Examples with DoubleSumAggregatorFactory org.apache.druid.query.aggregation.DoubleSumAggregatorFactory used on opensource projects

Example 71 with DoubleSumAggregatorFactory

use of org.apache.druid.query.aggregation.DoubleSumAggregatorFactory in project druid by druid-io.

the class IncrementalIndexTest method testConcurrentAddRead.

@Test(timeout = 60_000L)
public void testConcurrentAddRead() throws InterruptedException, ExecutionException {
    final int dimensionCount = 5;
    final ArrayList<AggregatorFactory> ingestAggregatorFactories = new ArrayList<>(dimensionCount + 1);
    ingestAggregatorFactories.add(new CountAggregatorFactory("rows"));
    for (int i = 0; i < dimensionCount; ++i) {
        ingestAggregatorFactories.add(new LongSumAggregatorFactory(StringUtils.format("sumResult%s", i), StringUtils.format("Dim_%s", i)));
        ingestAggregatorFactories.add(new DoubleSumAggregatorFactory(StringUtils.format("doubleSumResult%s", i), StringUtils.format("Dim_%s", i)));
    }
    final ArrayList<AggregatorFactory> queryAggregatorFactories = new ArrayList<>(dimensionCount + 1);
    queryAggregatorFactories.add(new CountAggregatorFactory("rows"));
    for (int i = 0; i < dimensionCount; ++i) {
        queryAggregatorFactories.add(new LongSumAggregatorFactory(StringUtils.format("sumResult%s", i), StringUtils.format("sumResult%s", i)));
        queryAggregatorFactories.add(new DoubleSumAggregatorFactory(StringUtils.format("doubleSumResult%s", i), StringUtils.format("doubleSumResult%s", i)));
    }
    final IncrementalIndex index = indexCreator.createIndex((Object) ingestAggregatorFactories.toArray(new AggregatorFactory[0]));
    final int concurrentThreads = 2;
    final int elementsPerThread = 10_000;
    final ListeningExecutorService indexExecutor = MoreExecutors.listeningDecorator(Executors.newFixedThreadPool(concurrentThreads, new ThreadFactoryBuilder().setDaemon(false).setNameFormat("index-executor-%d").setPriority(Thread.MIN_PRIORITY).build()));
    final ListeningExecutorService queryExecutor = MoreExecutors.listeningDecorator(Executors.newFixedThreadPool(concurrentThreads, new ThreadFactoryBuilder().setDaemon(false).setNameFormat("query-executor-%d").build()));
    final long timestamp = System.currentTimeMillis();
    final Interval queryInterval = Intervals.of("1900-01-01T00:00:00Z/2900-01-01T00:00:00Z");
    final List<ListenableFuture<?>> indexFutures = Lists.newArrayListWithExpectedSize(concurrentThreads);
    final List<ListenableFuture<?>> queryFutures = Lists.newArrayListWithExpectedSize(concurrentThreads);
    final Segment incrementalIndexSegment = new IncrementalIndexSegment(index, null);
    final QueryRunnerFactory factory = new TimeseriesQueryRunnerFactory(new TimeseriesQueryQueryToolChest(), new TimeseriesQueryEngine(), QueryRunnerTestHelper.NOOP_QUERYWATCHER);
    final AtomicInteger currentlyRunning = new AtomicInteger(0);
    final AtomicInteger concurrentlyRan = new AtomicInteger(0);
    final AtomicInteger someoneRan = new AtomicInteger(0);
    final CountDownLatch startLatch = new CountDownLatch(1);
    final CountDownLatch readyLatch = new CountDownLatch(concurrentThreads * 2);
    final AtomicInteger queriesAccumualted = new AtomicInteger(0);
    for (int j = 0; j < concurrentThreads; j++) {
        indexFutures.add(indexExecutor.submit(new Runnable() {

