use of org.apache.druid.segment.realtime.appenderator.SegmentsAndCommitMetadata in project druid by druid-io.
the class PartialSegmentGenerateTask method generateSegments.
private List<DataSegment> generateSegments(final TaskToolbox toolbox, final ParallelIndexSupervisorTaskClient taskClient, final InputSource inputSource, final File tmpDir) throws IOException, InterruptedException, ExecutionException, TimeoutException {
final DataSchema dataSchema = ingestionSchema.getDataSchema();
final FireDepartment fireDepartmentForMetrics = new FireDepartment(dataSchema, new RealtimeIOConfig(null, null), null);
final FireDepartmentMetrics fireDepartmentMetrics = fireDepartmentForMetrics.getMetrics();
final RowIngestionMeters buildSegmentsMeters = toolbox.getRowIngestionMetersFactory().createRowIngestionMeters();
toolbox.addMonitor(new RealtimeMetricsMonitor(Collections.singletonList(fireDepartmentForMetrics), Collections.singletonMap(DruidMetrics.TASK_ID, new String[] { getId() })));
final ParallelIndexTuningConfig tuningConfig = ingestionSchema.getTuningConfig();
final PartitionsSpec partitionsSpec = tuningConfig.getGivenOrDefaultPartitionsSpec();
final long pushTimeout = tuningConfig.getPushTimeout();
final SegmentAllocatorForBatch segmentAllocator = createSegmentAllocator(toolbox, taskClient);
final SequenceNameFunction sequenceNameFunction = segmentAllocator.getSequenceNameFunction();
final ParseExceptionHandler parseExceptionHandler = new ParseExceptionHandler(buildSegmentsMeters, tuningConfig.isLogParseExceptions(), tuningConfig.getMaxParseExceptions(), tuningConfig.getMaxSavedParseExceptions());
final boolean useMaxMemoryEstimates = getContextValue(Tasks.USE_MAX_MEMORY_ESTIMATES, Tasks.DEFAULT_USE_MAX_MEMORY_ESTIMATES);
final Appenderator appenderator = BatchAppenderators.newAppenderator(getId(), toolbox.getAppenderatorsManager(), fireDepartmentMetrics, toolbox, dataSchema, tuningConfig, new ShuffleDataSegmentPusher(supervisorTaskId, getId(), toolbox.getIntermediaryDataManager()), buildSegmentsMeters, parseExceptionHandler, useMaxMemoryEstimates);
boolean exceptionOccurred = false;
try (final BatchAppenderatorDriver driver = BatchAppenderators.newDriver(appenderator, toolbox, segmentAllocator)) {
driver.startJob();
final SegmentsAndCommitMetadata pushed = InputSourceProcessor.process(dataSchema, driver, partitionsSpec, inputSource, inputSource.needsFormat() ? ParallelIndexSupervisorTask.getInputFormat(ingestionSchema) : null, tmpDir, sequenceNameFunction, inputRowIteratorBuilder, buildSegmentsMeters, parseExceptionHandler, pushTimeout);
return pushed.getSegments();
} catch (Exception e) {
exceptionOccurred = true;
throw e;
} finally {
if (exceptionOccurred) {
appenderator.closeNow();
} else {
appenderator.close();
}
}
}
use of org.apache.druid.segment.realtime.appenderator.SegmentsAndCommitMetadata in project druid by druid-io.
the class IndexTask method generateAndPublishSegments.
/**
* This method reads input data row by row and adds the read row to a proper segment using {@link BaseAppenderatorDriver}.
* If there is no segment for the row, a new one is created. Segments can be published in the middle of reading inputs
* if {@link DynamicPartitionsSpec} is used and one of below conditions are satisfied.
*
* <ul>
* <li>
* If the number of rows in a segment exceeds {@link DynamicPartitionsSpec#maxRowsPerSegment}
* </li>
* <li>
* If the number of rows added to {@link BaseAppenderatorDriver} so far exceeds {@link DynamicPartitionsSpec#maxTotalRows}
* </li>
* </ul>
* <p>
* At the end of this method, all the remaining segments are published.
