Spring Batch 5 Interview: Partitioning, Chunks und Fehlertoleranz

// Spring Batch 5 Job-Konfiguration mit Java 21
@Configuration
public class BatchJobConfig {

    // JobRepository speichert die Ausführungs-Metadaten
    // Ermöglicht Restart und Job-Monitoring
    private final JobRepository jobRepository;
    private final PlatformTransactionManager transactionManager;

    public BatchJobConfig(JobRepository jobRepository,
                          PlatformTransactionManager transactionManager) {
        this.jobRepository = jobRepository;
        this.transactionManager = transactionManager;
    }

    // Ein Job kapselt den vollständigen Batch-Prozess
    // Besteht aus einem oder mehreren sequentiell ausgeführten Steps
    @Bean
    public Job importUserJob(Step processUsersStep, Step cleanupStep) {
        return new JobBuilder("importUserJob", jobRepository)
                .start(processUsersStep)      // Haupt-Verarbeitungs-Step
                .next(cleanupStep)             // Aufräum-Step
                .build();
    }

    // Ein Step repräsentiert eine unabhängige Arbeitseinheit
    // Zwei Modelle: Tasklet (einzelne Aufgabe) oder Chunk (iterative Verarbeitung)
    @Bean
    public Step processUsersStep(ItemReader<UserRecord> reader,
                                  ItemProcessor<UserRecord, User> processor,
                                  ItemWriter<User> writer) {
        return new StepBuilder("processUsersStep", jobRepository)
                .<UserRecord, User>chunk(100, transactionManager)  // Commit alle 100 Items
                .reader(reader)       // Liest Quelldaten
                .processor(processor) // Transformiert jedes Item
                .writer(writer)       // Schreibt in 100er-Batches
                .build();
    }
}

// Tasklet: einzelne Aktion ohne Iteration
@Component
public class CleanupTasklet implements Tasklet {

    private final Path tempDirectory = Path.of("/tmp/batch-work");

    @Override
    public RepeatStatus execute(StepContribution contribution,
                                 ChunkContext chunkContext) throws Exception {
        // Löscht alle temporären Dateien der Verarbeitung
        try (var files = Files.walk(tempDirectory)) {
            files.filter(Files::isRegularFile)
                 .forEach(this::deleteQuietly);
        }

        // FINISHED zeigt an, dass das Tasklet seine Arbeit abgeschlossen hat
        // CONTINUABLE würde die Ausführung neu starten (nützlich für Polling)
        return RepeatStatus.FINISHED;
    }

    private void deleteQuietly(Path file) {
        try {
            Files.delete(file);
        } catch (IOException e) {
            // Loggen und fortfahren - Job nicht wegen einer Datei abbrechen
        }
    }
}

// Chunk-Verarbeitung: Hochvolumige Verarbeitung
@Configuration
public class ChunkProcessingConfig {

    @Bean
    public Step processOrdersStep(JobRepository jobRepository,
                                   PlatformTransactionManager transactionManager,
                                   ItemReader<OrderRecord> reader,
                                   ItemProcessor<OrderRecord, ProcessedOrder> processor,
                                   ItemWriter<ProcessedOrder> writer) {
        return new StepBuilder("processOrdersStep", jobRepository)
                // Chunk von 500: liest 500 Items, verarbeitet, schreibt, committet
                .<OrderRecord, ProcessedOrder>chunk(500, transactionManager)
                .reader(reader)
                .processor(processor)
                .writer(writer)
                // Listener zur Fortschrittsüberwachung
                .listener(new ChunkProgressListener())
                .build();
    }
}

// ItemReader: liest ein Item nach dem anderen
@StepScope
@Component
public class OrderItemReader implements ItemReader<OrderRecord> {

    // @StepScope: neue Instanz pro Step-Ausführung
    // Ermöglicht das Injizieren dynamischer Job-Parameter
    @Value("#{jobParameters['startDate']}")
    private LocalDate startDate;

    private Iterator<OrderRecord> orderIterator;

    @BeforeStep
    public void initializeReader(StepExecution stepExecution) {
        // Lädt Daten beim Start des Steps
        List<OrderRecord> orders = fetchOrdersFromDate(startDate);
        this.orderIterator = orders.iterator();
    }

    @Override
    public OrderRecord read() {
        // Gibt null zurück, um das Datenende zu signalisieren
        // Spring Batch ruft read() auf, bis null zurückkommt
        if (orderIterator.hasNext()) {
            return orderIterator.next();
        }
        return null;  // Ende des Datasets
    }

    private List<OrderRecord> fetchOrdersFromDate(LocalDate date) {
        // Holt Daten aus der Datenquelle
        return List.of();  // Tatsächliche Implementierung
    }
}