            @Override
            public void run() {
                readyLatch.countDown();
                try {
                    startLatch.await();
                } catch (InterruptedException e) {
                    Thread.currentThread().interrupt();
                    throw new RuntimeException(e);
                }
                currentlyRunning.incrementAndGet();
                try {
                    for (int i = 0; i < elementsPerThread; i++) {
                        index.add(getLongRow(timestamp + i, dimensionCount));
                        someoneRan.incrementAndGet();
                    }
                } catch (IndexSizeExceededException e) {
                    throw new RuntimeException(e);
                }
                currentlyRunning.decrementAndGet();
            }
        }));
        final TimeseriesQuery query = Druids.newTimeseriesQueryBuilder().dataSource("xxx").granularity(Granularities.ALL).intervals(ImmutableList.of(queryInterval)).aggregators(queryAggregatorFactories).build();
        queryFutures.add(queryExecutor.submit(new Runnable() {

            @Override
            public void run() {
                readyLatch.countDown();
                try {
                    startLatch.await();
                } catch (InterruptedException e) {
                    Thread.currentThread().interrupt();
                    throw new RuntimeException(e);
                }
                while (concurrentlyRan.get() == 0) {
                    QueryRunner<Result<TimeseriesResultValue>> runner = new FinalizeResultsQueryRunner<Result<TimeseriesResultValue>>(factory.createRunner(incrementalIndexSegment), factory.getToolchest());
                    Sequence<Result<TimeseriesResultValue>> sequence = runner.run(QueryPlus.wrap(query));
                    Double[] results = sequence.accumulate(new Double[0], new Accumulator<Double[], Result<TimeseriesResultValue>>() {

                        @Override
                        public Double[] accumulate(Double[] accumulated, Result<TimeseriesResultValue> in) {
                            if (currentlyRunning.get() > 0) {
                                concurrentlyRan.incrementAndGet();
                            }
                            queriesAccumualted.incrementAndGet();
                            return Lists.asList(in.getValue().getDoubleMetric("doubleSumResult0"), accumulated).toArray(new Double[0]);
                        }
                    });
                    for (Double result : results) {
                        final Integer maxValueExpected = someoneRan.get() + concurrentThreads;
                        if (maxValueExpected > 0) {
                            // Eventually consistent, but should be somewhere in that range
                            // Actual result is validated after all writes are guaranteed done.
                            Assert.assertTrue(StringUtils.format("%d >= %g >= 0 violated", maxValueExpected, result), result >= 0 && result <= maxValueExpected);
                        }
                    }
                }
            }
        }));
    }
    readyLatch.await();
    startLatch.countDown();
    List<ListenableFuture<?>> allFutures = new ArrayList<>(queryFutures.size() + indexFutures.size());
    allFutures.addAll(queryFutures);
    allFutures.addAll(indexFutures);
    Futures.allAsList(allFutures).get();
    Assert.assertTrue("Queries ran too fast", queriesAccumualted.get() > 0);
    Assert.assertTrue("Did not hit concurrency, please try again", concurrentlyRan.get() > 0);
    queryExecutor.shutdown();
    indexExecutor.shutdown();
    QueryRunner<Result<TimeseriesResultValue>> runner = new FinalizeResultsQueryRunner<Result<TimeseriesResultValue>>(factory.createRunner(incrementalIndexSegment), factory.getToolchest());
    TimeseriesQuery query = Druids.newTimeseriesQueryBuilder().dataSource("xxx").granularity(Granularities.ALL).intervals(ImmutableList.of(queryInterval)).aggregators(queryAggregatorFactories).build();
    List<Result<TimeseriesResultValue>> results = runner.run(QueryPlus.wrap(query)).toList();
    boolean isRollup = index.isRollup();
    for (Result<TimeseriesResultValue> result : results) {
        Assert.assertEquals(elementsPerThread * (isRollup ? 1 : concurrentThreads), result.getValue().getLongMetric("rows").intValue());
        for (int i = 0; i < dimensionCount; ++i) {
            Assert.assertEquals(StringUtils.format("Failed long sum on dimension %d", i), elementsPerThread * concurrentThreads, result.getValue().getLongMetric(StringUtils.format("sumResult%s", i)).intValue());
            Assert.assertEquals(StringUtils.format("Failed double sum on dimension %d", i), elementsPerThread * concurrentThreads, result.getValue().getDoubleMetric(StringUtils.format("doubleSumResult%s", i)).intValue());
        }
    }
}

Example 72 with DoubleSumAggregatorFactory

use of org.apache.druid.query.aggregation.DoubleSumAggregatorFactory in project druid by druid-io.

the class IncrementalIndexTest method testSingleThreadedIndexingAndQuery.