*
* @return the last {@link TaskStatus}
*/
private TaskStatus generateAndPublishSegments(final TaskToolbox toolbox, final DataSchema dataSchema, final InputSource inputSource, final File tmpDir, final PartitionAnalysis partitionAnalysis) throws IOException, InterruptedException {
final FireDepartment fireDepartmentForMetrics = new FireDepartment(dataSchema, new RealtimeIOConfig(null, null), null);
FireDepartmentMetrics buildSegmentsFireDepartmentMetrics = fireDepartmentForMetrics.getMetrics();
if (toolbox.getMonitorScheduler() != null) {
final TaskRealtimeMetricsMonitor metricsMonitor = TaskRealtimeMetricsMonitorBuilder.build(this, fireDepartmentForMetrics, buildSegmentsMeters);
toolbox.getMonitorScheduler().addMonitor(metricsMonitor);
}
final PartitionsSpec partitionsSpec = partitionAnalysis.getPartitionsSpec();
final IndexTuningConfig tuningConfig = ingestionSchema.getTuningConfig();
final long pushTimeout = tuningConfig.getPushTimeout();
final SegmentAllocatorForBatch segmentAllocator;
final SequenceNameFunction sequenceNameFunction;
switch(partitionsSpec.getType()) {
case HASH:
case RANGE:
final SegmentAllocatorForBatch localSegmentAllocator = SegmentAllocators.forNonLinearPartitioning(toolbox, getDataSource(), baseSequenceName, dataSchema.getGranularitySpec(), null, (CompletePartitionAnalysis) partitionAnalysis);
sequenceNameFunction = localSegmentAllocator.getSequenceNameFunction();
segmentAllocator = localSegmentAllocator;
break;
case LINEAR:
segmentAllocator = SegmentAllocators.forLinearPartitioning(toolbox, baseSequenceName, null, dataSchema, getTaskLockHelper(), ingestionSchema.getIOConfig().isAppendToExisting(), partitionAnalysis.getPartitionsSpec(), null);
sequenceNameFunction = segmentAllocator.getSequenceNameFunction();
break;
default:
throw new UOE("[%s] secondary partition type is not supported", partitionsSpec.getType());
}
Set<DataSegment> segmentsFoundForDrop = null;
if (ingestionSchema.getIOConfig().isDropExisting()) {
segmentsFoundForDrop = getUsedSegmentsWithinInterval(toolbox, getDataSource(), ingestionSchema.getDataSchema().getGranularitySpec().inputIntervals());
}
final TransactionalSegmentPublisher publisher = (segmentsToBeOverwritten, segmentsToDrop, segmentsToPublish, commitMetadata) -> toolbox.getTaskActionClient().submit(SegmentTransactionalInsertAction.overwriteAction(segmentsToBeOverwritten, segmentsToDrop, segmentsToPublish));
String effectiveId = getContextValue(CompactionTask.CTX_KEY_APPENDERATOR_TRACKING_TASK_ID, null);
if (effectiveId == null) {
effectiveId = getId();
}
final Appenderator appenderator = BatchAppenderators.newAppenderator(effectiveId, toolbox.getAppenderatorsManager(), buildSegmentsFireDepartmentMetrics, toolbox, dataSchema, tuningConfig, buildSegmentsMeters, buildSegmentsParseExceptionHandler, isUseMaxMemoryEstimates());
boolean exceptionOccurred = false;
try (final BatchAppenderatorDriver driver = BatchAppenderators.newDriver(appenderator, toolbox, segmentAllocator)) {
driver.startJob();
InputSourceProcessor.process(dataSchema, driver, partitionsSpec, inputSource, inputSource.needsFormat() ? getInputFormat(ingestionSchema) : null, tmpDir, sequenceNameFunction, new DefaultIndexTaskInputRowIteratorBuilder(), buildSegmentsMeters, buildSegmentsParseExceptionHandler, pushTimeout);
// If we use timeChunk lock, then we don't have to specify what segments will be overwritten because
// it will just overwrite all segments overlapped with the new segments.
final Set<DataSegment> inputSegments = getTaskLockHelper().isUseSegmentLock() ? getTaskLockHelper().getLockedExistingSegments() : null;
final boolean storeCompactionState = getContextValue(Tasks.STORE_COMPACTION_STATE_KEY, Tasks.DEFAULT_STORE_COMPACTION_STATE);
final Function<Set<DataSegment>, Set<DataSegment>> annotateFunction = compactionStateAnnotateFunction(storeCompactionState, toolbox, ingestionSchema);
// Probably we can publish atomicUpdateGroup along with segments.
final SegmentsAndCommitMetadata published = awaitPublish(driver.publishAll(inputSegments, segmentsFoundForDrop, publisher, annotateFunction), pushTimeout);
appenderator.close();
// for awaitSegmentAvailabilityTimeoutMillis
if (tuningConfig.getAwaitSegmentAvailabilityTimeoutMillis() > 0 && published != null) {
ingestionState = IngestionState.SEGMENT_AVAILABILITY_WAIT;
ArrayList<DataSegment> segmentsToWaitFor = new ArrayList<>(published.getSegments());
waitForSegmentAvailability(toolbox, segmentsToWaitFor, tuningConfig.getAwaitSegmentAvailabilityTimeoutMillis());
}
ingestionState = IngestionState.COMPLETED;
if (published == null) {
log.error("Failed to publish segments, aborting!");
errorMsg = "Failed to publish segments.";
toolbox.getTaskReportFileWriter().write(getId(), getTaskCompletionReports());
return TaskStatus.failure(getId(), errorMsg);
} else {
log.info("Processed[%,d] events, unparseable[%,d], thrownAway[%,d].", buildSegmentsMeters.getProcessed(), buildSegmentsMeters.getUnparseable(), buildSegmentsMeters.getThrownAway());
log.info("Published [%s] segments", published.getSegments().size());
log.debugSegments(published.getSegments(), "Published segments");
toolbox.getTaskReportFileWriter().write(getId(), getTaskCompletionReports());
return TaskStatus.success(getId());
}
} catch (TimeoutException | ExecutionException e) {
exceptionOccurred = true;
throw new RuntimeException(e);
} catch (Exception e) {
exceptionOccurred = true;
throw e;
} finally {
if (exceptionOccurred) {
appenderator.closeNow();
} else {
appenderator.close();
}
}
}
use of org.apache.druid.segment.realtime.appenderator.SegmentsAndCommitMetadata in project druid by druid-io.
the class SinglePhaseSubTask method generateAndPushSegments.