// ItemProcessor: transformiert jedes Item einzeln
@Component
public class OrderItemProcessor implements ItemProcessor<OrderRecord, ProcessedOrder> {

    private final PricingService pricingService;
    private final ValidationService validationService;

    public OrderItemProcessor(PricingService pricingService,
                               ValidationService validationService) {
        this.pricingService = pricingService;
        this.validationService = validationService;
    }

    @Override
    public ProcessedOrder process(OrderRecord item) {
        // null zurückgeben filtert das Item (wird nicht geschrieben)
        if (!validationService.isValid(item)) {
            return null;  // Item gefiltert
        }

        // Geschäftliche Transformation
        BigDecimal finalPrice = pricingService.calculatePrice(item);

        return new ProcessedOrder(
                item.orderId(),
                item.customerId(),
                finalPrice,
                LocalDateTime.now()
        );
    }
}

// ItemWriter: schreibt den vollständigen Chunk in einer Operation
@Component
public class OrderItemWriter implements ItemWriter<ProcessedOrder> {

    private final JdbcTemplate jdbcTemplate;

    public OrderItemWriter(JdbcTemplate jdbcTemplate) {
        this.jdbcTemplate = jdbcTemplate;
    }

    @Override
    public void write(Chunk<? extends ProcessedOrder> chunk) {
        // Der Chunk enthält alle verarbeiteten Items
        // Batch-Schreiben für optimierte Performance
        List<? extends ProcessedOrder> items = chunk.getItems();

        jdbcTemplate.batchUpdate(
                "INSERT INTO processed_orders (order_id, customer_id, final_price, processed_at) VALUES (?, ?, ?, ?)",
                items,
                items.size(),
                (ps, order) -> {
                    ps.setLong(1, order.orderId());
                    ps.setLong(2, order.customerId());
                    ps.setBigDecimal(3, order.finalPrice());
                    ps.setTimestamp(4, Timestamp.valueOf(order.processedAt()));
                }
        );
    }
}

// Dynamische Konfiguration der Chunk-Größe
@Configuration
public class ChunkSizingConfig {

    // Sinnvoller Standardwert für die meisten Fälle
    private static final int DEFAULT_CHUNK_SIZE = 100;

    // Für leichte Items (wenige Felder)
    private static final int LIGHT_ITEMS_CHUNK_SIZE = 500;

    // Für schwere Items (Blobs, Dokumente)
    private static final int HEAVY_ITEMS_CHUNK_SIZE = 25;

    @Bean
    public Step processLightDataStep(JobRepository jobRepository,
                                      PlatformTransactionManager txManager,
                                      ItemReader<LightRecord> reader,
                                      ItemWriter<LightRecord> writer) {
        return new StepBuilder("processLightDataStep", jobRepository)
                // Leichte Items: größere Chunks für weniger Commits
                .<LightRecord, LightRecord>chunk(LIGHT_ITEMS_CHUNK_SIZE, txManager)
                .reader(reader)
                .writer(writer)
                .build();
    }

    @Bean
    public Step processDocumentsStep(JobRepository jobRepository,
                                      PlatformTransactionManager txManager,
                                      ItemReader<Document> reader,
                                      ItemProcessor<Document, ProcessedDocument> processor,
                                      ItemWriter<ProcessedDocument> writer) {
        return new StepBuilder("processDocumentsStep", jobRepository)
                // Schwere Dokumente: kleinere Chunks zur Speicherbegrenzung
                .<Document, ProcessedDocument>chunk(HEAVY_ITEMS_CHUNK_SIZE, txManager)
                .reader(reader)
                .processor(processor)
                .writer(writer)
                .build();
    }
}

// Konfiguration eines partitionierten Jobs
@Configuration
public class PartitionedJobConfig {

    private final JobRepository jobRepository;
    private final PlatformTransactionManager transactionManager;

    public PartitionedJobConfig(JobRepository jobRepository,
                                 PlatformTransactionManager transactionManager) {
        this.jobRepository = jobRepository;
        this.transactionManager = transactionManager;
    }

    @Bean
    public Job partitionedImportJob(Step partitionedStep) {
        return new JobBuilder("partitionedImportJob", jobRepository)
                .start(partitionedStep)
                .build();
    }

    // Manager-Step: orchestriert die Partitionen
    @Bean
    public Step partitionedStep(Partitioner partitioner,
                                 Step workerStep,
                                 TaskExecutor taskExecutor) {
        return new StepBuilder("partitionedStep", jobRepository)
                // Teilt die Arbeit über den Partitioner
                .partitioner("workerStep", partitioner)
                // Step, der für jede Partition ausgeführt wird
                .step(workerStep)
                // 8 parallele Threads
                .taskExecutor(taskExecutor)
                // Anzahl zu erstellender Partitionen
                .gridSize(8)
                .build();
    }

