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Example 6 with RealtimeIOConfig

use of org.apache.druid.segment.indexing.RealtimeIOConfig in project druid by druid-io.

the class TaskLifecycleTest method newRealtimeIndexTask.

private RealtimeIndexTask newRealtimeIndexTask() {
    String taskId = StringUtils.format("rt_task_%s", System.currentTimeMillis());
    DataSchema dataSchema = new DataSchema("test_ds", TestHelper.makeJsonMapper().convertValue(new MapInputRowParser(new TimeAndDimsParseSpec(new TimestampSpec(null, null, null), DimensionsSpec.EMPTY)), JacksonUtils.TYPE_REFERENCE_MAP_STRING_OBJECT), new AggregatorFactory[] { new LongSumAggregatorFactory("count", "rows") }, new UniformGranularitySpec(Granularities.DAY, Granularities.NONE, null), null, mapper);
    RealtimeIOConfig realtimeIOConfig = new RealtimeIOConfig(new MockFirehoseFactory(), null);
    RealtimeTuningConfig realtimeTuningConfig = new RealtimeTuningConfig(null, 1000, null, null, new Period("P1Y"), // default window period of 10 minutes
    null, // base persist dir ignored by Realtime Index task
    null, null, null, null, null, null, null, 0, 0, null, null, null, null, null);
    FireDepartment fireDepartment = new FireDepartment(dataSchema, realtimeIOConfig, realtimeTuningConfig);
    return new RealtimeIndexTask(taskId, new TaskResource(taskId, 1), fireDepartment, null);
}
Also used : RealtimeIOConfig(org.apache.druid.segment.indexing.RealtimeIOConfig) RealtimeIndexTask(org.apache.druid.indexing.common.task.RealtimeIndexTask) TaskResource(org.apache.druid.indexing.common.task.TaskResource) MapInputRowParser(org.apache.druid.data.input.impl.MapInputRowParser) LongSumAggregatorFactory(org.apache.druid.query.aggregation.LongSumAggregatorFactory) Period(org.joda.time.Period) RealtimeTuningConfig(org.apache.druid.segment.indexing.RealtimeTuningConfig) DataSchema(org.apache.druid.segment.indexing.DataSchema) TimeAndDimsParseSpec(org.apache.druid.data.input.impl.TimeAndDimsParseSpec) UniformGranularitySpec(org.apache.druid.segment.indexing.granularity.UniformGranularitySpec) FireDepartment(org.apache.druid.segment.realtime.FireDepartment) TimestampSpec(org.apache.druid.data.input.impl.TimestampSpec)

Example 7 with RealtimeIOConfig

use of org.apache.druid.segment.indexing.RealtimeIOConfig 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();
        }
    }
}
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Example 8 with RealtimeIOConfig

use of org.apache.druid.segment.indexing.RealtimeIOConfig 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();
        }
    }
}
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Example 9 with RealtimeIOConfig

use of org.apache.druid.segment.indexing.RealtimeIOConfig in project druid by druid-io.

the class RealtimeIndexTaskTest method makeRealtimeTask.

private RealtimeIndexTask makeRealtimeTask(final String taskId, final TransformSpec transformSpec, final boolean reportParseExceptions, final long handoffTimeout) {
    ObjectMapper objectMapper = new DefaultObjectMapper();
    DataSchema dataSchema = new DataSchema("test_ds", TestHelper.makeJsonMapper().convertValue(new MapInputRowParser(new TimeAndDimsParseSpec(new TimestampSpec("t", "auto", null), new DimensionsSpec(DimensionsSpec.getDefaultSchemas(ImmutableList.of("dim1", "dim2", "dim1t"))))), JacksonUtils.TYPE_REFERENCE_MAP_STRING_OBJECT), new AggregatorFactory[] { new CountAggregatorFactory("rows"), new LongSumAggregatorFactory("met1", "met1") }, new UniformGranularitySpec(Granularities.DAY, Granularities.NONE, null), transformSpec, objectMapper);
    RealtimeIOConfig realtimeIOConfig = new RealtimeIOConfig(new TestFirehose.TestFirehoseFactory(), null);
    RealtimeTuningConfig realtimeTuningConfig = new RealtimeTuningConfig(null, 1000, null, null, new Period("P1Y"), new Period("PT10M"), null, null, new ServerTimeRejectionPolicyFactory(), null, null, null, null, 0, 0, reportParseExceptions, handoffTimeout, null, null, null);
    return new RealtimeIndexTask(taskId, null, new FireDepartment(dataSchema, realtimeIOConfig, realtimeTuningConfig), null) {