/**
* This method reads input data row by row and adds the read row to a proper segment using {@link BaseAppenderatorDriver}.
* If there is no segment for the row, a new one is created. Segments can be published in the middle of reading inputs
* if one of below conditions are satisfied.
*
* <ul>
* <li>
* If the number of rows in a segment exceeds {@link DynamicPartitionsSpec#maxRowsPerSegment}
* </li>
* <li>
* If the number of rows added to {@link BaseAppenderatorDriver} so far exceeds {@link DynamicPartitionsSpec#maxTotalRows}
* </li>
* </ul>
* <p>
* At the end of this method, all the remaining segments are published.
*
* @return true if generated segments are successfully published, otherwise false
*/
private Set<DataSegment> generateAndPushSegments(final TaskToolbox toolbox, final ParallelIndexSupervisorTaskClient taskClient, final InputSource inputSource, final File tmpDir) throws IOException, InterruptedException {
final DataSchema dataSchema = ingestionSchema.getDataSchema();
final GranularitySpec granularitySpec = dataSchema.getGranularitySpec();
final FireDepartment fireDepartmentForMetrics = new FireDepartment(dataSchema, new RealtimeIOConfig(null, null), null);
final FireDepartmentMetrics fireDepartmentMetrics = fireDepartmentForMetrics.getMetrics();
toolbox.addMonitor(new RealtimeMetricsMonitor(Collections.singletonList(fireDepartmentForMetrics), Collections.singletonMap(DruidMetrics.TASK_ID, new String[] { getId() })));
final ParallelIndexTuningConfig tuningConfig = ingestionSchema.getTuningConfig();
final DynamicPartitionsSpec partitionsSpec = (DynamicPartitionsSpec) tuningConfig.getGivenOrDefaultPartitionsSpec();
final long pushTimeout = tuningConfig.getPushTimeout();
final boolean explicitIntervals = !granularitySpec.inputIntervals().isEmpty();
final boolean useLineageBasedSegmentAllocation = getContextValue(SinglePhaseParallelIndexTaskRunner.CTX_USE_LINEAGE_BASED_SEGMENT_ALLOCATION_KEY, SinglePhaseParallelIndexTaskRunner.LEGACY_DEFAULT_USE_LINEAGE_BASED_SEGMENT_ALLOCATION);
// subtaskSpecId is used as the sequenceName, so that retry tasks for the same spec
// can allocate the same set of segments.
final String sequenceName = useLineageBasedSegmentAllocation ? Preconditions.checkNotNull(subtaskSpecId, "subtaskSpecId") : getId();
final SegmentAllocatorForBatch segmentAllocator = SegmentAllocators.forLinearPartitioning(toolbox, sequenceName, new SupervisorTaskAccess(getSupervisorTaskId(), taskClient), getIngestionSchema().getDataSchema(), getTaskLockHelper(), ingestionSchema.getIOConfig().isAppendToExisting(), partitionsSpec, useLineageBasedSegmentAllocation);
final boolean useMaxMemoryEstimates = getContextValue(Tasks.USE_MAX_MEMORY_ESTIMATES, Tasks.DEFAULT_USE_MAX_MEMORY_ESTIMATES);
final Appenderator appenderator = BatchAppenderators.newAppenderator(getId(), toolbox.getAppenderatorsManager(), fireDepartmentMetrics, toolbox, dataSchema, tuningConfig, rowIngestionMeters, parseExceptionHandler, useMaxMemoryEstimates);
boolean exceptionOccurred = false;
try (final BatchAppenderatorDriver driver = BatchAppenderators.newDriver(appenderator, toolbox, segmentAllocator);
final CloseableIterator<InputRow> inputRowIterator = AbstractBatchIndexTask.inputSourceReader(tmpDir, dataSchema, inputSource, inputSource.needsFormat() ? ParallelIndexSupervisorTask.getInputFormat(ingestionSchema) : null, inputRow -> {
if (inputRow == null) {
return false;
}
if (explicitIntervals) {
final Optional<Interval> optInterval = granularitySpec.bucketInterval(inputRow.getTimestamp());
return optInterval.isPresent();
}
return true;
}, rowIngestionMeters, parseExceptionHandler)) {
driver.startJob();
final Set<DataSegment> pushedSegments = new HashSet<>();
while (inputRowIterator.hasNext()) {
final InputRow inputRow = inputRowIterator.next();
// Segments are created as needed, using a single sequence name. They may be allocated from the overlord
// (in append mode) or may be created on our own authority (in overwrite mode).
final AppenderatorDriverAddResult addResult = driver.add(inputRow, sequenceName);
if (addResult.isOk()) {
final boolean isPushRequired = addResult.isPushRequired(partitionsSpec.getMaxRowsPerSegment(), partitionsSpec.getMaxTotalRowsOr(DynamicPartitionsSpec.DEFAULT_MAX_TOTAL_ROWS));
if (isPushRequired) {
// There can be some segments waiting for being published even though any rows won't be added to them.