    // TaskExecutor für parallele Ausführung
    @Bean
    public TaskExecutor batchTaskExecutor() {
        ThreadPoolTaskExecutor executor = new ThreadPoolTaskExecutor();
        executor.setCorePoolSize(8);
        executor.setMaxPoolSize(16);
        executor.setQueueCapacity(50);
        executor.setThreadNamePrefix("batch-partition-");
        executor.initialize();
        return executor;
    }
}

// Partitioner basierend auf ID-Bereichen
@Component
public class RangePartitioner implements Partitioner {

    private final JdbcTemplate jdbcTemplate;

    public RangePartitioner(JdbcTemplate jdbcTemplate) {
        this.jdbcTemplate = jdbcTemplate;
    }

    @Override
    public Map<String, ExecutionContext> partition(int gridSize) {
        // Ermittelt die Grenzen des Datasets
        Long minId = jdbcTemplate.queryForObject(
                "SELECT MIN(id) FROM orders WHERE status = 'PENDING'", Long.class);
        Long maxId = jdbcTemplate.queryForObject(
                "SELECT MAX(id) FROM orders WHERE status = 'PENDING'", Long.class);

        if (minId == null || maxId == null) {
            return Map.of();  // Keine Daten zu verarbeiten
        }

        // Berechnet die Größe jeder Partition
        long range = (maxId - minId) / gridSize + 1;
        Map<String, ExecutionContext> partitions = new HashMap<>();

        for (int i = 0; i < gridSize; i++) {
            ExecutionContext context = new ExecutionContext();
            long start = minId + (i * range);
            long end = Math.min(start + range - 1, maxId);

            // Jede Partition erhält ihre Grenzen
            context.putLong("minId", start);
            context.putLong("maxId", end);
            context.putInt("partitionNumber", i);

            partitions.put("partition" + i, context);
        }

        return partitions;
    }
}

// Remote-Partitioning-Konfiguration mit Messaging
@Configuration
public class RemotePartitioningConfig {

    @Bean
    public Step managerStep(JobRepository jobRepository,
                             Partitioner partitioner,
                             MessageChannelPartitionHandler partitionHandler) {
        return new StepBuilder("managerStep", jobRepository)
                .partitioner("workerStep", partitioner)
                // Handler kommuniziert mit Remote-Workern
                .partitionHandler(partitionHandler)
                .build();
    }

    // PartitionHandler sendet ExecutionContexts an Worker
    @Bean
    public MessageChannelPartitionHandler partitionHandler(
            MessagingTemplate messagingTemplate,
            JobExplorer jobExplorer) {
        MessageChannelPartitionHandler handler = new MessageChannelPartitionHandler();
        handler.setStepName("workerStep");
        handler.setGridSize(4);
        handler.setMessagingOperations(messagingTemplate);
        handler.setJobExplorer(jobExplorer);
        // Timeout für die Wartezeit auf Worker
        handler.setPollInterval(5000L);
        return handler;
    }
}

// Konfiguration auf Worker-Seite
@Configuration
public class WorkerConfiguration {

    private final JobRepository jobRepository;
    private final PlatformTransactionManager transactionManager;

    public WorkerConfiguration(JobRepository jobRepository,
                                PlatformTransactionManager transactionManager) {
        this.jobRepository = jobRepository;
        this.transactionManager = transactionManager;
    }

    // Worker empfängt Partitionen und führt den Step aus
    @Bean
    public Step workerStep(ItemReader<OrderRecord> reader,
                            ItemProcessor<OrderRecord, ProcessedOrder> processor,
                            ItemWriter<ProcessedOrder> writer) {
        return new StepBuilder("workerStep", jobRepository)
                .<OrderRecord, ProcessedOrder>chunk(100, transactionManager)
                // Reader mit @StepScope für Partition-Parameter
                .reader(reader)
                .processor(processor)
                .writer(writer)
                .build();
    }

    // Reader, der Partitionsgrenzen verwendet
    @Bean
    @StepScope
    public JdbcCursorItemReader<OrderRecord> partitionedReader(
            DataSource dataSource,
            @Value("#{stepExecutionContext['minId']}") Long minId,
            @Value("#{stepExecutionContext['maxId']}") Long maxId) {
        return new JdbcCursorItemReaderBuilder<OrderRecord>()
                .name("partitionedOrderReader")
                .dataSource(dataSource)
                .sql("SELECT * FROM orders WHERE id BETWEEN ? AND ? AND status = 'PENDING'")
                .preparedStatementSetter(ps -> {
                    ps.setLong(1, minId);
                    ps.setLong(2, maxId);
                })
                .rowMapper(new OrderRecordRowMapper())
                .build();
    }
}

