Reading file is working good but writing file is not.
I would like to read multiple files then use MultiResourceItemWriter to write it separately, like:
Read Files:
source/abc.csv
source/cbd.csv
source/efg.csv
Should write files separate like:
target/abc.csv
target/cbd.csv
target/efg.csv
But currently it's putting all data in one file.
#Bean
public MultiResourceItemWriter<FooCsv> multipleCsvWriter(#Value("${directory.destination}") Resource folder) throws Exception {
MultiResourceItemWriter<FooCsv> writer = new MultiResourceItemWriter<>();
writer.setResource(folder);
writer.setDelegate(csvWriter(file));
return writer;
}
Note this is like copy and paste from source folder to target folder.
There are two ways to this-
Write custom reader by extending multiresourceitemreader, then in read() method you can get your current source file name. Then set this file to your csvFoo and pass this source file name dynamically to you are writer.
Write one extra step and taskley which will list all your available source files then add them to jobparameter and pass both source and dest file name dynamically to next step and call this step in cycle until all list files are not proceed.
You can use MultiResourcePartitioner to achieve the same. Here is sample Batch Config
#Configuration
#EnableBatchProcessing
public class BatchConfig {
#Autowired
private ResourcePatternResolver resourcePatternResolver;
#Autowired
private JobBuilderFactory jobBuilderFactory;
#Autowired
private StepBuilderFactory stepBuilderFactory;
#Autowired
public DataSource dataSource;
#Autowired
ApplicationContext context;
#Bean
#JobScope
public MultiResourcePartitioner paritioner(#Value("#{jobParameters[srcDir]}") String src) throws IOException {
Resource[] resources = resourcePatternResolver.getResources(src);
MultiResourcePartitioner partitioner = new MultiResourcePartitioner();
partitioner.partition(1);
partitioner.setResources(resources);
return partitioner;
}
#Bean
#StepScope
public FlatFileItemReader<String> reader(#Value("#{stepExecutionContext[fileName]}") Resource file) {
FlatFileItemReader<String> reader = new FlatFileItemReader<String>();
reader.setResource(file);
reader.setLineMapper(new PassThroughLineMapper());
return reader;
}
#Bean
#StepScope
public FlatFileItemWriter<String> writer(#Value("#{jobParameters[destDir]}") String dest,
#Value("#{stepExecutionContext[fileName]}") Resource file) {
String destFile = dest + file.getFilename();
System.out.println(destFile);
FlatFileItemWriter<String> writer = new FlatFileItemWriter<String>();
writer.setLineAggregator(new PassThroughLineAggregator<>());
writer.setResource(resourcePatternResolver.getResource(destFile));
return writer;
}
#Bean
public Job kpJob() {
return jobBuilderFactory.get("kpJob").incrementer(new RunIdIncrementer()).flow(step1()).end().build();
}
#Bean
public Step step1() {
Partitioner partitioner = context.getBean(MultiResourcePartitioner.class);
return stepBuilderFactory.get("step1").partitioner(slaveStep()).partitioner("step1.slave", partitioner).build();
}
#Bean
public Step slaveStep() {
ItemReader<String> reader = context.getBean(FlatFileItemReader.class);
ItemWriter<String> writer = context.getBean(FlatFileItemWriter.class);
return stepBuilderFactory.get("step1.slave").<String, String>chunk(10).reader(reader).writer(writer).build();
}
}
And pass srcDir and dstDir as job parameter.
simple solution to your problem - why not just create Steps for each of the source file. Given that and based in your scenario, file source and target is one to one. MultiResourceItemWriter is just a way to create new output file once it reaches the limit you set setItemCountLimitPerResource(int) (that i dont find in your example). You can even run the steps in parallel if you have any issue with performance, if there are no dependencies or sequence.
