Examples with TimeseriesQueryRunnerFactory org.apache.druid.query.timeseries.TimeseriesQueryRunnerFactory used on opensource projects

Example 11 with TimeseriesQueryRunnerFactory

use of org.apache.druid.query.timeseries.TimeseriesQueryRunnerFactory in project druid by druid-io.

the class AppenderatorDriverRealtimeIndexTaskTest method makeToolboxFactory.

private void makeToolboxFactory(final File directory) {
    taskStorage = new HeapMemoryTaskStorage(new TaskStorageConfig(null));
    publishedSegments = new CopyOnWriteArrayList<>();
    ObjectMapper mapper = new DefaultObjectMapper();
    mapper.registerSubtypes(LinearShardSpec.class);
    mapper.registerSubtypes(NumberedShardSpec.class);
    IndexerSQLMetadataStorageCoordinator mdc = new IndexerSQLMetadataStorageCoordinator(mapper, derbyConnectorRule.metadataTablesConfigSupplier().get(), derbyConnectorRule.getConnector()) {

        @Override
        public Set<DataSegment> announceHistoricalSegments(Set<DataSegment> segments) throws IOException {
            Set<DataSegment> result = super.announceHistoricalSegments(segments);
            Assert.assertFalse("Segment latch not initialized, did you forget to call expectPublishSegments?", segmentLatch == null);
            publishedSegments.addAll(result);
            segments.forEach(s -> segmentLatch.countDown());
            return result;
        }

        @Override
        public SegmentPublishResult announceHistoricalSegments(Set<DataSegment> segments, Set<DataSegment> segmentsToDrop, DataSourceMetadata startMetadata, DataSourceMetadata endMetadata) throws IOException {
            SegmentPublishResult result = super.announceHistoricalSegments(segments, segmentsToDrop, startMetadata, endMetadata);
            Assert.assertFalse("Segment latch not initialized, did you forget to call expectPublishSegments?", segmentLatch == null);
            publishedSegments.addAll(result.getSegments());
            result.getSegments().forEach(s -> segmentLatch.countDown());
            return result;
        }
    };
    taskLockbox = new TaskLockbox(taskStorage, mdc);
    final TaskConfig taskConfig = new TaskConfig(directory.getPath(), null, null, 50000, null, true, null, null, null, false, false, TaskConfig.BATCH_PROCESSING_MODE_DEFAULT.name());
    final TaskActionToolbox taskActionToolbox = new TaskActionToolbox(taskLockbox, taskStorage, mdc, EMITTER, EasyMock.createMock(SupervisorManager.class));
    final TaskActionClientFactory taskActionClientFactory = new LocalTaskActionClientFactory(taskStorage, taskActionToolbox, new TaskAuditLogConfig(false));
    final QueryRunnerFactoryConglomerate conglomerate = new DefaultQueryRunnerFactoryConglomerate(ImmutableMap.of(TimeseriesQuery.class, new TimeseriesQueryRunnerFactory(new TimeseriesQueryQueryToolChest(), new TimeseriesQueryEngine(), (query, future) -> {
    // do nothing
    })));
    handOffCallbacks = new ConcurrentHashMap<>();
    final SegmentHandoffNotifierFactory handoffNotifierFactory = dataSource -> new SegmentHandoffNotifier() {

        @Override
        public boolean registerSegmentHandoffCallback(SegmentDescriptor descriptor, Executor exec, Runnable handOffRunnable) {
            handOffCallbacks.put(descriptor, new Pair<>(exec, handOffRunnable));
            handoffLatch.countDown();
            return true;
        }