// Vollständige Fehlertoleranz-Konfiguration
@Configuration
public class FaultTolerantStepConfig {

    @Bean
    public Step faultTolerantStep(JobRepository jobRepository,
                                   PlatformTransactionManager transactionManager,
                                   ItemReader<DataRecord> reader,
                                   ItemProcessor<DataRecord, ProcessedRecord> processor,
                                   ItemWriter<ProcessedRecord> writer,
                                   SkipPolicy customSkipPolicy) {
        return new StepBuilder("faultTolerantStep", jobRepository)
                .<DataRecord, ProcessedRecord>chunk(100, transactionManager)
                .reader(reader)
                .processor(processor)
                .writer(writer)
                // Aktiviert den fehlertoleranten Modus
                .faultTolerant()
                // SKIP: ignoriert bis zu 10 Validierungsfehler
                .skipLimit(10)
                .skip(ValidationException.class)
                .skip(DataIntegrityViolationException.class)
                // Manche Fehler dürfen nie übersprungen werden
                .noSkip(FatalBatchException.class)
                // RETRY: wiederholt vorübergehende Fehler
                .retryLimit(3)
                .retry(TransientDataAccessException.class)
                .retry(DeadlockLoserDataAccessException.class)
                // Exponentieller Backoff zwischen Retries
                .backOffPolicy(exponentialBackOffPolicy())
                // Listener zum Loggen der Skips
                .listener(skipListener())
                .build();
    }

    @Bean
    public BackOffPolicy exponentialBackOffPolicy() {
        ExponentialBackOffPolicy policy = new ExponentialBackOffPolicy();
        policy.setInitialInterval(1000);  // 1 Sekunde
        policy.setMultiplier(2.0);         // Verdoppelt sich pro Retry
        policy.setMaxInterval(10000);      // Maximal 10 Sekunden
        return policy;
    }

    @Bean
    public SkipListener<DataRecord, ProcessedRecord> skipListener() {
        return new SkipListener<>() {
            @Override
            public void onSkipInRead(Throwable t) {
                // Loggt unlesbares Item
            }

            @Override
            public void onSkipInProcess(DataRecord item, Throwable t) {
                // Loggt Item, das bei der Verarbeitung fehlschlug
            }

            @Override
            public void onSkipInWrite(ProcessedRecord item, Throwable t) {
                // Loggt Item, das beim Schreiben fehlschlug
            }
        };
    }
}

// SkipPolicy mit fortgeschrittener Geschäftslogik
@Component
public class AdaptiveSkipPolicy implements SkipPolicy {

    private static final int MAX_SKIP_COUNT = 100;
    private static final double MAX_SKIP_PERCENTAGE = 0.05;  // Max 5%

    private final AtomicInteger totalProcessed = new AtomicInteger(0);
    private final AtomicInteger skipCount = new AtomicInteger(0);

    @Override
    public boolean shouldSkip(Throwable exception, long skipCountSoFar) {
        // Fatale Fehler nie überspringen
        if (exception instanceof FatalBatchException
                || exception instanceof OutOfMemoryError) {
            return false;
        }

        // Absolutes Skip-Limit
        if (skipCountSoFar >= MAX_SKIP_COUNT) {
            return false;  // Job stoppen
        }

        // Prozentuales Limit
        int total = totalProcessed.get();
        if (total > 1000) {  // Erst nach Aufwärmphase anwenden
            double skipPercentage = (double) skipCountSoFar / total;
            if (skipPercentage > MAX_SKIP_PERCENTAGE) {
                return false;  // Anteilig zu viele Fehler
            }
        }

        // Validierungs- und Datenfehler überspringen
        return exception instanceof ValidationException
                || exception instanceof DataFormatException
                || exception instanceof IllegalArgumentException;
    }

    // Wird von einem Listener zur Fortschrittsverfolgung aufgerufen
    public void incrementProcessed() {
        totalProcessed.incrementAndGet();
    }
}

// Service zur Verwaltung von Job-Restarts
@Service
public class JobRestartService {

    private final JobLauncher jobLauncher;
    private final JobExplorer jobExplorer;
    private final JobRepository jobRepository;
    private final Job importJob;

    public JobRestartService(JobLauncher jobLauncher,
                              JobExplorer jobExplorer,
                              JobRepository jobRepository,
                              @Qualifier("importJob") Job importJob) {
        this.jobLauncher = jobLauncher;
        this.jobExplorer = jobExplorer;
        this.jobRepository = jobRepository;
        this.importJob = importJob;
    }

    public JobExecution restartFailedJob(Long jobExecutionId) throws Exception {
        // Holt die fehlgeschlagene Ausführung
        JobExecution failedExecution = jobExplorer.getJobExecution(jobExecutionId);

        if (failedExecution == null) {
            throw new IllegalArgumentException("Job execution not found: " + jobExecutionId);
        }