Related
I want to read a large file using spring batch. I want to split into multiple files and process each of them in a different thread using partitions. I am using the below code:
#Bean
#StepScope
public MultiResourcePartitioner partitioner() {
MultiResourcePartitioner partitioner = new MultiResourcePartitioner();
partitioner.setKeyName("file");
partitioner.setResources(splitFiles());
return partitioner;
}
private Resource[] splitFiles() {
// Read the large File available in the specified folder
// split the file to smaller files and return them as resource list
}
#Bean
public TaskExecutorPartitionHandler partitionHandler() {
TaskExecutorPartitionHandler partitionHandler = new TaskExecutorPartitionHandler();
partitionHandler.setStep(step1());
partitionHandler.setTaskExecutor(new SimpleAsyncTaskExecutor());
return partitionHandler;
}
#Bean
public Step partitionedMaster() {
return this.stepBuilderFactory.get("step1")
.partitioner(step1().getName(), partitioner(null))
.partitionHandler(partitionHandler())
.build();
}
#Bean
public Job partitionedJob() {
return this.jobBuilderFactory.get("partitionedJob")
.start(partitionedMaster())
.build();
}
#Bean
#StepScope
public FlatFileItemReader<Transaction> fileTransactionReader(#Value("#{stepExecutionContext['file']}") Resource resource) {
return new FlatFileItemReaderBuilder<Transaction>()
.name("flatFileTransactionReader")
.resource(resource)
.fieldSetMapper(fsm)
.build();
}
My issue is that the partitioner is partitioning the files which are only available in the folder at the start of the application. Once the application is up and running, if a new file is available in the same folder, the job couldn't read them/partition them.
I used #StepScope, still i'm having the issue.
How do I read and partition the files dynamically at runtime?
Editing it after the first answer:
Hi, Thanks for the inputs.
I can modify the code as below to send the files as parameters and invoke the job, but still the control is not going inside partitioner method, hence could not leverage partitioning.
Any inputs on this?
public JobParameters getJobParameters() {
Resource[] resources = //getFileToProcessResource
return new JobParametersBuilder()
.addLong(TIME, System.currentTimeMillis())
.addString("inputFiles", resources)
.toJobParameters();
}
JobParameters jobParameters = getJobParameters();
jobLauncher.run(partitionedJob(), jobParameters);
#Bean
#StepScope
public MultiResourcePartitioner partitioner(#Value("#{jobParameters['inputFiles']}") Resource[] resources) {
MultiResourcePartitioner partitioner = new MultiResourcePartitioner();
partitioner.setKeyName("file");
partitioner.setResources(resources);
return partitioner;
}
Once the application is up and running, if a new file is available in the same folder, the job couldn't read them/partition them
Batch processing is about fixed data sets. In your case, you start a job but its input data changes in the meantime, so that's not going to work as you expect. A fixed data set is required for restartability in order to work on the same data set in case of failure.
Since the input of your job is a file, you can use the file as a job parameter and configure a watch service (or similar mechanism) to launch a new job instance for each new file in the folder.
EDIT: Add example to make the partitioner aware of the job parameter
#Bean
#StepScope
public MultiResourcePartitioner partitioner(#Value("#{jobParameters['fileName']}") String fileName) {
MultiResourcePartitioner partitioner = new MultiResourcePartitioner();
partitioner.setKeyName("file");
partitioner.setResources(splitFiles(fileName));
return partitioner;
}
private Resource[] splitFiles(String fileName) {
// Read the large File available in the specified folder
// split the file to smaller files and return them as resource list
return null;
}
I am reading from Oracle and writing to a CSV file. I have one step which reads and writes to the CSV file. I implemented a ChunkListener so I know how many records were written.
I want to be able to write a file trailer showing the number of records written to my file. I implemented FlatFileFooterCallback but cannot figure out how to get the data from StepExecution (the "readCount") to my FlatFileFooterCallback.
I guess I am struggling with how to get access to Job, Step scopes in my write.
Any examples, or links would be helpful. I am using [Spring Batch / Boot] so I am all annotated. I can find xml examples, so maybe this annotated stuff is more complicated.
