Reputation: 437
I have a reader who knows how to read a CSV file with 14 columns, i would like it to be able to receive a file with many columns (~500) and read only these 14 columns, i know that the solution should include FieldSetMapper (according to this question: read only selective columns from csv file using spring batch )but i couldn't find a proper example for it. here is my current reader:
@Bean
public FlatFileItemReader<RowInput> csvRowsReader() {
FlatFileItemReader<RowInput> reader = new FlatFileItemReader<>();
Resource resource = new FileSystemResource(new File(FileManager.getInstance().getInputFileLocation()));
reader.setResource(resource);
reader.setLinesToSkip(1);
reader.setLineMapper(new DefaultLineMapper<RowInput>(){{
setLineTokenizer(new DelimitedLineTokenizer(){{
setNames(new String[]{"Field_1", "Field_2", "Field_3", "Field_4", "Field_5",
"Field_6", "Field_7", "Field_8", "Field_9", "Field_10", "Field_11",
"Field_12", "Field_13", "Field_14"});
}});
setFieldSetMapper(new BeanWrapperFieldSetMapper<RowInput>(){{
setTargetType(RowInput.class);
}});
}});
reader.setLinesToSkip(1);
return reader;
}
And the exception is:
Caused by: org.springframework.batch.item.file.transform.IncorrectTokenCountException: Incorrect number of tokens found in record: expected 14 actual 544
FieldSetMapper that i tried to use:
public class InputFieldSetMapper implements FieldSetMapper<RowInput>{
public RowInput mapFieldSet(FieldSet fs) {
if (fs == null) {
return null;
}
RowInput input = new RowInput();
input.setField1(fs.readString("Field_1"));
input.setField2(fs.readString("Field_2"));
// and so on...
return input;
}
}
Upvotes: 2
Views: 4202
Reputation: 31600
You need to set the includedFields
property on the LineTokenizer
to specify which fields to include when parsing the input file. In your case, it should be something like:
@Bean
public FlatFileItemReader<RowInput> csvRowsReader() {
FlatFileItemReader<RowInput> reader = new FlatFileItemReader<>();
Resource resource = new FileSystemResource(new File(FileManager.getInstance().getInputFileLocation()));
reader.setResource(resource);
reader.setLinesToSkip(1);
reader.setLineMapper(new DefaultLineMapper<RowInput>(){{
setLineTokenizer(new DelimitedLineTokenizer(){{
setNames(new String[]{"Field_1", "Field_2", "Field_3", "Field_4", "Field_5",
"Field_6", "Field_7", "Field_8", "Field_9", "Field_10", "Field_11",
"Field_12", "Field_13", "Field_14"});
setIncludedFields(0, 1, 2, 3, 4, 5, 6, 7, 8, 9,10 ,11 ,12 ,13);
}});
setFieldSetMapper(new BeanWrapperFieldSetMapper<RowInput>(){{
setTargetType(RowInput.class);
}});
}});
return reader;
}
EDIT: add an example with non sequential fields
import org.springframework.batch.core.Job;
import org.springframework.batch.core.JobParameters;
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.JobLauncher;
import org.springframework.batch.item.ItemWriter;
import org.springframework.batch.item.file.FlatFileItemReader;
import org.springframework.batch.item.file.builder.FlatFileItemReaderBuilder;
import org.springframework.beans.factory.annotation.Autowired;
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.ClassPathResource;
@Configuration
@EnableBatchProcessing
public class MyJob {
@Autowired
private JobBuilderFactory jobs;
@Autowired
private StepBuilderFactory steps;
@Bean
public FlatFileItemReader<Person> itemReader() {
return new FlatFileItemReaderBuilder<Person>()
.name("personItemReader")
.resource(new ClassPathResource("persons.csv"))
.delimited()
.includedFields(new Integer[] {0, 2})
.names(new String[] {"id", "lastName"})
.targetType(Person.class)
.build();
}
@Bean
public ItemWriter<Person> itemWriter() {
return items -> {
for (Person item : items) {
System.out.println("person = " + item);
}
};
}
@Bean
public Step step() {
return steps.get("step")
.<Person, Person>chunk(1)
.reader(itemReader())
.writer(itemWriter())
.build();
}
@Bean
public Job job() {
return jobs.get("job")
.start(step())
.build();
}
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());
}
public static class Person {
String id;
String firstName;
String lastName;
int age;
public Person() {
}
public String getId() {
return id;
}
public void setId(String id) {
this.id = id;
}
public String getFirstName() {
return firstName;
}
public void setFirstName(String firstName) {
this.firstName = firstName;
}
public String getLastName() {
return lastName;
}
public void setLastName(String lastName) {
this.lastName = lastName;
}
public int getAge() {
return age;
}
public void setAge(int age) {
this.age = age;
}
@Override
public String toString() {
return "Person{" +
"id='" + id + '\'' +
", firstName='" + firstName + '\'' +
", lastName='" + lastName + '\'' +
", age=" + age +
'}';
}
}
}
The input file persons.csv
is the following:
1,foo1,bar1,10
2,foo2,bar2,20
The example shows how to map only the id
and lastName
fields.
Hope this helps.
Upvotes: 5