        // Prüft, ob der Job neu gestartet werden kann
        if (!failedExecution.getStatus().equals(BatchStatus.FAILED)) {
            throw new IllegalStateException("Only FAILED jobs can be restarted");
        }

        // Verwendet die gleichen Parameter wie die ursprüngliche Ausführung
        JobParameters originalParams = failedExecution.getJobParameters();

        // Startet den Job neu - nimmt automatisch vom letzten Checkpoint wieder auf
        return jobLauncher.run(importJob, originalParams);
    }

    public List<JobExecution> findRestartableJobs() {
        // Listet alle FAILED-Ausführungen, die noch nicht neu gestartet wurden
        return jobExplorer.findJobInstancesByJobName(importJob.getName(), 0, 100)
                .stream()
                .flatMap(instance -> jobExplorer.getJobExecutions(instance).stream())
                .filter(exec -> exec.getStatus() == BatchStatus.FAILED)
                .filter(this::isRestartable)
                .toList();
    }

    private boolean isRestartable(JobExecution execution) {
        // Prüft, dass keine neuere erfolgreiche Ausführung existiert
        JobInstance instance = execution.getJobInstance();
        return jobExplorer.getJobExecutions(instance).stream()
                .noneMatch(exec -> exec.getStatus() == BatchStatus.COMPLETED);
    }
}

// Multi-threaded Step: mehrere Threads verarbeiten denselben Datensatz
@Configuration
public class MultiThreadedStepConfig {

    @Bean
    public Step multiThreadedStep(JobRepository jobRepository,
                                   PlatformTransactionManager transactionManager,
                                   ItemReader<Record> reader,
                                   ItemProcessor<Record, ProcessedRecord> processor,
                                   ItemWriter<ProcessedRecord> writer,
                                   TaskExecutor taskExecutor) {
        return new StepBuilder("multiThreadedStep", jobRepository)
                .<Record, ProcessedRecord>chunk(100, transactionManager)
                // ACHTUNG: Reader muss thread-safe sein
                .reader(synchronizedReader(reader))
                .processor(processor)
                .writer(writer)
                // 4 Threads verarbeiten Chunks parallel
                .taskExecutor(taskExecutor)
                .throttleLimit(4)
                .build();
    }

    // Wrapper, um den Reader thread-safe zu machen
    private ItemReader<Record> synchronizedReader(ItemReader<Record> reader) {
        SynchronizedItemStreamReader<Record> syncReader = new SynchronizedItemStreamReader<>();
        syncReader.setDelegate((ItemStreamReader<Record>) reader);
        return syncReader;
    }
}

// Ausführung unabhängiger Steps parallel
@Configuration
public class ParallelStepsConfig {

    @Bean
    public Job parallelJob(JobRepository jobRepository,
                            Step loadCustomersStep,
                            Step loadProductsStep,
                            Step loadOrdersStep,
                            Step processDataStep) {
        // Paralleler Flow: Customers und Products gleichzeitig geladen
        Flow loadCustomersFlow = new FlowBuilder<Flow>("loadCustomersFlow")
                .start(loadCustomersStep)
                .build();

        Flow loadProductsFlow = new FlowBuilder<Flow>("loadProductsFlow")
                .start(loadProductsStep)
                .build();

        Flow loadOrdersFlow = new FlowBuilder<Flow>("loadOrdersFlow")
                .start(loadOrdersStep)
                .build();

        // Split führt die Flows parallel aus
        return new JobBuilder("parallelJob", jobRepository)
                .start(new FlowBuilder<Flow>("parallelLoadFlow")
                        .split(new SimpleAsyncTaskExecutor())
                        .add(loadCustomersFlow, loadProductsFlow, loadOrdersFlow)
                        .build())
                // Nach parallelem Laden: sequentielle Verarbeitung
                .next(processDataStep)
                .build()
                .build();
    }
}

// Monitoring-Konfiguration mit Micrometer
@Configuration
public class BatchMetricsConfig {

    private final MeterRegistry meterRegistry;

    public BatchMetricsConfig(MeterRegistry meterRegistry) {
        this.meterRegistry = meterRegistry;
    }

    @Bean
    public JobExecutionListener metricsJobListener() {
        return new JobExecutionListener() {

            private Timer.Sample jobTimer;

