Examples with DataSetMoveTask gov.cms.bfd.pipeline.ccw.rif.extract.s3.task.DataSetMoveTask used on opensource projects

Example 1 with DataSetMoveTask

use of gov.cms.bfd.pipeline.ccw.rif.extract.s3.task.DataSetMoveTask in project beneficiary-fhir-data by CMSgov.

the class CcwRifLoadJob method call.

/**
 * @see gov.cms.bfd.pipeline.sharedutils.PipelineJob#call()
 */
@Override
public PipelineJobOutcome call() throws Exception {
    LOGGER.debug("Scanning for data sets to process...");
    // Update the queue from S3.
    dataSetQueue.updatePendingDataSets();
    // If no manifest was found, we're done (until next time).
    if (dataSetQueue.isEmpty()) {
        LOGGER.debug(LOG_MESSAGE_NO_DATA_SETS);
        listener.noDataAvailable();
        return PipelineJobOutcome.NOTHING_TO_DO;
    }
    // We've found the oldest manifest.
    DataSetManifest manifestToProcess = dataSetQueue.getNextDataSetToProcess().get();
    LOGGER.info("Found data set to process: '{}'." + " There were '{}' total pending data sets and '{}' completed ones.", manifestToProcess.toString(), dataSetQueue.getPendingManifestsCount(), dataSetQueue.getCompletedManifestsCount().get());
    /*
     * We've got a data set to process. However, it might still be uploading
     * to S3, so we need to wait for that to complete before we start
     * processing it.
     */
    boolean alreadyLoggedWaitingEvent = false;
    while (!dataSetIsAvailable(manifestToProcess)) {
        /*
       * We're very patient here, so we keep looping, but it's prudent to
       * pause between each iteration. TODO should eventually time out,
       * once we know how long transfers might take
       */
        try {
            if (!alreadyLoggedWaitingEvent) {
                LOGGER.info("Data set not ready. Waiting for it to finish uploading...");
                alreadyLoggedWaitingEvent = true;
            }
            Thread.sleep(1000 * 1);
        } catch (InterruptedException e) {
            /*
         * Many Java applications use InterruptedExceptions to signal
         * that a thread should stop what it's doing ASAP. This app
         * doesn't, so this is unexpected, and accordingly, we don't
         * know what to do. Safest bet is to blow up.
         */
            throw new RuntimeException(e);
        }
    }
    /*
     * Huzzah! We've got a data set to process and we've verified it's all there
     * waiting for us in S3. Now convert it into a RifFilesEvent (containing a List
     * of asynchronously-downloading S3RifFiles.
     */
    LOGGER.info(LOG_MESSAGE_DATA_SET_READY);
    List<S3RifFile> rifFiles = manifestToProcess.getEntries().stream().map(manifestEntry -> new S3RifFile(appMetrics, manifestEntry, s3TaskManager.downloadAsync(manifestEntry))).collect(Collectors.toList());
    RifFilesEvent rifFilesEvent = new RifFilesEvent(manifestToProcess.getTimestamp(), new ArrayList<>(rifFiles));
    /*
     * To save time for the next data set, peek ahead at it. If it's available and
     * it looks like there's enough disk space, start downloading it early in the
     * background.
     */
    Optional<DataSetManifest> secondManifestToProcess = dataSetQueue.getSecondDataSetToProcess();
    if (secondManifestToProcess.isPresent() && dataSetIsAvailable(secondManifestToProcess.get())) {
        Path tmpdir = Paths.get(System.getProperty("java.io.tmpdir"));
        long usableFreeTempSpace;
        try {
            usableFreeTempSpace = Files.getFileStore(tmpdir).getUsableSpace();
        } catch (IOException e) {
            throw new UncheckedIOException(e);
        }
        if (usableFreeTempSpace >= (50 * GIGA)) {
            secondManifestToProcess.get().getEntries().stream().forEach(manifestEntry -> s3TaskManager.downloadAsync(manifestEntry));
        }
    }
    /*
     * Now we hand that off to the DataSetMonitorListener, to do the *real*
     * work of actually processing that data set. It's important that we
     * block until it's completed, in order to ensure that we don't end up
     * processing multiple data sets in parallel (which would lead to data
     * consistency problems).
     */
    listener.dataAvailable(rifFilesEvent);
    LOGGER.info(LOG_MESSAGE_DATA_SET_COMPLETE);
    /*
     * Now that the data set has been processed, we need to ensure that we
     * don't end up processing it again. We ensure this two ways: 1) we keep
     * a list of the data sets most recently processed, and 2) we rename the
     * S3 objects that comprise that data set. (#1 is required as S3
     * deletes/moves are only *eventually* consistent, so #2 may not take
     * effect right away.)
     */
    rifFiles.stream().forEach(f -> f.cleanupTempFile());
    dataSetQueue.markProcessed(manifestToProcess);
    s3TaskManager.submit(new DataSetMoveTask(s3TaskManager, options, manifestToProcess));
    return PipelineJobOutcome.WORK_DONE;
}