// If those segments are not published here, the available space in appenderator will be kept to be small
// which makes the size of segments smaller.
final SegmentsAndCommitMetadata pushed = driver.pushAllAndClear(pushTimeout);
pushedSegments.addAll(pushed.getSegments());
LOG.info("Pushed [%s] segments", pushed.getSegments().size());
LOG.infoSegments(pushed.getSegments(), "Pushed segments");
}
} else {
throw new ISE("Failed to add a row with timestamp[%s]", inputRow.getTimestamp());
}
fireDepartmentMetrics.incrementProcessed();
}
final SegmentsAndCommitMetadata pushed = driver.pushAllAndClear(pushTimeout);
pushedSegments.addAll(pushed.getSegments());
LOG.info("Pushed [%s] segments", pushed.getSegments().size());
LOG.infoSegments(pushed.getSegments(), "Pushed segments");
appenderator.close();
return pushedSegments;
} catch (TimeoutException | ExecutionException e) {
exceptionOccurred = true;
throw new RuntimeException(e);
} catch (Exception e) {
exceptionOccurred = true;
throw e;
} finally {
if (exceptionOccurred) {
appenderator.closeNow();
} else {
appenderator.close();
}
}
}
use of org.apache.druid.segment.realtime.appenderator.SegmentsAndCommitMetadata in project druid by druid-io.
the class InputSourceProcessor method process.
/**
* This method opens the given {@link InputSource} and processes data via {@link InputSourceReader}.
* All read data is consumed by {@link BatchAppenderatorDriver} which creates new segments.
* All created segments are pushed when all input data is processed successfully.
*
* @return {@link SegmentsAndCommitMetadata} for the pushed segments.
*/
public static SegmentsAndCommitMetadata process(DataSchema dataSchema, BatchAppenderatorDriver driver, PartitionsSpec partitionsSpec, InputSource inputSource, @Nullable InputFormat inputFormat, File tmpDir, SequenceNameFunction sequenceNameFunction, IndexTaskInputRowIteratorBuilder inputRowIteratorBuilder, RowIngestionMeters buildSegmentsMeters, ParseExceptionHandler parseExceptionHandler, long pushTimeout) throws IOException, InterruptedException, ExecutionException, TimeoutException {
@Nullable final DynamicPartitionsSpec dynamicPartitionsSpec = partitionsSpec instanceof DynamicPartitionsSpec ? (DynamicPartitionsSpec) partitionsSpec : null;
final GranularitySpec granularitySpec = dataSchema.getGranularitySpec();
try (final CloseableIterator<InputRow> inputRowIterator = AbstractBatchIndexTask.inputSourceReader(tmpDir, dataSchema, inputSource, inputFormat, AbstractBatchIndexTask.defaultRowFilter(granularitySpec), buildSegmentsMeters, parseExceptionHandler);
final HandlingInputRowIterator iterator = inputRowIteratorBuilder.delegate(inputRowIterator).granularitySpec(granularitySpec).build()) {
while (iterator.hasNext()) {
final InputRow inputRow = iterator.next();
if (inputRow == null) {
continue;
}
// IndexTaskInputRowIteratorBuilder.absentBucketIntervalConsumer() ensures the interval will be present here
Optional<Interval> optInterval = granularitySpec.bucketInterval(inputRow.getTimestamp());
@SuppressWarnings("OptionalGetWithoutIsPresent") final Interval interval = optInterval.get();
final String sequenceName = sequenceNameFunction.getSequenceName(interval, inputRow);
final AppenderatorDriverAddResult addResult = driver.add(inputRow, sequenceName);
if (addResult.isOk()) {
// incremental segment publishment is allowed only when rollup doesn't have to be perfect.
if (dynamicPartitionsSpec != null) {
final boolean isPushRequired = addResult.isPushRequired(dynamicPartitionsSpec.getMaxRowsPerSegment(), dynamicPartitionsSpec.getMaxTotalRowsOr(DynamicPartitionsSpec.DEFAULT_MAX_TOTAL_ROWS));
if (isPushRequired) {
// There can be some segments waiting for being pushed even though no more rows will be added to them
// in the future.