@Test
public void testSingleThreadedIndexingAndQuery() throws Exception {
    final int dimensionCount = 5;
    final ArrayList<AggregatorFactory> ingestAggregatorFactories = new ArrayList<>();
    ingestAggregatorFactories.add(new CountAggregatorFactory("rows"));
    for (int i = 0; i < dimensionCount; ++i) {
        ingestAggregatorFactories.add(new LongSumAggregatorFactory(StringUtils.format("sumResult%s", i), StringUtils.format("Dim_%s", i)));
        ingestAggregatorFactories.add(new DoubleSumAggregatorFactory(StringUtils.format("doubleSumResult%s", i), StringUtils.format("Dim_%s", i)));
    }
    final IncrementalIndex index = indexCreator.createIndex((Object) ingestAggregatorFactories.toArray(new AggregatorFactory[0]));
    final long timestamp = System.currentTimeMillis();
    final int rows = 50;
    // ingesting same data twice to have some merging happening
    for (int i = 0; i < rows; i++) {
        index.add(getLongRow(timestamp + i, dimensionCount));
    }
    for (int i = 0; i < rows; i++) {
        index.add(getLongRow(timestamp + i, dimensionCount));
    }
    // run a timeseries query on the index and verify results
    final ArrayList<AggregatorFactory> queryAggregatorFactories = new ArrayList<>();
    queryAggregatorFactories.add(new CountAggregatorFactory("rows"));
    for (int i = 0; i < dimensionCount; ++i) {
        queryAggregatorFactories.add(new LongSumAggregatorFactory(StringUtils.format("sumResult%s", i), StringUtils.format("sumResult%s", i)));
        queryAggregatorFactories.add(new DoubleSumAggregatorFactory(StringUtils.format("doubleSumResult%s", i), StringUtils.format("doubleSumResult%s", i)));
    }
    TimeseriesQuery query = Druids.newTimeseriesQueryBuilder().dataSource("xxx").granularity(Granularities.ALL).intervals(ImmutableList.of(Intervals.of("2000/2030"))).aggregators(queryAggregatorFactories).build();
    final Segment incrementalIndexSegment = new IncrementalIndexSegment(index, null);
    final QueryRunnerFactory factory = new TimeseriesQueryRunnerFactory(new TimeseriesQueryQueryToolChest(), new TimeseriesQueryEngine(), QueryRunnerTestHelper.NOOP_QUERYWATCHER);
    final QueryRunner<Result<TimeseriesResultValue>> runner = new FinalizeResultsQueryRunner<Result<TimeseriesResultValue>>(factory.createRunner(incrementalIndexSegment), factory.getToolchest());
    List<Result<TimeseriesResultValue>> results = runner.run(QueryPlus.wrap(query)).toList();
    Result<TimeseriesResultValue> result = Iterables.getOnlyElement(results);
    boolean isRollup = index.isRollup();
    Assert.assertEquals(rows * (isRollup ? 1 : 2), result.getValue().getLongMetric("rows").intValue());
    for (int i = 0; i < dimensionCount; ++i) {
        Assert.assertEquals("Failed long sum on dimension " + i, 2 * rows, result.getValue().getLongMetric("sumResult" + i).intValue());
        Assert.assertEquals("Failed double sum on dimension " + i, 2 * rows, result.getValue().getDoubleMetric("doubleSumResult" + i).intValue());
    }
}

Example 73 with DoubleSumAggregatorFactory

use of org.apache.druid.query.aggregation.DoubleSumAggregatorFactory in project druid by druid-io.

the class CalciteQueryTest method testStringLatestInSubquery.