ItemWriter<Object> databaseCsvItemWriter() {
FlatFileItemWriter<Object> csvFileWriter = new FlatFileItemWriter<>();
String exportFileHeader = "one,two,three";
StringHeaderWriter headerWriter = new StringHeaderWriter(exportFileHeader);
csvFileWriter.setHeaderCallback(headerWriter);
String exportFilePath = "/tmp/students.csv";
csvFileWriter.setResource(new FileSystemResource(exportFilePath));
LineAggregator<McsendRequest> lineAggregator = createRequestLineAggregator();
csvFileWriter.setLineAggregator(lineAggregator);
csvFileWriter.setFooterCallback(headerWriter);
return csvFileWriter;
}
You can implement CustomFooterCallback as follows:
public class CustomFooterCallback implements FlatFileFooterCallback {
#Value("#{StepExecution}")
private StepExecution stepExecution;
#Override
public void writeFooter(Writer writer) throws IOException {
writer.write("footer - number of items read: " + stepExecution.getReadCount());
writer.write("footer - number of items written: " + stepExecution.getWriteCount());
}
}
Then in a #Configuration class:
#Bean
#StepScope
public FlatFileFooterCallback customFooterCallback() {
return new CustomFooterCallback();
}
And use in the Writer:
csvFileWriter.setFooterCallback(customFooterCallback());
This way, you have access to StepExecution in order to read data as needed.
I have a spring batch job which reads from a db then outputs to a multiple csv's. Inside my db I have a special column named divisionId. A CSV file should exist for every distinct value of divisionId. I split out the data using a ClassifierCompositeItemWriter.
At the moment I have an ItemWriter bean defined for every distinct value of divisionId. The beans are the same, it's only the file name that is different.
How can I change the configuration below to create a file with the divisionId automatically pre-pended to the file name without having to register a new ItemWriter for each divisionId?
I've been playing around with #JobScope and #StepScope annotations but can't get it right.
Thanks in advance.
#Bean
public Step readStgDbAndExportMasterListStep() {
return commonJobConfig.stepBuilderFactory
.get("readStgDbAndExportMasterListStep")
.<MasterList,MasterList>chunk(commonJobConfig.chunkSize)
.reader(commonJobConfig.queryStagingDbReader())
.processor(masterListOutputProcessor())
.writer(masterListFileWriter())
.stream((ItemStream) divisionMasterListFileWriter45())
.stream((ItemStream) divisionMasterListFileWriter90())
.build();
}
#Bean
public ItemWriter<MasterList> masterListFileWriter() {
BackToBackPatternClassifier classifier = new BackToBackPatternClassifier();
classifier.setRouterDelegate(new DivisionClassifier());
classifier.setMatcherMap(new HashMap<String, ItemWriter<? extends MasterList>>() {{
put("45", divisionMasterListFileWriter45());
put("90", divisionMasterListFileWriter90());
}});
ClassifierCompositeItemWriter<MasterList> writer = new ClassifierCompositeItemWriter<MasterList>();
writer.setClassifier(classifier);
return writer;
}
#Bean
public ItemWriter<MasterList> divisionMasterListFileWriter45() {
FlatFileItemWriter<MasterList> writer = new FlatFileItemWriter<>();
writer.setResource(new FileSystemResource(new File(commonJobConfig.outDir, "45_masterList" + "" + ".csv")));
writer.setHeaderCallback(masterListFlatFileHeaderCallback());
writer.setLineAggregator(masterListFormatterLineAggregator());
return writer;
}
#Bean
public ItemWriter<MasterList> divisionMasterListFileWriter90() {
FlatFileItemWriter<MasterList> writer = new FlatFileItemWriter<>();
writer.setResource(new FileSystemResource(new File(commonJobConfig.outDir, "90_masterList" + "" + ".csv")));
writer.setHeaderCallback(masterListFlatFileHeaderCallback());
writer.setLineAggregator(masterListFormatterLineAggregator());
return writer;
}
I came up with a pretty complex way of doing this. I followed a tutorial at https://github.com/langmi/spring-batch-examples/wiki/Rename-Files.
The premise is to use the step execution context to place the file name in it.
I am writing a spring batch job. I am implementing custom writer using KafkaClientWriter extends AbstractItemStreamItemWriter<ProducerMessage>
I have fields which need to be unique for each instance. But I could see this class initiated only once. Rest jobs have same instance of writer class.
Where as my custom readers and processors are getting initiated for each job.