// If those segments are not pushed here, the remaining available space in appenderator will be kept
// small which could lead to smaller segments.
final SegmentsAndCommitMetadata pushed = driver.pushAllAndClear(pushTimeout);
LOG.debugSegments(pushed.getSegments(), "Pushed segments");
}
}
} else {
throw new ISE("Failed to add a row with timestamp[%s]", inputRow.getTimestamp());
}
}
final SegmentsAndCommitMetadata pushed = driver.pushAllAndClear(pushTimeout);
LOG.debugSegments(pushed.getSegments(), "Pushed segments");
return pushed;
}
}
use of org.apache.druid.segment.realtime.appenderator.SegmentsAndCommitMetadata in project druid by druid-io.
the class SeekableStreamIndexTaskRunner method runInternal.
private TaskStatus runInternal(TaskToolbox toolbox) throws Exception {
startTime = DateTimes.nowUtc();
status = Status.STARTING;
setToolbox(toolbox);
authorizerMapper = toolbox.getAuthorizerMapper();
rowIngestionMeters = toolbox.getRowIngestionMetersFactory().createRowIngestionMeters();
parseExceptionHandler = new ParseExceptionHandler(rowIngestionMeters, tuningConfig.isLogParseExceptions(), tuningConfig.getMaxParseExceptions(), tuningConfig.getMaxSavedParseExceptions());
// Now we can initialize StreamChunkReader with the given toolbox.
final StreamChunkParser parser = new StreamChunkParser<RecordType>(this.parser, inputFormat, inputRowSchema, task.getDataSchema().getTransformSpec(), toolbox.getIndexingTmpDir(), row -> row != null && task.withinMinMaxRecordTime(row), rowIngestionMeters, parseExceptionHandler);
initializeSequences();
log.debug("Found chat handler of class[%s]", toolbox.getChatHandlerProvider().getClass().getName());
toolbox.getChatHandlerProvider().register(task.getId(), this, false);
runThread = Thread.currentThread();
// Set up FireDepartmentMetrics
final FireDepartment fireDepartmentForMetrics = new FireDepartment(task.getDataSchema(), new RealtimeIOConfig(null, null), null);
this.fireDepartmentMetrics = fireDepartmentForMetrics.getMetrics();
toolbox.addMonitor(TaskRealtimeMetricsMonitorBuilder.build(task, fireDepartmentForMetrics, rowIngestionMeters));
final String lookupTier = task.getContextValue(RealtimeIndexTask.CTX_KEY_LOOKUP_TIER);
final LookupNodeService lookupNodeService = lookupTier == null ? toolbox.getLookupNodeService() : new LookupNodeService(lookupTier);
final DiscoveryDruidNode discoveryDruidNode = new DiscoveryDruidNode(toolbox.getDruidNode(), NodeRole.PEON, ImmutableMap.of(toolbox.getDataNodeService().getName(), toolbox.getDataNodeService(), lookupNodeService.getName(), lookupNodeService));
Throwable caughtExceptionOuter = null;
// milliseconds waited for created segments to be handed off
long handoffWaitMs = 0L;
try (final RecordSupplier<PartitionIdType, SequenceOffsetType, RecordType> recordSupplier = task.newTaskRecordSupplier()) {
if (toolbox.getAppenderatorsManager().shouldTaskMakeNodeAnnouncements()) {
toolbox.getDataSegmentServerAnnouncer().announce();
toolbox.getDruidNodeAnnouncer().announce(discoveryDruidNode);
}
appenderator = task.newAppenderator(toolbox, fireDepartmentMetrics, rowIngestionMeters, parseExceptionHandler);
driver = task.newDriver(appenderator, toolbox, fireDepartmentMetrics);
// Start up, set up initial sequences.
final Object restoredMetadata = driver.startJob(segmentId -> {
try {
if (lockGranularityToUse == LockGranularity.SEGMENT) {
return toolbox.getTaskActionClient().submit(new SegmentLockAcquireAction(TaskLockType.EXCLUSIVE, segmentId.getInterval(), segmentId.getVersion(), segmentId.getShardSpec().getPartitionNum(), 1000L)).isOk();
} else {
final TaskLock lock = toolbox.getTaskActionClient().submit(new TimeChunkLockAcquireAction(TaskLockType.EXCLUSIVE, segmentId.getInterval(), 1000L));
if (lock == null) {
return false;
}
if (lock.isRevoked()) {
throw new ISE(StringUtils.format("Lock for interval [%s] was revoked.", segmentId.getInterval()));
}
return true;
}
} catch (IOException e) {
throw new RuntimeException(e);
}
});
if (restoredMetadata == null) {
// no persist has happened so far
// so either this is a brand new task or replacement of a failed task
Preconditions.checkState(sequences.get(0).startOffsets.entrySet().stream().allMatch(partitionOffsetEntry -> createSequenceNumber(partitionOffsetEntry.getValue()).compareTo(createSequenceNumber(ioConfig.getStartSequenceNumbers().getPartitionSequenceNumberMap().get(partitionOffsetEntry.getKey()))) >= 0), "Sequence sequences are not compatible with start sequences of task");
currOffsets.putAll(sequences.get(0).startOffsets);
} else {
@SuppressWarnings("unchecked") final Map<String, Object> restoredMetadataMap = (Map) restoredMetadata;
final SeekableStreamEndSequenceNumbers<PartitionIdType, SequenceOffsetType> restoredNextPartitions = deserializePartitionsFromMetadata(toolbox.getJsonMapper(), restoredMetadataMap.get(METADATA_NEXT_PARTITIONS));
currOffsets.putAll(restoredNextPartitions.getPartitionSequenceNumberMap());
// Sanity checks.