            @Override
            public void beforeJob(JobExecution jobExecution) {
                // Startet den Job-Dauer-Timer
                jobTimer = Timer.start(meterRegistry);
                Counter.builder("batch.job.started")
                        .tag("job", jobExecution.getJobInstance().getJobName())
                        .register(meterRegistry)
                        .increment();
            }

            @Override
            public void afterJob(JobExecution jobExecution) {
                // Erfasst die Gesamtdauer
                jobTimer.stop(Timer.builder("batch.job.duration")
                        .tag("job", jobExecution.getJobInstance().getJobName())
                        .tag("status", jobExecution.getStatus().toString())
                        .register(meterRegistry));

                // Job-Counter nach Status
                Counter.builder("batch.job.completed")
                        .tag("job", jobExecution.getJobInstance().getJobName())
                        .tag("status", jobExecution.getStatus().toString())
                        .register(meterRegistry)
                        .increment();
            }
        };
    }

    @Bean
    public StepExecutionListener metricsStepListener() {
        return new StepExecutionListener() {

            @Override
            public void afterStep(StepExecution stepExecution) {
                String jobName = stepExecution.getJobExecution().getJobInstance().getJobName();
                String stepName = stepExecution.getStepName();

                // Throughput-Metriken
                Gauge.builder("batch.step.read.count", stepExecution, StepExecution::getReadCount)
                        .tag("job", jobName)
                        .tag("step", stepName)
                        .register(meterRegistry);

                Gauge.builder("batch.step.write.count", stepExecution, StepExecution::getWriteCount)
                        .tag("job", jobName)
                        .tag("step", stepName)
                        .register(meterRegistry);

                Gauge.builder("batch.step.skip.count", stepExecution, StepExecution::getSkipCount)
                        .tag("job", jobName)
                        .tag("step", stepName)
                        .register(meterRegistry);

                return null;
            }
        };
    }
}

// Partitioner, der die Last tatsächlich ausgleicht
@Component
public class BalancedPartitioner implements Partitioner {

    private final JdbcTemplate jdbcTemplate;

    public BalancedPartitioner(JdbcTemplate jdbcTemplate) {
        this.jdbcTemplate = jdbcTemplate;
    }

    @Override
    public Map<String, ExecutionContext> partition(int gridSize) {
        // Zählt die Gesamtanzahl der zu verarbeitenden Items
        Integer totalCount = jdbcTemplate.queryForObject(
                "SELECT COUNT(*) FROM orders WHERE status = 'PENDING'", Integer.class);

        if (totalCount == null || totalCount == 0) {
            return Map.of();
        }

        // Berechnet die Zielgröße pro Partition
        int itemsPerPartition = (int) Math.ceil((double) totalCount / gridSize);

        Map<String, ExecutionContext> partitions = new HashMap<>();

        // Verwendet OFFSET/LIMIT für ausgeglichene Partitionen
        // Teurer als Ranges, garantiert aber den Ausgleich
        for (int i = 0; i < gridSize; i++) {
            ExecutionContext context = new ExecutionContext();
            context.putInt("offset", i * itemsPerPartition);
            context.putInt("limit", itemsPerPartition);
            context.putInt("partitionNumber", i);

            partitions.put("partition" + i, context);
        }

        return partitions;
    }
}

// OffsetBasedReader.java
// Reader kompatibel mit Offset-basiertem Partitioning
@StepScope
@Component
public class OffsetBasedReader implements ItemReader<OrderRecord>, ItemStream {

    private final JdbcTemplate jdbcTemplate;
    private Iterator<OrderRecord> iterator;

    @Value("#{stepExecutionContext['offset']}")
    private int offset;

    @Value("#{stepExecutionContext['limit']}")
    private int limit;

    public OffsetBasedReader(JdbcTemplate jdbcTemplate) {
        this.jdbcTemplate = jdbcTemplate;
    }

    @Override
    public void open(ExecutionContext executionContext) {
        // Lädt genau den dieser Partition zugewiesenen Anteil
        List<OrderRecord> records = jdbcTemplate.query(
                "SELECT * FROM orders WHERE status = 'PENDING' ORDER BY id LIMIT ? OFFSET ?",
                new OrderRecordRowMapper(),
                limit, offset
        );
        this.iterator = records.iterator();
    }

    @Override
    public OrderRecord read() {
        return iterator.hasNext() ? iterator.next() : null;
    }

    @Override
    public void update(ExecutionContext executionContext) {
        // Statusspeicherung für Restart, falls nötig
    }