Below is my job configurations. How can I achieve the same behavior for writer as well?
#Bean
#Scope("job")
public ZipMultiResourceItemReader reader(#Value("#{jobParameters[fileName]}") String fileName, #Value("#{jobParameters[s3SourceFolderPrefix]}") String s3SourceFolderPrefix, #Value("#{jobParameters[timeStamp]}") long timeStamp, com.fastretailing.catalogPlatformSCMProducer.service.ConfigurationService confService) {
FlatFileItemReader faltFileReader = new FlatFileItemReader();
ZipMultiResourceItemReader zipReader = new ZipMultiResourceItemReader();
Resource[] resArray = new Resource[1];
resArray[0] = new FileSystemResource(new File(fileName));
zipReader.setArchives(resArray);
DefaultLineMapper<ProducerMessage> lineMapper = new DefaultLineMapper<ProducerMessage>();
lineMapper.setLineTokenizer(new DelimitedLineTokenizer());
CSVFieldMapper csvFieldMapper = new CSVFieldMapper(fileName, s3SourceFolderPrefix, timeStamp, confService);
lineMapper.setFieldSetMapper(csvFieldMapper);
faltFileReader.setLineMapper(lineMapper);
zipReader.setDelegate(faltFileReader);
return zipReader;
}
#Bean
#Scope("job")
public ItemProcessor<ProducerMessage, ProducerMessage> processor(#Value("#{jobParameters[timeStamp]}") long timeStamp) {
ProducerProcessor processor = new ProducerProcessor();
processor.setS3FileTimeStamp(timeStamp);
return processor;
}
#Bean
#ConfigurationProperties
public ItemWriter<ProducerMessage> writer() {
return new KafkaClientWriter();
}
#Bean
public Step step1(StepBuilderFactory stepBuilderFactory,
ItemReader reader, ItemWriter writer,
ItemProcessor processor, #Value("${reader.chunkSize}")
int chunkSize) {
LOGGER.info("Step configuration loaded with chunk size {}", chunkSize);
return stepBuilderFactory.get("step1")
.chunk(chunkSize).reader(reader)
.processor(processor).writer(writer)
.build();
}
#Bean
public StepScope stepScope() {
final StepScope stepScope = new StepScope();
stepScope.setAutoProxy(true);
return stepScope;
}
#Bean
public JobScope jobScope() {
final JobScope jobScope = new JobScope();
return jobScope;
}
#Bean
public Configuration configuration() {
return new Configuration();
}
I tried making the writer with job scope. But in that case open is not getting called. This is where I am doing some initializations.
When using java based configuration and a scoped proxy what happens is that the return type of the method is detected and for that a proxy is created. So when you return ItemWriter you will get a JDK proxy only implementing ItemWriter, whereas your open method is on the ItemStream interface. Because that interface isn't included on the proxy there is no way to call the method.
Either change the return type to KafkaClientWriter or ItemStreamWriter< ProducerMessage> (assuming the KafkaCLientWriter implements that method). Next add #Scope("job") and you should have your open method called again with a properly scoped writer.
Background
I am working on designing a file reading layer that can read delimited files and load it in a List. I have decided to use Spring Batch because it provides a lot of scalability options which I can leverage for different sets of files depending on their size.
The requirement
I want to design a generic Job API that can be used to read any delimited file.
There should be a single Job structure that should be used for parsing every delimited file. For example, if the system needs to read 5 files, there will be 5 jobs (one for each file). The only way the 5 jobs will be different from each other is that they will use a different FieldSetMapper, column name, directory path and additional scaling parameters such as commit-interval and throttle-limit.
The user of this API should not need to configure a Spring
batch job, step, chunking, partitioning, etc on his own when a new file type is introduced in the system.
All that the user needs to do is to provide the FieldsetMapperto be used by the job along with the commit-interval, throttle-limit and the directory where each type of file will be placed.
There will be one predefined directory per file. Each directory can contain multiple files of the same type and format. A MultiResourcePartioner will be used to look inside a directory. The number of partitions = number of files in the directory.
My requirement is to build a Spring Batch infrastructure that gives me a unique job I can launch once I have the bits and pieces that will make up the job.