        @Override
        protected boolean isFirehoseDrainableByClosing(FirehoseFactory firehoseFactory) {
            return true;
        }
    };
}
Also used : RealtimeIOConfig(org.apache.druid.segment.indexing.RealtimeIOConfig) MapInputRowParser(org.apache.druid.data.input.impl.MapInputRowParser) FirehoseFactory(org.apache.druid.data.input.FirehoseFactory) LongSumAggregatorFactory(org.apache.druid.query.aggregation.LongSumAggregatorFactory) Period(org.joda.time.Period) RealtimeTuningConfig(org.apache.druid.segment.indexing.RealtimeTuningConfig) TestFirehose(org.apache.druid.indexing.common.TestFirehose) DataSchema(org.apache.druid.segment.indexing.DataSchema) TimeAndDimsParseSpec(org.apache.druid.data.input.impl.TimeAndDimsParseSpec) UniformGranularitySpec(org.apache.druid.segment.indexing.granularity.UniformGranularitySpec) FireDepartment(org.apache.druid.segment.realtime.FireDepartment) ServerTimeRejectionPolicyFactory(org.apache.druid.segment.realtime.plumber.ServerTimeRejectionPolicyFactory) CountAggregatorFactory(org.apache.druid.query.aggregation.CountAggregatorFactory) TimestampSpec(org.apache.druid.data.input.impl.TimestampSpec) DimensionsSpec(org.apache.druid.data.input.impl.DimensionsSpec) DefaultObjectMapper(org.apache.druid.jackson.DefaultObjectMapper) DefaultObjectMapper(org.apache.druid.jackson.DefaultObjectMapper) ObjectMapper(com.fasterxml.jackson.databind.ObjectMapper)

Example 10 with RealtimeIOConfig

use of org.apache.druid.segment.indexing.RealtimeIOConfig in project druid by druid-io.

the class KinesisSupervisorTest method testDontKillTasksWithMismatchedType.

