCE_ID BIGINT NOT NULL,CREATE_TIME DATETIME NOT NULL,START_TIME DATETIME DEFAULT NULL ,END_TIME DATETIME DEFAULT NULL ,STATUS VARCHAR(10) ,EXIT_CODE VARCHAR(2500) ,EXIT_MESSAGE VARCHAR(2500) ,LAST_UPDATED DATETIME,JOB_CONFIGURATION_LOCATION VARCHAR(2500) NULL,constraint JOB_INST_EXEC_FK foreign key (JOB_INSTANCE_ID)references BATCH_JOB_INSTANCE(JOB_INSTANCE_ID) ) ENGINE=InnoDB; -- 该表包含与该JobParameters对象相关的所有信息 CREATE TABLE BATCH_JOB_EXECUTION_PARAMS (JOB_EXECUTION_ID BIGINT NOT NULL ,TYPE_CD VARCHAR(6) NOT NULL ,KEY_NAME VARCHAR(100) NOT NULL ,STRING_VAL VARCHAR(250) ,DATE_VAL DATETIME DEFAULT NULL ,LONG_VAL BIGINT ,DOUBLE_VAL DOUBLE PRECISION ,IDENTIFYING CHAR(1) NOT NULL ,constraint JOB_EXEC_PARAMS_FK foreign key (JOB_EXECUTION_ID)references BATCH_JOB_EXECUTION(JOB_EXECUTION_ID) ) ENGINE=InnoDB; -- 该表包含与该StepExecution 对象相关的所有信息 CREATE TABLE BATCH_STEP_EXECUTION (STEP_EXECUTION_ID BIGINT NOT NULL PRIMARY KEY ,VERSION BIGINT NOT NULL,STEP_NAME VARCHAR(100) NOT NULL,JOB_EXECUTION_ID BIGINT NOT NULL,START_TIME DATETIME NOT NULL ,END_TIME DATETIME DEFAULT NULL ,STATUS VARCHAR(10) ,COMMIT_COUNT BIGINT ,READ_COUNT BIGINT ,FILTER_COUNT BIGINT ,WRITE_COUNT BIGINT ,READ_SKIP_COUNT BIGINT ,WRITE_SKIP_COUNT BIGINT ,PROCESS_SKIP_COUNT BIGINT ,ROLLBACK_COUNT BIGINT ,EXIT_CODE VARCHAR(2500) ,EXIT_MESSAGE VARCHAR(2500) ,LAST_UPDATED DATETIME,constraint JOB_EXEC_STEP_FK foreign key (JOB_EXECUTION_ID)references BATCH_JOB_EXECUTION(JOB_EXECUTION_ID) ) ENGINE=InnoDB; -- 该BATCH_STEP_EXECUTION_CONTEXT表包含ExecutionContext与Step相关的所有信息 CREATE TABLE BATCH_STEP_EXECUTION_CONTEXT (STEP_EXECUTION_ID BIGINT NOT NULL PRIMARY KEY,SHORT_CONTEXT VARCHAR(2500) NOT NULL,SERIALIZED_CONTEXT TEXT ,constraint STEP_EXEC_CTX_FK foreign key (STEP_EXECUTION_ID)references BATCH_STEP_EXECUTION(STEP_EXECUTION_ID) ) ENGINE=InnoDB; -- 该表包含ExecutionContext与Job相关的所有信息 CREATE TABLE BATCH_JOB_EXECUTION_CONTEXT (JOB_EXECUTION_ID BIGINT NOT NULL PRIMARY KEY,SHORT_CONTEXT VARCHAR(2500) NOT NULL,SERIALIZED_CONTEXT TEXT ,constraint JOB_EXEC_CTX_FK foreign key (JOB_EXECUTION_ID)references BATCH_JOB_EXECUTION(JOB_EXECUTION_ID) ) ENGINE=InnoDB; CREATE TABLE BATCH_STEP_EXECUTION_SEQ (ID BIGINT NOT NULL,UNIQUE_KEY CHAR(1) NOT NULL,constraint UNIQUE_KEY_UN unique (UNIQUE_KEY) ) ENGINE=InnoDB; INSERT INTO BATCH_STEP_EXECUTION_SEQ (ID, UNIQUE_KEY) select * from (select 0 as ID, '0' as UNIQUE_KEY) as tmp where not exists(select * from BATCH_STEP_EXECUTION_SEQ); CREATE TABLE BATCH_JOB_EXECUTION_SEQ (ID BIGINT NOT NULL,UNIQUE_KEY CHAR(1) NOT NULL,constraint UNIQUE_KEY_UN unique (UNIQUE_KEY) ) ENGINE=InnoDB; INSERT INTO BATCH_JOB_EXECUTION_SEQ (ID, UNIQUE_KEY) select * from (select 0 as ID, '0' as UNIQUE_KEY) as tmp where not exists(select * from BATCH_JOB_EXECUTION_SEQ); CREATE TABLE BATCH_JOB_SEQ (ID BIGINT NOT NULL,UNIQUE_KEY CHAR(1) NOT NULL,constraint UNIQUE_KEY_UN unique (UNIQUE_KEY) ) ENGINE=InnoDB; INSERT INTO BATCH_JOB_SEQ (ID, UNIQUE_KEY) select * from (select 0 as ID, '0' as UNIQUE_KEY) as tmp where not exists(select * from BATCH_JOB_SEQ);
3 . 测试数据的实体类 : Access.java
package name.ealen.model;import javax.persistence.*; /*** Created by EalenXie on 2018/9/10 16:17.