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Spring Batch-了解塊大小和ItemReadListener之間的行為

[英]Spring Batch - Understanding the behaviour between chunk size and ItemReadListener

情況

我已經使用java config在spring批處理中設置了一個簡單的讀取作業,並且我試圖編寫一個簡單的偵聽器。 偵聽器應顯示讀取特定數量的記錄所花費的時間(以秒為單位)。

Bean如下所示:

@Bean
public SimpleItemReaderListener listener(){
    SimpleItemReaderListener listener = new SimpleItemReaderListener<>();           
    listener.setLogInterval(50000);
    return listener;
}

根據設置的日志間隔,將顯示一條消息,並且該消息將如下所示:

14:42:11,445  INFO main SimpleItemReaderListener:45 - Read records [0] to [50.000] in average 1,30 seconds
14:42:14,453  INFO main SimpleItemReaderListener:45 - Read records [50.000] to [100.000] in average 2,47 seconds
14:42:15,489  INFO main SimpleItemReaderListener:45 - Read records [100.000] to [150.000] in average 1,03 seconds
14:42:16,448  INFO main SimpleItemReaderListener:45 - Read records [150.000] to [200.000] in average 0,44 seconds 

正是我想要的,完美。 但是,當我將batchConfiguration中的塊從100.000更改為1.000時,日志記錄發生了變化,我不知道是什么導致了更改...

14:51:24,893  INFO main SimpleItemReaderListener:45 - Read records [0] to [50.000] in average 0,90 seconds
14:51:50,657  INFO main SimpleItemReaderListener:45 - Read records [50.000] to [100.000] in average 0,57 seconds
14:52:16,392  INFO main SimpleItemReaderListener:45 - Read records [100.000] to [150.000] in average 0,59 seconds
14:52:42,125  INFO main SimpleItemReaderListener:45 - Read records [150.000] to [200.000] in average 0,61 seconds

在給每個項目執行ItemReaderListener中的beforeRead和afterRead方法的印象下,我期望每50.000花費的時間與slf4j日志中顯示的時間更加一致(例如,大約26秒每個50.000)。

更改塊大小時,偵聽器的哪一部分會導致此不良行為?

復制

我對ItemReadListener的實現如下:

public class SimpleItemReaderListener<Item> implements ItemReadListener<Item>{

    private static final Logger LOG = LoggerFactory.getLogger(SimpleItemReaderListener.class);
    private static final double NANO_TO_SECOND_DIVIDER_NUMBER = 1_000_000_000.0;    
    private static final String PATTERN = ",###";   

    private int startCount = 0;
    private int logInterval = 50000;
    private int currentCount;
    private int totalCount;
    private long timeElapsed;
    private long startTime;
    private DecimalFormat decimalFormat = new DecimalFormat(PATTERN);

    @Override
    public void beforeRead() {
        startTime = System.nanoTime();              
    }

    @Override
    public void afterRead(Item item) {
        updateTimeElapsed();        
        if (currentCount == logInterval) {          
            displayMessage();
            updateStartCount();
            resetCount();
        } else {
            increaseCount();
        }       
    }

    private void updateTimeElapsed() {
        timeElapsed += System.nanoTime() - startTime;
    }

    private void displayMessage() {
        LOG.info(String.format("Read records [%s] to [%s] in average %.2f seconds", 
                decimalFormat.format(startCount), 
                decimalFormat.format(totalCount), 
                timeElapsed / NANO_TO_SECOND_DIVIDER_NUMBER));      
    }

    private void updateStartCount() {
        startCount += currentCount;
    }

    private void resetCount() {
        currentCount = 0;
        timeElapsed = 0;
    }

    private void increaseCount() {
        currentCount++;
        totalCount++;
    }

    @Override
    public void onReadError(Exception arg0) {
        // NO-OP
    }

    public void setLogInterval(int logInterval){
        this.logInterval = logInterval;
    }
}

完整的batchconfiguration類:

@Configuration
@EnableBatchProcessing
public class BatchConfiguration {   

    @Autowired
    public JobBuilderFactory jobBuilderFactory;

    @Autowired
    public StepBuilderFactory stepBuilderFactory;

    @Bean
    public Job importUserJob() {
        return jobBuilderFactory.get("importUserJob")            
                .flow(validateInput())
                .end()
                .build();
    }    

    @Bean
    public Step validateInput() {
        return stepBuilderFactory.get("validateInput")
                .chunk(1000)
                .reader(reader())               
                .listener(listener())
                .writer(writer())
                .build();
    }

    @Bean 
    public HeaderTokenizer tokenizeHeader(){
        HeaderTokenizer tokenizer = new HeaderTokenizer();
        //optional setting, custom delimiter is set to ','
        //tokenizer.setDelimiter(",");
        return tokenizer;
    }

    @Bean
    public SimpleItemReaderListener listener(){
        SimpleItemReaderListener listener = new SimpleItemReaderListener<>();
        //optional setting, custom logging is set to 1000, increase for less verbose logging
        listener.setLogInterval(50000);
        return listener;
    }

    @Bean   
    public FlatFileItemReader reader() {
        FlatFileItemReader reader = new FlatFileItemReader();        
        reader.setLinesToSkip(1);        
        reader.setSkippedLinesCallback(tokenizeHeader());
        reader.setResource(new ClassPathResource("majestic_million.csv"));
        reader.setLineMapper(new DefaultLineMapper() {{
            setLineTokenizer(tokenizeHeader());
            setFieldSetMapper(new PassThroughFieldSetMapper());
        }});
        return reader;
    }    

    @Bean
    public DummyItemWriter writer(){
        DummyItemWriter writer = new DummyItemWriter();
        return writer;
    }
}

或者使用http://projects.spring.io/spring-batch/中的spring引導示例,並添加SimpleItemReaderListener bean。

當批處理量較小時,您的應用程序在閱讀器上花費了更多時間。 您的計時代碼僅測量花費在閱讀器上的時間,但是日志記錄框架顯示時間戳,這是總花費的時間。

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