My solution :
I created an abstract configuration class that will be extended by concrete configuration classes (There will be 1 concrete class per file to be read).
#Configuration
#EnableBatchProcessing
public abstract class AbstractFileLoader<T> {
private static final String FILE_PATTERN = "*.dat";
#Autowired
JobBuilderFactory jobs;
#Autowired
ResourcePatternResolver resourcePatternResolver;
public final Job createJob(Step s1, JobExecutionListener listener) {
return jobs.get(this.getClass().getSimpleName())
.incrementer(new RunIdIncrementer()).listener(listener)
.start(s1).build();
}
public abstract Job loaderJob(Step s1, JobExecutionListener listener);
public abstract FieldSetMapper<T> getFieldSetMapper();
public abstract String getFilesPath();
public abstract String[] getColumnNames();
public abstract int getChunkSize();
public abstract int getThrottleLimit();
#Bean
#StepScope
#Value("#{stepExecutionContext['fileName']}")
public FlatFileItemReader<T> reader(String file) {
FlatFileItemReader<T> reader = new FlatFileItemReader<T>();
String path = file.substring(file.indexOf(":") + 1, file.length());
FileSystemResource resource = new FileSystemResource(path);
reader.setResource(resource);
DefaultLineMapper<T> lineMapper = new DefaultLineMapper<T>();
lineMapper.setFieldSetMapper(getFieldSetMapper());
DelimitedLineTokenizer tokenizer = new DelimitedLineTokenizer(",");
tokenizer.setNames(getColumnNames());
lineMapper.setLineTokenizer(tokenizer);
reader.setLineMapper(lineMapper);
reader.setLinesToSkip(1);
return reader;
}
#Bean
public ItemProcessor<T, T> processor() {
// TODO add transformations here
return null;
}
#Bean
#JobScope
public ListItemWriter<T> writer() {
ListItemWriter<T> writer = new ListItemWriter<T>();
return writer;
}
#Bean
#JobScope
public Step readStep(StepBuilderFactory stepBuilderFactory,
ItemReader<T> reader, ItemWriter<T> writer,
ItemProcessor<T, T> processor, TaskExecutor taskExecutor) {
final Step readerStep = stepBuilderFactory
.get(this.getClass().getSimpleName() + " ReadStep:slave")
.<T, T> chunk(getChunkSize()).reader(reader)
.processor(processor).writer(writer).taskExecutor(taskExecutor)
.throttleLimit(getThrottleLimit()).build();
final Step partitionedStep = stepBuilderFactory
.get(this.getClass().getSimpleName() + " ReadStep:master")
.partitioner(readerStep)
.partitioner(
this.getClass().getSimpleName() + " ReadStep:slave",
partitioner()).taskExecutor(taskExecutor).build();
return partitionedStep;
}
/*
* #Bean public TaskExecutor taskExecutor() { return new
* SimpleAsyncTaskExecutor(); }
*/
#Bean
#JobScope
public Partitioner partitioner() {
MultiResourcePartitioner partitioner = new MultiResourcePartitioner();
Resource[] resources;
try {
resources = resourcePatternResolver.getResources("file:"
+ getFilesPath() + FILE_PATTERN);
} catch (IOException e) {
throw new RuntimeException(
"I/O problems when resolving the input file pattern.", e);
}
partitioner.setResources(resources);
return partitioner;
}
#Bean
#JobScope
public JobExecutionListener listener(ListItemWriter<T> writer) {
return new JobCompletionNotificationListener<T>(writer);
}
/*
* Use this if you want the writer to have job scope (JIRA BATCH-2269). Also
* change the return type of writer to ListItemWriter for this to work.