if (!restoredNextPartitions.getStream().equals(ioConfig.getStartSequenceNumbers().getStream())) {
throw new ISE("Restored stream[%s] but expected stream[%s]", restoredNextPartitions.getStream(), ioConfig.getStartSequenceNumbers().getStream());
}
if (!currOffsets.keySet().equals(ioConfig.getStartSequenceNumbers().getPartitionSequenceNumberMap().keySet())) {
throw new ISE("Restored partitions[%s] but expected partitions[%s]", currOffsets.keySet(), ioConfig.getStartSequenceNumbers().getPartitionSequenceNumberMap().keySet());
}
// which is super rare
if (sequences.size() == 0 || getLastSequenceMetadata().isCheckpointed()) {
this.endOffsets.putAll(sequences.size() == 0 ? currOffsets : getLastSequenceMetadata().getEndOffsets());
}
}
log.info("Initialized sequences: %s", sequences.stream().map(SequenceMetadata::toString).collect(Collectors.joining(", ")));
// Filter out partitions with END_OF_SHARD markers since these partitions have already been fully read. This
// should have been done by the supervisor already so this is defensive.
int numPreFilterPartitions = currOffsets.size();
if (currOffsets.entrySet().removeIf(x -> isEndOfShard(x.getValue()))) {
log.info("Removed [%d] partitions from assignment which have already been closed.", numPreFilterPartitions - currOffsets.size());
}
// When end offsets are exclusive, we never skip the start record.
if (!isEndOffsetExclusive()) {
for (Map.Entry<PartitionIdType, SequenceOffsetType> entry : currOffsets.entrySet()) {
final boolean isAtStart = entry.getValue().equals(ioConfig.getStartSequenceNumbers().getPartitionSequenceNumberMap().get(entry.getKey()));
if (!isAtStart || ioConfig.getStartSequenceNumbers().getExclusivePartitions().contains(entry.getKey())) {
lastReadOffsets.put(entry.getKey(), entry.getValue());
}
}
}
// Set up committer.
final Supplier<Committer> committerSupplier = () -> {
final Map<PartitionIdType, SequenceOffsetType> snapshot = ImmutableMap.copyOf(currOffsets);
lastPersistedOffsets.clear();
lastPersistedOffsets.putAll(snapshot);
return new Committer() {
@Override
public Object getMetadata() {
return ImmutableMap.of(METADATA_NEXT_PARTITIONS, new SeekableStreamEndSequenceNumbers<>(stream, snapshot));
}
@Override
public void run() {
// Do nothing.
}
};
};
// restart publishing of sequences (if any)
maybePersistAndPublishSequences(committerSupplier);
Set<StreamPartition<PartitionIdType>> assignment = assignPartitions(recordSupplier);
possiblyResetDataSourceMetadata(toolbox, recordSupplier, assignment);
seekToStartingSequence(recordSupplier, assignment);
ingestionState = IngestionState.BUILD_SEGMENTS;
// Main loop.
// Could eventually support leader/follower mode (for keeping replicas more in sync)
boolean stillReading = !assignment.isEmpty();
status = Status.READING;
Throwable caughtExceptionInner = null;
try {
while (stillReading) {
if (possiblyPause()) {
// The partition assignments may have changed while paused by a call to setEndOffsets() so reassign
// partitions upon resuming. Don't call "seekToStartingSequence" after "assignPartitions", because there's
// no need to re-seek here. All we're going to be doing is dropping partitions.
assignment = assignPartitions(recordSupplier);
possiblyResetDataSourceMetadata(toolbox, recordSupplier, assignment);
if (assignment.isEmpty()) {
log.debug("All partitions have been fully read.");
publishOnStop.set(true);
stopRequested.set(true);
}
}
// if stop is requested or task's end sequence is set by call to setEndOffsets method with finish set to true
if (stopRequested.get() || sequences.size() == 0 || getLastSequenceMetadata().isCheckpointed()) {
status = Status.PUBLISHING;
}
if (stopRequested.get()) {
break;
}
if (backgroundThreadException != null) {
throw new RuntimeException(backgroundThreadException);
}
checkPublishAndHandoffFailure();
maybePersistAndPublishSequences(committerSupplier);
// calling getRecord() ensures that exceptions specific to kafka/kinesis like OffsetOutOfRangeException
// are handled in the subclasses.