// This test the off-heap (buffer) version of the LatestAggregator (String)
@Test
public void testStringLatestInSubquery() throws Exception {
    // Cannot vectorize LATEST aggregator.
    skipVectorize();
    testQuery("SELECT SUM(val) FROM (SELECT dim2, LATEST(dim1, 10) AS val FROM foo GROUP BY dim2)", ImmutableList.of(GroupByQuery.builder().setDataSource(GroupByQuery.builder().setDataSource(CalciteTests.DATASOURCE1).setInterval(querySegmentSpec(Filtration.eternity())).setGranularity(Granularities.ALL).setDimensions(dimensions(new DefaultDimensionSpec("dim2", "d0"))).setAggregatorSpecs(aggregators(new StringLastAggregatorFactory("a0:a", "dim1", null, 10))).setPostAggregatorSpecs(ImmutableList.of(new FinalizingFieldAccessPostAggregator("a0", "a0:a"))).setContext(QUERY_CONTEXT_DEFAULT).build()).setInterval(querySegmentSpec(Filtration.eternity())).setGranularity(Granularities.ALL).setAggregatorSpecs(aggregators(new DoubleSumAggregatorFactory("_a0", null, "CAST(\"a0\", 'DOUBLE')", ExprMacroTable.nil()))).setContext(QUERY_CONTEXT_DEFAULT).build()), ImmutableList.of(new Object[] { NullHandling.sqlCompatible() ? 3 : 1.0 }));
}

Example 74 with DoubleSumAggregatorFactory

use of org.apache.druid.query.aggregation.DoubleSumAggregatorFactory in project druid by druid-io.

the class CalciteQueryTest method testPrimitiveEarliestInSubquery.

// This test the off-heap (buffer) version of the EarliestAggregator (Double/Float/Long)
@Test
public void testPrimitiveEarliestInSubquery() throws Exception {
    // Cannot vectorize EARLIEST aggregator.
    skipVectorize();
    testQuery("SELECT SUM(val1), SUM(val2), SUM(val3) FROM (SELECT dim2, EARLIEST(m1) AS val1, EARLIEST(cnt) AS val2, EARLIEST(m2) AS val3 FROM foo GROUP BY dim2)", ImmutableList.of(GroupByQuery.builder().setDataSource(GroupByQuery.builder().setDataSource(CalciteTests.DATASOURCE1).setInterval(querySegmentSpec(Filtration.eternity())).setGranularity(Granularities.ALL).setDimensions(dimensions(new DefaultDimensionSpec("dim2", "d0"))).setAggregatorSpecs(aggregators(new FloatFirstAggregatorFactory("a0:a", "m1", null), new LongFirstAggregatorFactory("a1:a", "cnt", null), new DoubleFirstAggregatorFactory("a2:a", "m2", null))).setPostAggregatorSpecs(ImmutableList.of(new FinalizingFieldAccessPostAggregator("a0", "a0:a"), new FinalizingFieldAccessPostAggregator("a1", "a1:a"), new FinalizingFieldAccessPostAggregator("a2", "a2:a"))).setContext(QUERY_CONTEXT_DEFAULT).build()).setInterval(querySegmentSpec(Filtration.eternity())).setGranularity(Granularities.ALL).setAggregatorSpecs(aggregators(new DoubleSumAggregatorFactory("_a0", "a0"), new LongSumAggregatorFactory("_a1", "a1"), new DoubleSumAggregatorFactory("_a2", "a2"))).setContext(QUERY_CONTEXT_DEFAULT).build()), NullHandling.sqlCompatible() ? ImmutableList.of(new Object[] { 11.0, 4L, 11.0 }) : ImmutableList.of(new Object[] { 8.0, 3L, 8.0 }));
}

Example 75 with DoubleSumAggregatorFactory

use of org.apache.druid.query.aggregation.DoubleSumAggregatorFactory in project druid by druid-io.

the class DataSchemaTest method testDefaultExclusions.

@Test
public void testDefaultExclusions() {
    Map<String, Object> parser = jsonMapper.convertValue(new StringInputRowParser(new JSONParseSpec(new TimestampSpec("time", "auto", null), new DimensionsSpec(DimensionsSpec.getDefaultSchemas(ImmutableList.of("dimB", "dimA"))), null, null, null), null), JacksonUtils.TYPE_REFERENCE_MAP_STRING_OBJECT);
    DataSchema schema = new DataSchema(IdUtilsTest.VALID_ID_CHARS, parser, new AggregatorFactory[] { new DoubleSumAggregatorFactory("metric1", "col1"), new DoubleSumAggregatorFactory("metric2", "col2") }, new ArbitraryGranularitySpec(Granularities.DAY, ImmutableList.of(Intervals.of("2014/2015"))), null, jsonMapper);
    Assert.assertEquals(ImmutableSet.of("__time", "time", "col1", "col2", "metric1", "metric2"), schema.getDimensionsSpec().getDimensionExclusions());
}