*/
#Bean
public TaskExecutor taskExecutor() {
return new SimpleAsyncTaskExecutor() {
#Override
protected void doExecute(final Runnable task) {
// gets the jobExecution of the configuration thread
final JobExecution jobExecution = JobSynchronizationManager
.getContext().getJobExecution();
super.doExecute(new Runnable() {
public void run() {
JobSynchronizationManager.register(jobExecution);
try {
task.run();
} finally {
JobSynchronizationManager.close();
}
}
});
}
};
}
}
Let's say I have to read Invoice data for the sake of discussion. I can therefore extend the above class for creating an InvoiceLoader :
#Configuration
public class InvoiceLoader extends AbstractFileLoader<Invoice>{
private class InvoiceFieldSetMapper implements FieldSetMapper<Invoice> {
public Invoice mapFieldSet(FieldSet f) {
Invoice invoice = new Invoice();
invoice.setNo(f.readString("INVOICE_NO");
return e;
}
}
#Override
public FieldSetMapper<Invoice> getFieldSetMapper() {
return new InvoiceFieldSetMapper();
}
#Override
public String getFilesPath() {
return "I:/CK/invoices/partitions/";
}
#Override
public String[] getColumnNames() {
return new String[] { "INVOICE_NO", "DATE"};
}
#Override
#Bean(name="invoiceJob")
public Job loaderJob(Step s1,
JobExecutionListener listener) {
return createJob(s1, listener);
}
#Override
public int getChunkSize() {
return 25254;
}
#Override
public int getThrottleLimit() {
return 8;
}
}
Let's say I have one more class called Inventory that extends AbstractFileLoader.
On application startup, I can load these two annotation configurations as follows :
AbstractApplicationContext context1 = new AnnotationConfigApplicationContext(InvoiceLoader.class, InventoryLoader.class);
Somewhere else in my application two different threads can launch the jobs as follows :
Thread 1 :
JobLauncher jobLauncher1 = context1.getBean(JobLauncher.class);
Job job1 = context1.getBean("invoiceJob", Job.class);
JobExecution jobExecution = jobLauncher1.run(job1, jobParams1);
Thread 2 :
JobLauncher jobLauncher1 = context1.getBean(JobLauncher.class);
Job job1 = context1.getBean("inventoryJob", Job.class);
JobExecution jobExecution = jobLauncher1.run(job1, jobParams1);
The advantage of this approach is that everytime there is a new file to be read, all that the developer/user has to do is subclass AbstractFileLoader and implement the required abstract methods without the need to get into the details of how to assemble the job.
The questions :
I am new to Spring batch so I may have overlooked some of the not-so-obvious issues with this approach such as shared internal objects in Spring batch that may cause two jobs running together to fail or obvious issues such as scoping of the beans.
Is there a better way to achieve my objective?
The fileName attribute of the #Value("#{stepExecutionContext['fileName']}") is always being assigned the value as I:/CK/invoices/partitions/ which is the value returned by getPathmethod in InvoiceLoader even though the getPathmethod inInventoryLoader`returns a different value.
One option is passing them as job parameters. For instance:
#Bean
Job job() {
jobs.get("myJob").start(step1(null)).build()
}
#Bean
#JobScope
Step step1(#Value('#{jobParameters["commitInterval"]}') commitInterval) {
steps.get('step1')
.chunk((int) commitInterval)
.reader(new IterableItemReader(iterable: [1, 2, 3, 4], name: 'foo'))
.writer(writer(null))
.build()
}
#Bean
#JobScope
ItemWriter writer(#Value('#{jobParameters["writerClass"]}') writerClass) {
applicationContext.classLoader.loadClass(writerClass).newInstance()
}
With MyWriter:
class MyWriter implements ItemWriter<Integer> {
#Override
void write(List<? extends Integer> items) throws Exception {
println "Write $items"
}
}
Then executed with:
def jobExecution = launcher.run(ctx.getBean(Job), new JobParameters([
commitInterval: new JobParameter(3),
writerClass: new JobParameter('MyWriter'), ]))
Output is:
INFO: Executing step: [step1]
Write [1, 2, 3]
Write [4]
Feb 24, 2016 2:30:22 PM org.springframework.batch.core.launch.support.SimpleJobLauncher$1 run
INFO: Job: [SimpleJob: [name=myJob]] completed with the following parameters: [{commitInterval=3, writerClass=MyWriter}] and the following status: [COMPLETED]
Status is: COMPLETED, job execution id 0
#1 step1 COMPLETED
Full example here.