@Test
public void testDontKillTasksWithMismatchedType() throws Exception {
    supervisor = getTestableSupervisor(2, 1, true, "PT1H", null, null);
    supervisorRecordSupplier.assign(EasyMock.anyObject());
    EasyMock.expectLastCall().anyTimes();
    EasyMock.expect(supervisorRecordSupplier.getPartitionIds(STREAM)).andReturn(ImmutableSet.of(SHARD_ID1, SHARD_ID0)).anyTimes();
    EasyMock.expect(supervisorRecordSupplier.getAssignment()).andReturn(ImmutableSet.of(SHARD1_PARTITION, SHARD0_PARTITION)).anyTimes();
    supervisorRecordSupplier.seekToLatest(EasyMock.anyObject());
    EasyMock.expectLastCall().anyTimes();
    EasyMock.expect(supervisorRecordSupplier.getEarliestSequenceNumber(EasyMock.anyObject())).andReturn("0").anyTimes();
    EasyMock.expect(supervisorRecordSupplier.getLatestSequenceNumber(EasyMock.anyObject())).andReturn("100").anyTimes();
    supervisorRecordSupplier.seek(EasyMock.anyObject(), EasyMock.anyString());
    EasyMock.expectLastCall().anyTimes();
    // non KinesisIndexTask (don't kill)
    Task id2 = new RealtimeIndexTask("id2", null, new FireDepartment(dataSchema, new RealtimeIOConfig(null, null), null), null);
    List<Task> existingTasks = ImmutableList.of(id2);
    EasyMock.expect(taskMaster.getTaskQueue()).andReturn(Optional.of(taskQueue)).anyTimes();
    EasyMock.expect(taskMaster.getTaskRunner()).andReturn(Optional.of(taskRunner)).anyTimes();
    EasyMock.expect(taskRunner.getRunningTasks()).andReturn(Collections.emptyList()).anyTimes();
    EasyMock.expect(taskStorage.getActiveTasksByDatasource(DATASOURCE)).andReturn(existingTasks).anyTimes();
    EasyMock.expect(taskClient.getStatusAsync(EasyMock.anyString())).andReturn(Futures.immediateFuture(SeekableStreamIndexTaskRunner.Status.NOT_STARTED)).anyTimes();
    EasyMock.expect(taskClient.getStartTimeAsync(EasyMock.anyString())).andReturn(Futures.immediateFuture(DateTimes.nowUtc())).anyTimes();
    EasyMock.expect(indexerMetadataStorageCoordinator.retrieveDataSourceMetadata(DATASOURCE)).andReturn(new KinesisDataSourceMetadata(null)).anyTimes();
    taskRunner.registerListener(EasyMock.anyObject(TaskRunnerListener.class), EasyMock.anyObject(Executor.class));
    EasyMock.expect(taskQueue.add(EasyMock.anyObject(Task.class))).andReturn(true).times(2);
    replayAll();
    supervisor.start();
    supervisor.runInternal();
    verifyAll();
}
Also used : FireDepartment(org.apache.druid.segment.realtime.FireDepartment) TaskRunnerListener(org.apache.druid.indexing.overlord.TaskRunnerListener) Task(org.apache.druid.indexing.common.task.Task) RealtimeIndexTask(org.apache.druid.indexing.common.task.RealtimeIndexTask) KinesisIndexTask(org.apache.druid.indexing.kinesis.KinesisIndexTask) RealtimeIOConfig(org.apache.druid.segment.indexing.RealtimeIOConfig) RealtimeIndexTask(org.apache.druid.indexing.common.task.RealtimeIndexTask) Executor(java.util.concurrent.Executor) KinesisDataSourceMetadata(org.apache.druid.indexing.kinesis.KinesisDataSourceMetadata) Test(org.junit.Test)

Aggregations

RealtimeIOConfig (org.apache.druid.segment.indexing.RealtimeIOConfig)15 FireDepartment (org.apache.druid.segment.realtime.FireDepartment)13 DataSchema (org.apache.druid.segment.indexing.DataSchema)12 File (java.io.File)6 IOException (java.io.IOException)6 RealtimeIndexTask (org.apache.druid.indexing.common.task.RealtimeIndexTask)6 Test (org.junit.Test)6 ObjectMapper (com.fasterxml.jackson.databind.ObjectMapper)5 ExecutionException (java.util.concurrent.ExecutionException)5 TimeoutException (java.util.concurrent.TimeoutException)5 FirehoseFactory (org.apache.druid.data.input.FirehoseFactory)5 InputRow (org.apache.druid.data.input.InputRow)4 TaskStatus (org.apache.druid.indexer.TaskStatus)4 DynamicPartitionsSpec (org.apache.druid.indexer.partitions.DynamicPartitionsSpec)4 ISE (org.apache.druid.java.util.common.ISE)4 UniformGranularitySpec (org.apache.druid.segment.indexing.granularity.UniformGranularitySpec)4 FireDepartmentMetrics (org.apache.druid.segment.realtime.FireDepartmentMetrics)4 Appenderator (org.apache.druid.segment.realtime.appenderator.Appenderator)4 SegmentsAndCommitMetadata (org.apache.druid.segment.realtime.appenderator.SegmentsAndCommitMetadata)4 Preconditions (com.google.common.base.Preconditions)3