This question might seem to be a duplicate of this but it is not
My requirement is to read data from db using JdbcPagingItemReader and process individual records for some additional processing and in writer create individual json files for each processed item with file name id_of_record_json_fie.txt
For example if reader reads 100 records then 100 JSON files has to be created
What is the best way to do this, Can we use spring batch for this ?
Update 1-:
As per @Mahmoud answer, tasklet can be used , I have also tried implementing custom itemwriter in a chunk oriented step , this also seems to work
@Override
public void write(final List<? extends Person> persons) throws Exception {
for (Person person: persons) {
objectMapper.writeValue(new File("D:/cp/dataTwo.json"), person);
}
}
Using a chunk-oriented tasklet won't work, because there will be a single item writer on which the resource is set upfront and will be fixed during the entire step. Using a composite item writer might work but you need to know how many distinct writers to create and configure upfront.
The most straightforward option I see is to use a tasklet, something like:
import java.util.Collections;
import java.util.HashMap;
import javax.sql.DataSource;
import org.springframework.batch.core.Job;
import org.springframework.batch.core.JobParameters;
import org.springframework.batch.core.StepContribution;
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.JobLauncher;
import org.springframework.batch.core.scope.context.ChunkContext;
import org.springframework.batch.core.step.tasklet.Tasklet;
import org.springframework.batch.item.ExecutionContext;
import org.springframework.batch.item.database.JdbcPagingItemReader;
import org.springframework.batch.item.database.Order;
import org.springframework.batch.item.database.builder.JdbcPagingItemReaderBuilder;
import org.springframework.batch.item.file.FlatFileItemWriter;
import org.springframework.batch.item.file.builder.FlatFileItemWriterBuilder;
import org.springframework.batch.repeat.RepeatStatus;
import org.springframework.context.ApplicationContext;
import org.springframework.context.annotation.AnnotationConfigApplicationContext;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.core.io.FileSystemResource;
import org.springframework.jdbc.core.JdbcTemplate;
import org.springframework.jdbc.datasource.embedded.EmbeddedDatabase;
import org.springframework.jdbc.datasource.embedded.EmbeddedDatabaseBuilder;
import org.springframework.jdbc.datasource.embedded.EmbeddedDatabaseType;
@Configuration
@EnableBatchProcessing
public class MyJob {
@Bean
public JdbcPagingItemReader<Person> itemReader() {
return new JdbcPagingItemReaderBuilder<Person>()
.name("personItemReader")
.dataSource(dataSource())
.beanRowMapper(Person.class)
.selectClause("select *")
.fromClause("from person")
.sortKeys(new HashMap<String, Order>() {{ put("id", Order.DESCENDING);}})
.build();
}
@Bean
public Job job(JobBuilderFactory jobs, StepBuilderFactory steps) {
return jobs.get("job")
.start(steps.get("step")
.tasklet(new MyTasklet(itemReader()))
.build())
.build();
}
private static class MyTasklet implements Tasklet {
private boolean readerInitialized;
private JdbcPagingItemReader<Person> itemReader;
public MyTasklet(JdbcPagingItemReader<Person> itemReader) {
this.itemReader = itemReader;
}
@Override
public RepeatStatus execute(StepContribution contribution, ChunkContext chunkContext) throws Exception {
ExecutionContext executionContext = chunkContext.getStepContext().getStepExecution().getExecutionContext();
if (!readerInitialized) {
itemReader.open(executionContext);
readerInitialized = true;
}
Person person = itemReader.read();
if (person == null) {
itemReader.close();
return RepeatStatus.FINISHED;
}
// process the item
process(person);
// write the item in its own file (dynamically generated at runtime)
write(person, executionContext);
// save current state in execution context: in case of restart after failure, the job would resume where it left off.
itemReader.update(executionContext);
return RepeatStatus.CONTINUABLE;
}
private void process(Person person) {
// do something with the item
}
private void write(Person person, ExecutionContext executionContext) throws Exception {
FlatFileItemWriter<Person> itemWriter = new FlatFileItemWriterBuilder<Person>()
.resource(new FileSystemResource("person" + person.getId() + ".csv"))
.name("personItemWriter")
.delimited()
.names("id", "name")
.build();
itemWriter.open(executionContext);
itemWriter.write(Collections.singletonList(person));
itemWriter.close();
}
}
public static void main(String[] args) throws Exception {
ApplicationContext context = new AnnotationConfigApplicationContext(MyJob.class);
JobLauncher jobLauncher = context.getBean(JobLauncher.class);
Job job = context.getBean(Job.class);
jobLauncher.run(job, new JobParameters());
}
@Bean
public DataSource dataSource() {
EmbeddedDatabase embeddedDatabase = new EmbeddedDatabaseBuilder()
.setType(EmbeddedDatabaseType.H2)
.addScript("/org/springframework/batch/core/schema-drop-h2.sql")
.addScript("/org/springframework/batch/core/schema-h2.sql")
.build();
JdbcTemplate jdbcTemplate = new JdbcTemplate(embeddedDatabase);
jdbcTemplate.execute("create table person (id int primary key, name varchar(20));");
for (int i = 1; i <= 10; i++) {
jdbcTemplate.execute(String.format("insert into person values (%s, 'foo%s');", i, i));
}
return embeddedDatabase;
}
static class Person {
private int id;
private String name;
public Person() {
}
public int getId() {
return id;
}
public void setId(int id) {
this.id = id;
}
public String getName() {
return name;
}
public void setName(String name) {
this.name = name;
}
public String toString() {
return "Person{id=" + id + ", name='" + name + '\'' + '}';
}
}
}
This example reads 10 persons from a db table and generates 10 csv files (person1.csv
, person2.csv
, etc)
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With