*/ @Entity @Table public class Access {@Id@GeneratedValue(strategy = GenerationType.AUTO)private Integer id;private String username;private String shopName;private String categoryName;private String brandName;private String shopId;private String omit;private String updateTime;private boolean deleteStatus;private String createTime;private String description;public Integer getId() {return id;}public void setId(Integer id) {this.id = id;}public String getUsername() {return username;}public void setUsername(String username) {this.username = username;}public String getShopName() {return shopName;}public void setShopName(String shopName) {this.shopName = shopName;}public String getCategoryName() {return categoryName;}public void setCategoryName(String categoryName) {this.categoryName = categoryName;}public String getBrandName() {return brandName;}public void setBrandName(String brandName) {this.brandName = brandName;}public String getShopId() {return shopId;}public void setShopId(String shopId) {this.shopId = shopId;}public String getOmit() {return omit;}public void setOmit(String omit) {this.omit = omit;}public String getUpdateTime() {return updateTime;}public void setUpdateTime(String updateTime) {this.updateTime = updateTime;}public boolean isDeleteStatus() {return deleteStatus;}public void setDeleteStatus(boolean deleteStatus) {this.deleteStatus = deleteStatus;}public String getCreateTime() {return createTime;}public void setCreateTime(String createTime) {this.createTime = createTime;}public String getDescription() {return description;}public void setDescription(String description) {this.description = description;}@Overridepublic String toString() {return "Access{" +"id=" + id +", username='" + username + '\'' +", shopName='" + shopName + '\'' +", categoryName='" + categoryName + '\'' +", brandName='" + brandName + '\'' +", shopId='" + shopId + '\'' +", omit='" + omit + '\'' +", updateTime='" + updateTime + '\'' +", deleteStatus=" + deleteStatus +", createTime='" + createTime + '\'' +", description='" + description + '\'' +'}';} }
4 . 配置一个最简单的Job 之前，准备一些基本配置，例如为Job添加一个监听器 :
配置TaskExecutor，ExecutorConfiguration.java
package name.ealen.config;import org.springframework.context.annotation.Bean; import org.springframework.context.annotation.Configuration; import org.springframework.scheduling.concurrent.ThreadPoolTaskExecutor;/*** 配置TaskExecutor*/ @Configuration public class ExecutorConfiguration {@Beanpublic ThreadPoolTaskExecutor threadPoolTaskExecutor() {ThreadPoolTaskExecutor threadPoolTaskExecutor = new ThreadPoolTaskExecutor();threadPoolTaskExecutor.setCorePoolSize(50);threadPoolTaskExecutor.setMaxPoolSize(200);threadPoolTaskExecutor.setQueueCapacity(1000);threadPoolTaskExecutor.setThreadNamePrefix("Data-Job");return threadPoolTaskExecutor;} }
为Job准备一个简单的监听器 ，实现JobExecutionListener即可 :
package name.ealen.listener;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.JobExecutionListener; import org.springframework.scheduling.concurrent.ThreadPoolTaskExecutor; import org.springframework.stereotype.Component;import javax.annotation.Resource;/*** Created by EalenXie on 2018/9/10 15:09.* 一个简单的JOB listener*/ @Component public class JobListener implements JobExecutionListener {private static final Logger log = LoggerFactory.getLogger(JobListener.class);@Resourceprivate ThreadPoolTaskExecutor threadPoolTaskExecutor;private long startTime;@Overridepublic void beforeJob(JobExecution jobExecution) {startTime = System.currentTimeMillis();log.info("job before " + jobExecution.getJobParameters());}@Overridepublic void afterJob(JobExecution jobExecution) {log.info("JOB STATUS : {}", jobExecution.getStatus());if (jobExecution.getStatus() == BatchStatus.COMPLETED) {log.info("JOB FINISHED");threadPoolTaskExecutor.destroy();} else if (jobExecution.getStatus() == BatchStatus.FAILED) {log.info("JOB FAILED");}log.info("Job Cost Time : {}ms" , (System.currentTimeMillis() - startTime));} }
5 . 配置一个最基本的Job : 一个Job 通常由一个或多个Step组成(基本就像是一个工作流)；一个Step通常由三部分组成(读入数据 ItemReader，处理数据 ItemProcessor，写入数据 ItemWriter)