List<OrderedPartitionableRecord<PartitionIdType, SequenceOffsetType, RecordType>> records = getRecords(recordSupplier, toolbox);
// note: getRecords() also updates assignment
stillReading = !assignment.isEmpty();
SequenceMetadata<PartitionIdType, SequenceOffsetType> sequenceToCheckpoint = null;
for (OrderedPartitionableRecord<PartitionIdType, SequenceOffsetType, RecordType> record : records) {
final boolean shouldProcess = verifyRecordInRange(record.getPartitionId(), record.getSequenceNumber());
log.trace("Got stream[%s] partition[%s] sequenceNumber[%s], shouldProcess[%s].", record.getStream(), record.getPartitionId(), record.getSequenceNumber(), shouldProcess);
if (shouldProcess) {
final List<InputRow> rows = parser.parse(record.getData(), isEndOfShard(record.getSequenceNumber()));
boolean isPersistRequired = false;
final SequenceMetadata<PartitionIdType, SequenceOffsetType> sequenceToUse = sequences.stream().filter(sequenceMetadata -> sequenceMetadata.canHandle(this, record)).findFirst().orElse(null);
if (sequenceToUse == null) {
throw new ISE("Cannot find any valid sequence for record with partition [%s] and sequenceNumber [%s]. Current sequences: %s", record.getPartitionId(), record.getSequenceNumber(), sequences);
}
for (InputRow row : rows) {
final AppenderatorDriverAddResult addResult = driver.add(row, sequenceToUse.getSequenceName(), committerSupplier, true, // of rows are indexed
false);
if (addResult.isOk()) {
// If the number of rows in the segment exceeds the threshold after adding a row,
// move the segment out from the active segments of BaseAppenderatorDriver to make a new segment.
final boolean isPushRequired = addResult.isPushRequired(tuningConfig.getPartitionsSpec().getMaxRowsPerSegment(), tuningConfig.getPartitionsSpec().getMaxTotalRowsOr(DynamicPartitionsSpec.DEFAULT_MAX_TOTAL_ROWS));
if (isPushRequired && !sequenceToUse.isCheckpointed()) {
sequenceToCheckpoint = sequenceToUse;
}
isPersistRequired |= addResult.isPersistRequired();
} else {
// If we allow continuing, then consider blacklisting the interval for a while to avoid constant checks.
throw new ISE("Could not allocate segment for row with timestamp[%s]", row.getTimestamp());
}
}
if (isPersistRequired) {
Futures.addCallback(driver.persistAsync(committerSupplier.get()), new FutureCallback<Object>() {
@Override
public void onSuccess(@Nullable Object result) {
log.debug("Persist completed with metadata: %s", result);
}
@Override
public void onFailure(Throwable t) {
log.error("Persist failed, dying");
backgroundThreadException = t;
}
});
}
// in kafka, we can easily get the next offset by adding 1, but for kinesis, there's no way
// to get the next sequence number without having to make an expensive api call. So the behavior
// here for kafka is to +1 while for kinesis we simply save the current sequence number
lastReadOffsets.put(record.getPartitionId(), record.getSequenceNumber());
currOffsets.put(record.getPartitionId(), getNextStartOffset(record.getSequenceNumber()));
}
// Use record.getSequenceNumber() in the moreToRead check, since currOffsets might not have been
// updated if we were skipping records for being beyond the end.
final boolean moreToReadAfterThisRecord = isMoreToReadAfterReadingRecord(record.getSequenceNumber(), endOffsets.get(record.getPartitionId()));
if (!moreToReadAfterThisRecord && assignment.remove(record.getStreamPartition())) {
log.info("Finished reading stream[%s], partition[%s].", record.getStream(), record.getPartitionId());
recordSupplier.assign(assignment);
stillReading = !assignment.isEmpty();
}
}
if (!stillReading) {
// We let the fireDepartmentMetrics know that all messages have been read. This way, some metrics such as
// high message gap need not be reported
fireDepartmentMetrics.markProcessingDone();
}
if (System.currentTimeMillis() > nextCheckpointTime) {
sequenceToCheckpoint = getLastSequenceMetadata();
}
if (sequenceToCheckpoint != null && stillReading) {
Preconditions.checkArgument(getLastSequenceMetadata().getSequenceName().equals(sequenceToCheckpoint.getSequenceName()), "Cannot checkpoint a sequence [%s] which is not the latest one, sequences %s", sequenceToCheckpoint, sequences);
requestPause();
final CheckPointDataSourceMetadataAction checkpointAction = new CheckPointDataSourceMetadataAction(task.getDataSource(), ioConfig.getTaskGroupId(), null, createDataSourceMetadata(new SeekableStreamStartSequenceNumbers<>(stream, sequenceToCheckpoint.getStartOffsets(), sequenceToCheckpoint.getExclusiveStartPartitions())));
if (!toolbox.getTaskActionClient().submit(checkpointAction)) {
throw new ISE("Checkpoint request with sequences [%s] failed, dying", currOffsets);
}
}
}
ingestionState = IngestionState.COMPLETED;
} catch (Exception e) {
// (1) catch all exceptions while reading from kafka
caughtExceptionInner = e;
log.error(e, "Encountered exception in run() before persisting.");
throw e;
} finally {
try {
// persist pending data
driver.persist(committerSupplier.get());
} catch (Exception e) {
if (caughtExceptionInner != null) {
caughtExceptionInner.addSuppressed(e);
} else {
throw e;
}
}
}
synchronized (statusLock) {
if (stopRequested.get() && !publishOnStop.get()) {
throw new InterruptedException("Stopping without publishing");
}
status = Status.PUBLISHING;
}
// We need to copy sequences here, because the success callback in publishAndRegisterHandoff removes items from
// the sequence list. If a publish finishes before we finish iterating through the sequence list, we can
// end up skipping some sequences.