        @Override
        public void start() {
        // Noop
        }

        @Override
        public void close() {
        // Noop
        }
    };
    final TestUtils testUtils = new TestUtils();
    taskToolboxFactory = new TaskToolboxFactory(taskConfig, new DruidNode("druid/middlemanager", "localhost", false, 8091, null, true, false), taskActionClientFactory, EMITTER, new TestDataSegmentPusher(), new TestDataSegmentKiller(), // DataSegmentMover
    null, // DataSegmentArchiver
    null, new TestDataSegmentAnnouncer(), EasyMock.createNiceMock(DataSegmentServerAnnouncer.class), handoffNotifierFactory, () -> conglomerate, // queryExecutorService
    DirectQueryProcessingPool.INSTANCE, NoopJoinableFactory.INSTANCE, () -> EasyMock.createMock(MonitorScheduler.class), new SegmentCacheManagerFactory(testUtils.getTestObjectMapper()), testUtils.getTestObjectMapper(), testUtils.getTestIndexIO(), MapCache.create(1024), new CacheConfig(), new CachePopulatorStats(), testUtils.getTestIndexMergerV9(), EasyMock.createNiceMock(DruidNodeAnnouncer.class), EasyMock.createNiceMock(DruidNode.class), new LookupNodeService("tier"), new DataNodeService("tier", 1000, ServerType.INDEXER_EXECUTOR, 0), new SingleFileTaskReportFileWriter(reportsFile), null, AuthTestUtils.TEST_AUTHORIZER_MAPPER, new NoopChatHandlerProvider(), testUtils.getRowIngestionMetersFactory(), new TestAppenderatorsManager(), new NoopIndexingServiceClient(), null, null, null);
}

Example 12 with TimeseriesQueryRunnerFactory

use of org.apache.druid.query.timeseries.TimeseriesQueryRunnerFactory in project druid by druid-io.

the class CachingClusteredClientBenchmark method setup.

@Setup(Level.Trial)
public void setup() {
    final String schemaName = "basic";
    parallelCombine = parallelism > 0;
    GeneratorSchemaInfo schemaInfo = GeneratorBasicSchemas.SCHEMA_MAP.get(schemaName);
    Map<DataSegment, QueryableIndex> queryableIndexes = Maps.newHashMapWithExpectedSize(numServers);
    for (int i = 0; i < numServers; i++) {
        final DataSegment dataSegment = DataSegment.builder().dataSource(DATA_SOURCE).interval(schemaInfo.getDataInterval()).version("1").shardSpec(new LinearShardSpec(i)).size(0).build();
        final SegmentGenerator segmentGenerator = closer.register(new SegmentGenerator());
        LOG.info("Starting benchmark setup using cacheDir[%s], rows[%,d].", segmentGenerator.getCacheDir(), rowsPerSegment);
        final QueryableIndex index = segmentGenerator.generate(dataSegment, schemaInfo, Granularities.NONE, rowsPerSegment);
        queryableIndexes.put(dataSegment, index);
    }
    final DruidProcessingConfig processingConfig = new DruidProcessingConfig() {

        @Override
        public String getFormatString() {
            return null;
        }

        @Override
        public int intermediateComputeSizeBytes() {
            return PROCESSING_BUFFER_SIZE;
        }

        @Override
        public int getNumMergeBuffers() {
            return 1;
        }

        @Override
        public int getNumThreads() {
            return numProcessingThreads;
        }

        @Override
        public boolean useParallelMergePool() {
            return true;
        }
    };
    conglomerate = new DefaultQueryRunnerFactoryConglomerate(ImmutableMap.<Class<? extends Query>, QueryRunnerFactory>builder().put(TimeseriesQuery.class, new TimeseriesQueryRunnerFactory(new TimeseriesQueryQueryToolChest(), new TimeseriesQueryEngine(), QueryRunnerTestHelper.NOOP_QUERYWATCHER)).put(TopNQuery.class, new TopNQueryRunnerFactory(new StupidPool<>("TopNQueryRunnerFactory-bufferPool", () -> ByteBuffer.allocate(PROCESSING_BUFFER_SIZE)), new TopNQueryQueryToolChest(new TopNQueryConfig()), QueryRunnerTestHelper.NOOP_QUERYWATCHER)).put(GroupByQuery.class, makeGroupByQueryRunnerFactory(GroupByQueryRunnerTest.DEFAULT_MAPPER, new GroupByQueryConfig() {

        @Override
        public String getDefaultStrategy() {
            return GroupByStrategySelector.STRATEGY_V2;
        }
    }, processingConfig)).build());
    toolChestWarehouse = new QueryToolChestWarehouse() {