package name.ealen.batch;import name.ealen.listener.JobListener; import name.ealen.model.Access; import org.slf4j.Logger; import org.slf4j.LoggerFactory; 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.ItemProcessor; import org.springframework.batch.item.ItemReader; import org.springframework.batch.item.ItemWriter; import org.springframework.batch.item.database.JpaPagingItemReader; import org.springframework.batch.item.database.orm.JpaNativeQueryProvider; import org.springframework.context.annotation.Bean; import org.springframework.context.annotation.Configuration;import javax.annotation.Resource; import javax.persistence.EntityManagerFactory;/*** Created by EalenXie on 2018/9/10 14:50.* :@EnableBatchProcessing提供用于构建批处理作业的基本配置*/ @Configuration @EnableBatchProcessing public class DataBatchConfiguration {private static final Logger log = LoggerFactory.getLogger(DataBatchConfiguration.class);@Resourceprivate JobBuilderFactory jobBuilderFactory; //用于构建JOB @Resourceprivate StepBuilderFactory stepBuilderFactory; //用于构建Step @Resourceprivate EntityManagerFactory emf; //注入实例化Factory 访问数据 @Resourceprivate JobListener jobListener; //简单的JOB listener/*** 一个简单基础的Job通常由一个或者多个Step组成*/@Beanpublic Job dataHandleJob() {return jobBuilderFactory.get("dataHandleJob").incrementer(new RunIdIncrementer()).start(handleDataStep()). //start是JOB执行的第一个step // next(xxxStep()). // next(xxxStep()). // ...listener(jobListener). //设置了一个简单JobListener build();}/*** 一个简单基础的Step主要分为三个部分* ItemReader : 用于读取数据* ItemProcessor : 用于处理数据* ItemWriter : 用于写数据*/@Beanpublic Step handleDataStep() {return stepBuilderFactory.get("getData").<Access, Access>chunk(100). // <输入,输出> 。chunk通俗的讲类似于SQL的commit; 这里表示处理(processor)100条后写入(writer)一次。faultTolerant().retryLimit(3).retry(Exception.class).skipLimit(100).skip(Exception.class). //捕捉到异常就重试,重试100次还是异常,JOB就停止并标志失败reader(getDataReader()). //指定ItemReaderprocessor(getDataProcessor()). //指定ItemProcessorwriter(getDataWriter()). //指定ItemWriter build();}@Beanpublic ItemReader<? extends Access> getDataReader() {//读取数据,这里可以用JPA,JDBC,JMS 等方式 读入数据JpaPagingItemReader<Access> reader = new JpaPagingItemReader<>();//这里选择JPA方式读数据 一个简单的 native SQLString sqlQuery = "SELECT * FROM access";try {JpaNativeQueryProvider<Access> queryProvider = new JpaNativeQueryProvider<>();queryProvider.setSqlQuery(sqlQuery);queryProvider.setEntityClass(Access.class);queryProvider.afterPropertiesSet();reader.setEntityManagerFactory(emf);reader.setPageSize(3);reader.setQueryProvider(queryProvider);reader.afterPropertiesSet();//所有ItemReader和ItemWriter实现都会在ExecutionContext提交之前将其当前状态存储在其中,如果不希望这样做,可以设置setSaveState(false)reader.setSaveState(true);} catch (Exception e) {e.printStackTrace();}return reader;}@Beanpublic ItemProcessor<Access, Access> getDataProcessor() {return new ItemProcessor<Access, Access>() {@Overridepublic Access process(Access access) throws Exception {log.info("processor data : " + access.toString()); //模拟 假装处理数据,这里处理就是打印一下return access;}}; // lambda也可以写为: // return access -> { // log.info("processor data : " + access.toString()); // return access; // }; }@Beanpublic ItemWriter<Access> getDataWriter() {return list -> {for (Access access : list) {log.info("write data : " + access); //模拟 假装写数据 ,这里写真正写入数据的逻辑 }};} }
6 . 配置好基本的Job之后，为Access表导入一些基本的数据(git上面有demo数据，access.sql)，写一个SpringBoot的启动类进行测试。
注意 : Job中的各个组件请使用@Bean注解声明，这样在元数据中才会有相应的正常操作记录 :
package name.ealen;import org.springframework.boot.SpringApplication; import org.springframework.boot.autoconfigure.SpringBootApplication;/*** Created by EalenXie on 2018/9/10 14:41.*/ @SpringBootApplication public class SpringBatchApplication {public static void main(String[] args) {SpringApplication.run(SpringBatchApplication.class, args);} }
7 . 运行可以看到基本数据处理效果，这里是模拟处理，和模拟写入 :
8 . 从元数据等表中查看验证JOB的执行情况 :
这里提一下，之前写过一篇SpringBoot+Quartz的整合， 大家应该想到些什么了吧。SpringBatch像是一个天然的Job，Quartz是完全可以做为它运作的调度器。两者结合，效果很不错。
感谢各位提出意见和支持。