    @Override
    public void close() {
        // Aufräumen
    }
}

// Verwaltung von Job-Abhängigkeiten
@Service
public class JobDependencyService {

    private final JobExplorer jobExplorer;
    private final JobLauncher jobLauncher;
    private final Map<String, Job> jobs;

    public JobDependencyService(JobExplorer jobExplorer,
                                  JobLauncher jobLauncher,
                                  Map<String, Job> jobs) {
        this.jobExplorer = jobExplorer;
        this.jobLauncher = jobLauncher;
        this.jobs = jobs;
    }

    public JobExecution runWithDependencies(String jobName,
                                             JobParameters params,
                                             List<String> dependsOn) throws Exception {
        // Prüft, dass alle Abhängigkeiten erfolgreich waren
        for (String dependency : dependsOn) {
            if (!hasSuccessfulExecution(dependency, params)) {
                throw new JobExecutionException(
                        "Dependency not satisfied: " + dependency);
            }
        }

        Job job = jobs.get(jobName);
        if (job == null) {
            throw new IllegalArgumentException("Unknown job: " + jobName);
        }

        return jobLauncher.run(job, params);
    }

    private boolean hasSuccessfulExecution(String jobName, JobParameters params) {
        // Sucht eine COMPLETED-Ausführung mit denselben Geschäftsparametern
        return jobExplorer.findJobInstancesByJobName(jobName, 0, 1)
                .stream()
                .flatMap(instance -> jobExplorer.getJobExecutions(instance).stream())
                .filter(exec -> exec.getStatus() == BatchStatus.COMPLETED)
                .anyMatch(exec -> matchesBusinessParams(exec.getJobParameters(), params));
    }

    private boolean matchesBusinessParams(JobParameters actual, JobParameters expected) {
        // Vergleicht Geschäftsparameter (ignoriert Ausführungs-Timestamps)
        String actualDate = actual.getString("businessDate");
        String expectedDate = expected.getString("businessDate");
        return Objects.equals(actualDate, expectedDate);
    }
}

// Unit-Test des Processors
@ExtendWith(MockitoExtension.class)
class OrderProcessorTest {

    @Mock
    private PricingService pricingService;

    @Mock
    private ValidationService validationService;

    @InjectMocks
    private OrderItemProcessor processor;

    @Test
    void shouldProcessValidOrder() {
        // Given
        OrderRecord input = new OrderRecord(1L, 100L, BigDecimal.TEN);
        when(validationService.isValid(input)).thenReturn(true);
        when(pricingService.calculatePrice(input)).thenReturn(new BigDecimal("12.50"));

        // When
        ProcessedOrder result = processor.process(input);

        // Then
        assertThat(result).isNotNull();
        assertThat(result.finalPrice()).isEqualTo(new BigDecimal("12.50"));
    }

    @Test
    void shouldFilterInvalidOrder() {
        // Given
        OrderRecord input = new OrderRecord(1L, 100L, BigDecimal.TEN);
        when(validationService.isValid(input)).thenReturn(false);

        // When
        ProcessedOrder result = processor.process(input);

        // Then - null bedeutet gefiltert
        assertThat(result).isNull();
        verify(pricingService, never()).calculatePrice(any());
    }
}

// Integrationstest des vollständigen Jobs
@SpringBatchTest
@SpringBootTest
@ActiveProfiles("test")
class ImportJobIntegrationTest {

    @Autowired
    private JobLauncherTestUtils jobLauncherTestUtils;

    @Autowired
    private JobRepositoryTestUtils jobRepositoryTestUtils;

    @Autowired
    private JdbcTemplate jdbcTemplate;

    @BeforeEach
    void setup() {
        // Säubert Metadaten zwischen Tests
        jobRepositoryTestUtils.removeJobExecutions();
        // Setzt Testdaten zurück
        jdbcTemplate.execute("DELETE FROM processed_orders");
        jdbcTemplate.execute("DELETE FROM orders");
    }

    @Test
    void shouldCompleteJobSuccessfully() throws Exception {
        // Given - Testdaten
        insertTestOrders(100);

        // When
        JobParameters params = new JobParametersBuilder()
                .addLocalDate("businessDate", LocalDate.now())
                .addLong("run.id", System.currentTimeMillis())
                .toJobParameters();

        JobExecution execution = jobLauncherTestUtils.launchJob(params);

        // Then
        assertThat(execution.getStatus()).isEqualTo(BatchStatus.COMPLETED);
        assertThat(countProcessedOrders()).isEqualTo(100);
    }

    @Test
    void shouldHandleEmptyDataset() throws Exception {
        // Given - keine Daten

        // When
        JobExecution execution = jobLauncherTestUtils.launchJob();

        // Then - Job ist auch ohne Daten erfolgreich
        assertThat(execution.getStatus()).isEqualTo(BatchStatus.COMPLETED);
    }