        @Override
        public <T, QueryType extends Query<T>> QueryToolChest<T, QueryType> getToolChest(final QueryType query) {
            return conglomerate.findFactory(query).getToolchest();
        }
    };
    SimpleServerView serverView = new SimpleServerView();
    int serverSuffx = 1;
    for (Entry<DataSegment, QueryableIndex> entry : queryableIndexes.entrySet()) {
        serverView.addServer(createServer(serverSuffx++), entry.getKey(), entry.getValue());
    }
    processingPool = Execs.multiThreaded(processingConfig.getNumThreads(), "caching-clustered-client-benchmark");
    forkJoinPool = new ForkJoinPool((int) Math.ceil(Runtime.getRuntime().availableProcessors() * 0.75), ForkJoinPool.defaultForkJoinWorkerThreadFactory, null, true);
    cachingClusteredClient = new CachingClusteredClient(toolChestWarehouse, serverView, MapCache.create(0), JSON_MAPPER, new ForegroundCachePopulator(JSON_MAPPER, new CachePopulatorStats(), 0), new CacheConfig(), new DruidHttpClientConfig(), processingConfig, forkJoinPool, QueryStackTests.DEFAULT_NOOP_SCHEDULER, new MapJoinableFactory(ImmutableSet.of(), ImmutableMap.of()), new NoopServiceEmitter());
}

Example 13 with TimeseriesQueryRunnerFactory

use of org.apache.druid.query.timeseries.TimeseriesQueryRunnerFactory in project druid by druid-io.

the class TimeseriesBenchmark method setup.

/**
 * Setup everything common for benchmarking both the incremental-index and the queriable-index.
 */
@Setup
public void setup() {
    log.info("SETUP CALLED AT " + System.currentTimeMillis());
    ComplexMetrics.registerSerde("hyperUnique", new HyperUniquesSerde());
    setupQueries();
    String[] schemaQuery = schemaAndQuery.split("\\.");
    String schemaName = schemaQuery[0];
    String queryName = schemaQuery[1];
    schemaInfo = GeneratorBasicSchemas.SCHEMA_MAP.get(schemaName);
    query = SCHEMA_QUERY_MAP.get(schemaName).get(queryName);
    generator = new DataGenerator(schemaInfo.getColumnSchemas(), RNG_SEED, schemaInfo.getDataInterval(), rowsPerSegment);
    factory = new TimeseriesQueryRunnerFactory(new TimeseriesQueryQueryToolChest(), new TimeseriesQueryEngine(), QueryBenchmarkUtil.NOOP_QUERYWATCHER);
}

Example 14 with TimeseriesQueryRunnerFactory

use of org.apache.druid.query.timeseries.TimeseriesQueryRunnerFactory in project druid by druid-io.

the class TimeCompareBenchmark method setupQueries.