List<SequenceMetadata<PartitionIdType, SequenceOffsetType>> sequencesSnapshot = new ArrayList<>(sequences);
for (int i = 0; i < sequencesSnapshot.size(); i++) {
final SequenceMetadata<PartitionIdType, SequenceOffsetType> sequenceMetadata = sequencesSnapshot.get(i);
if (!publishingSequences.contains(sequenceMetadata.getSequenceName())) {
final boolean isLast = i == (sequencesSnapshot.size() - 1);
if (isLast) {
// Shorten endOffsets of the last sequence to match currOffsets.
sequenceMetadata.setEndOffsets(currOffsets);
}
// Update assignments of the sequence, which should clear them. (This will be checked later, when the
// Committer is built.)
sequenceMetadata.updateAssignments(currOffsets, this::isMoreToReadAfterReadingRecord);
publishingSequences.add(sequenceMetadata.getSequenceName());
// persist already done in finally, so directly add to publishQueue
publishAndRegisterHandoff(sequenceMetadata);
}
}
if (backgroundThreadException != null) {
throw new RuntimeException(backgroundThreadException);
}
// Wait for publish futures to complete.
Futures.allAsList(publishWaitList).get();
// Wait for handoff futures to complete.
// Note that every publishing task (created by calling AppenderatorDriver.publish()) has a corresponding
// handoffFuture. handoffFuture can throw an exception if 1) the corresponding publishFuture failed or 2) it
// failed to persist sequences. It might also return null if handoff failed, but was recoverable.
// See publishAndRegisterHandoff() for details.
List<SegmentsAndCommitMetadata> handedOffList = Collections.emptyList();
if (tuningConfig.getHandoffConditionTimeout() == 0) {
handedOffList = Futures.allAsList(handOffWaitList).get();
} else {
final long start = System.nanoTime();
try {
handedOffList = Futures.allAsList(handOffWaitList).get(tuningConfig.getHandoffConditionTimeout(), TimeUnit.MILLISECONDS);
} catch (TimeoutException e) {
// Handoff timeout is not an indexing failure, but coordination failure. We simply ignore timeout exception
// here.
log.makeAlert("Timeout waiting for handoff").addData("taskId", task.getId()).addData("handoffConditionTimeout", tuningConfig.getHandoffConditionTimeout()).emit();
} finally {
handoffWaitMs = TimeUnit.NANOSECONDS.toMillis(System.nanoTime() - start);
}
}
for (SegmentsAndCommitMetadata handedOff : handedOffList) {
log.info("Handoff complete for segments: %s", String.join(", ", Lists.transform(handedOff.getSegments(), DataSegment::toString)));
}
appenderator.close();
} catch (InterruptedException | RejectedExecutionException e) {
// (2) catch InterruptedException and RejectedExecutionException thrown for the whole ingestion steps including
// the final publishing.
caughtExceptionOuter = e;
try {
Futures.allAsList(publishWaitList).cancel(true);
Futures.allAsList(handOffWaitList).cancel(true);
if (appenderator != null) {
appenderator.closeNow();
}
} catch (Exception e2) {
e.addSuppressed(e2);
}
// handle the InterruptedException that gets wrapped in a RejectedExecutionException
if (e instanceof RejectedExecutionException && (e.getCause() == null || !(e.getCause() instanceof InterruptedException))) {
throw e;
}
// if we were interrupted because we were asked to stop, handle the exception and return success, else rethrow
if (!stopRequested.get()) {
Thread.currentThread().interrupt();
throw e;
}
} catch (Exception e) {
// (3) catch all other exceptions thrown for the whole ingestion steps including the final publishing.
caughtExceptionOuter = e;
try {
Futures.allAsList(publishWaitList).cancel(true);
Futures.allAsList(handOffWaitList).cancel(true);
if (appenderator != null) {
appenderator.closeNow();
}
} catch (Exception e2) {
e.addSuppressed(e2);
}
throw e;
} finally {
try {
if (driver != null) {
driver.close();
}
toolbox.getChatHandlerProvider().unregister(task.getId());
if (toolbox.getAppenderatorsManager().shouldTaskMakeNodeAnnouncements()) {
toolbox.getDruidNodeAnnouncer().unannounce(discoveryDruidNode);
toolbox.getDataSegmentServerAnnouncer().unannounce();
}
} catch (Throwable e) {
if (caughtExceptionOuter != null) {
caughtExceptionOuter.addSuppressed(e);
} else {
throw e;
}
}
}
toolbox.getTaskReportFileWriter().write(task.getId(), getTaskCompletionReports(null, handoffWaitMs));
return TaskStatus.success(task.getId());
}
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