    @Test
    void shouldRestartFromFailurePoint() throws Exception {
        // Given - simuliert Fehler mitten in der Verarbeitung
        insertTestOrders(100);
        insertPoisonOrder(50);  // Verursacht einen Fehler

        // When - erste Ausführung schlägt fehl
        JobExecution firstExecution = jobLauncherTestUtils.launchJob();
        assertThat(firstExecution.getStatus()).isEqualTo(BatchStatus.FAILED);

        // Daten korrigieren
        removePoisonOrder(50);

        // When - Restart
        JobExecution restartExecution = jobLauncherTestUtils.launchJob(
                firstExecution.getJobParameters());

        // Then - nimmt vom Fehlerpunkt wieder auf
        assertThat(restartExecution.getStatus()).isEqualTo(BatchStatus.COMPLETED);
    }

    private void insertTestOrders(int count) {
        for (int i = 1; i <= count; i++) {
            jdbcTemplate.update(
                    "INSERT INTO orders (id, customer_id, amount, status) VALUES (?, ?, ?, 'PENDING')",
                    i, i * 10, BigDecimal.valueOf(i * 10));
        }
    }

    private int countProcessedOrders() {
        return jdbcTemplate.queryForObject(
                "SELECT COUNT(*) FROM processed_orders", Integer.class);
    }
}

// Writer optimiert für hohe Volumina
@Component
public class OptimizedJdbcWriter implements ItemWriter<ProcessedOrder> {

    private final JdbcTemplate jdbcTemplate;
    private final DataSource dataSource;

    public OptimizedJdbcWriter(JdbcTemplate jdbcTemplate, DataSource dataSource) {
        this.jdbcTemplate = jdbcTemplate;
        this.dataSource = dataSource;
    }

    @Override
    public void write(Chunk<? extends ProcessedOrder> chunk) throws Exception {
        List<? extends ProcessedOrder> items = chunk.getItems();

        if (items.isEmpty()) {
            return;
        }

        // Verwendet PreparedStatement mit Batch
        try (Connection connection = dataSource.getConnection();
             PreparedStatement ps = connection.prepareStatement(
                     "INSERT INTO processed_orders (order_id, customer_id, final_price, processed_at) " +
                             "VALUES (?, ?, ?, ?)")) {

            for (ProcessedOrder order : items) {
                ps.setLong(1, order.orderId());
                ps.setLong(2, order.customerId());
                ps.setBigDecimal(3, order.finalPrice());
                ps.setTimestamp(4, Timestamp.valueOf(order.processedAt()));
                ps.addBatch();
            }

            // Führt alle Inserts in einer einzigen Netzwerk-Operation aus
            ps.executeBatch();
        }
    }
}

// StagingTableWriter.java
// Staging-Table-Pattern für sehr hohe Volumina
@Component
public class StagingTableWriter implements ItemWriter<ProcessedOrder>, StepExecutionListener {

    private final JdbcTemplate jdbcTemplate;
    private String stagingTable;

    public StagingTableWriter(JdbcTemplate jdbcTemplate) {
        this.jdbcTemplate = jdbcTemplate;
    }

    @Override
    public void beforeStep(StepExecution stepExecution) {
        // Erstellt eine temporäre Tabelle für diesen Step
        stagingTable = "staging_orders_" + stepExecution.getId();
        jdbcTemplate.execute(
                "CREATE TEMP TABLE " + stagingTable + " (LIKE processed_orders INCLUDING ALL)");
    }

    @Override
    public void write(Chunk<? extends ProcessedOrder> chunk) {
        // Schreibt in die Staging-Tabelle (ohne FK-Constraints)
        String sql = "INSERT INTO " + stagingTable +
                " (order_id, customer_id, final_price, processed_at) VALUES (?, ?, ?, ?)";

        jdbcTemplate.batchUpdate(sql, chunk.getItems(), chunk.size(),
                (ps, order) -> {
                    ps.setLong(1, order.orderId());
                    ps.setLong(2, order.customerId());
                    ps.setBigDecimal(3, order.finalPrice());
                    ps.setTimestamp(4, Timestamp.valueOf(order.processedAt()));
                });
    }

    @Override
    public ExitStatus afterStep(StepExecution stepExecution) {
        if (stepExecution.getStatus() == BatchStatus.COMPLETED) {
            // Bulk Copy in die finale Tabelle
            jdbcTemplate.execute(
                    "INSERT INTO processed_orders SELECT * FROM " + stagingTable);
        }
        // Säubert die Staging-Tabelle
        jdbcTemplate.execute("DROP TABLE IF EXISTS " + stagingTable);
        return stepExecution.getExitStatus();
    }
}