private void setupQueries() {
    // queries for the basic schema
    GeneratorSchemaInfo basicSchema = GeneratorBasicSchemas.SCHEMA_MAP.get("basic");
    QuerySegmentSpec intervalSpec = new MultipleIntervalSegmentSpec(Collections.singletonList(basicSchema.getDataInterval()));
    long startMillis = basicSchema.getDataInterval().getStartMillis();
    long endMillis = basicSchema.getDataInterval().getEndMillis();
    long half = (endMillis - startMillis) / 2;
    Interval recent = Intervals.utc(half, endMillis);
    Interval previous = Intervals.utc(startMillis, half);
    log.info("Recent interval: " + recent);
    log.info("Previous interval: " + previous);
    {
        // basic.topNTimeCompare
        List<AggregatorFactory> queryAggs = new ArrayList<>();
        queryAggs.add(new FilteredAggregatorFactory(// jsAgg1,
        new LongSumAggregatorFactory("sumLongSequential", "sumLongSequential"), new IntervalDimFilter(ColumnHolder.TIME_COLUMN_NAME, Collections.singletonList(recent), null)));
        queryAggs.add(new FilteredAggregatorFactory(new LongSumAggregatorFactory("_cmp_sumLongSequential", "sumLongSequential"), new IntervalDimFilter(ColumnHolder.TIME_COLUMN_NAME, Collections.singletonList(previous), null)));
        TopNQueryBuilder queryBuilderA = new TopNQueryBuilder().dataSource("blah").granularity(Granularities.ALL).dimension("dimUniform").metric("sumLongSequential").intervals(intervalSpec).aggregators(queryAggs).threshold(threshold);
        topNQuery = queryBuilderA.build();
        topNFactory = new TopNQueryRunnerFactory(new StupidPool<>("TopNBenchmark-compute-bufferPool", new OffheapBufferGenerator("compute", 250000000), 0, Integer.MAX_VALUE), new TopNQueryQueryToolChest(new TopNQueryConfig()), QueryBenchmarkUtil.NOOP_QUERYWATCHER);
    }
    {
        // basic.timeseriesTimeCompare
        List<AggregatorFactory> queryAggs = new ArrayList<>();
        queryAggs.add(new FilteredAggregatorFactory(new LongSumAggregatorFactory("sumLongSequential", "sumLongSequential"), new IntervalDimFilter(ColumnHolder.TIME_COLUMN_NAME, Collections.singletonList(recent), null)));
        queryAggs.add(new FilteredAggregatorFactory(new LongSumAggregatorFactory("_cmp_sumLongSequential", "sumLongSequential"), new IntervalDimFilter(ColumnHolder.TIME_COLUMN_NAME, Collections.singletonList(previous), null)));
        Druids.TimeseriesQueryBuilder timeseriesQueryBuilder = Druids.newTimeseriesQueryBuilder().dataSource("blah").granularity(Granularities.ALL).intervals(intervalSpec).aggregators(queryAggs).descending(false);
        timeseriesQuery = timeseriesQueryBuilder.build();
        timeseriesFactory = new TimeseriesQueryRunnerFactory(new TimeseriesQueryQueryToolChest(), new TimeseriesQueryEngine(), QueryBenchmarkUtil.NOOP_QUERYWATCHER);
    }
}

Example 15 with TimeseriesQueryRunnerFactory

use of org.apache.druid.query.timeseries.TimeseriesQueryRunnerFactory in project druid by druid-io.

the class FilteredAggregatorBenchmark method setup.

/**
 * Setup everything common for benchmarking both the incremental-index and the queriable-index.
 */
@Setup
public void setup() {
    log.info("SETUP CALLED AT " + System.currentTimeMillis());
    ComplexMetrics.registerSerde("hyperUnique", new HyperUniquesSerde());
    schemaInfo = GeneratorBasicSchemas.SCHEMA_MAP.get(schema);
    generator = new DataGenerator(schemaInfo.getColumnSchemas(), RNG_SEED, schemaInfo.getDataInterval(), rowsPerSegment);
    filter = new OrDimFilter(Arrays.asList(new BoundDimFilter("dimSequential", "-1", "-1", true, true, null, null, StringComparators.ALPHANUMERIC), new RegexDimFilter("dimSequential", "X", null), new SearchQueryDimFilter("dimSequential", new ContainsSearchQuerySpec("X", false), null), new InDimFilter("dimSequential", Collections.singletonList("X"), null)));
    filteredMetric = new FilteredAggregatorFactory(new CountAggregatorFactory("rows"), filter);
    factory = new TimeseriesQueryRunnerFactory(new TimeseriesQueryQueryToolChest(), new TimeseriesQueryEngine(), QueryBenchmarkUtil.NOOP_QUERYWATCHER);
    GeneratorSchemaInfo basicSchema = GeneratorBasicSchemas.SCHEMA_MAP.get("basic");
    QuerySegmentSpec intervalSpec = new MultipleIntervalSegmentSpec(Collections.singletonList(basicSchema.getDataInterval()));
    List<AggregatorFactory> queryAggs = Collections.singletonList(filteredMetric);
    query = Druids.newTimeseriesQueryBuilder().dataSource("blah").granularity(Granularities.ALL).intervals(intervalSpec).aggregators(queryAggs).descending(descending).build();
}