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

Example 6 with TimeseriesQueryRunnerFactory

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

the class SpatialFilterTest method testSpatialQueryWithOtherSpatialDim.

@Test
public void testSpatialQueryWithOtherSpatialDim() {
    TimeseriesQuery query = Druids.newTimeseriesQueryBuilder().dataSource("test").granularity(Granularities.ALL).intervals(Collections.singletonList(Intervals.of("2013-01-01/2013-01-07"))).filters(new SpatialDimFilter("spatialIsRad", new RadiusBound(new float[] { 0.0f, 0.0f }, 5))).aggregators(Arrays.asList(new CountAggregatorFactory("rows"), new LongSumAggregatorFactory("val", "val"))).build();
    List<Result<TimeseriesResultValue>> expectedResults = Collections.singletonList(new Result<TimeseriesResultValue>(DateTimes.of("2013-01-01T00:00:00.000Z"), new TimeseriesResultValue(ImmutableMap.<String, Object>builder().put("rows", 1L).put("val", 13L).build())));
    try {
        TimeseriesQueryRunnerFactory factory = new TimeseriesQueryRunnerFactory(new TimeseriesQueryQueryToolChest(), new TimeseriesQueryEngine(), QueryRunnerTestHelper.NOOP_QUERYWATCHER);
        QueryRunner runner = new FinalizeResultsQueryRunner(factory.createRunner(segment), factory.getToolchest());
        TestHelper.assertExpectedResults(expectedResults, runner.run(QueryPlus.wrap(query)));
    } catch (Exception e) {
        throw new RuntimeException(e);
    }
}

Example 7 with TimeseriesQueryRunnerFactory

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

the class QueryStackTests method createQueryRunnerFactoryConglomerate.

public static QueryRunnerFactoryConglomerate createQueryRunnerFactoryConglomerate(final Closer closer, final DruidProcessingConfig processingConfig, final Supplier<Integer> minTopNThresholdSupplier) {
    final CloseableStupidPool<ByteBuffer> stupidPool = new CloseableStupidPool<>("TopNQueryRunnerFactory-bufferPool", () -> ByteBuffer.allocate(COMPUTE_BUFFER_SIZE));
    closer.register(stupidPool);
    final Pair<GroupByQueryRunnerFactory, Closer> factoryCloserPair = GroupByQueryRunnerTest.makeQueryRunnerFactory(GroupByQueryRunnerTest.DEFAULT_MAPPER, new GroupByQueryConfig() {

        @Override
        public String getDefaultStrategy() {
            return GroupByStrategySelector.STRATEGY_V2;
        }
    }, processingConfig);
    final GroupByQueryRunnerFactory groupByQueryRunnerFactory = factoryCloserPair.lhs;
    closer.register(factoryCloserPair.rhs);
    final QueryRunnerFactoryConglomerate conglomerate = new DefaultQueryRunnerFactoryConglomerate(ImmutableMap.<Class<? extends Query>, QueryRunnerFactory>builder().put(SegmentMetadataQuery.class, new SegmentMetadataQueryRunnerFactory(new SegmentMetadataQueryQueryToolChest(new SegmentMetadataQueryConfig("P1W")), QueryRunnerTestHelper.NOOP_QUERYWATCHER)).put(ScanQuery.class, new ScanQueryRunnerFactory(new ScanQueryQueryToolChest(new ScanQueryConfig(), new DefaultGenericQueryMetricsFactory()), new ScanQueryEngine(), new ScanQueryConfig())).put(TimeseriesQuery.class, new TimeseriesQueryRunnerFactory(new TimeseriesQueryQueryToolChest(), new TimeseriesQueryEngine(), QueryRunnerTestHelper.NOOP_QUERYWATCHER)).put(TopNQuery.class, new TopNQueryRunnerFactory(stupidPool, new TopNQueryQueryToolChest(new TopNQueryConfig() {

        @Override
        public int getMinTopNThreshold() {
            return minTopNThresholdSupplier.get();
        }
    }), QueryRunnerTestHelper.NOOP_QUERYWATCHER)).put(GroupByQuery.class, groupByQueryRunnerFactory).build());
    return conglomerate;
}

Example 8 with TimeseriesQueryRunnerFactory

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

the class SchemaEvolutionTest method testHyperUniqueEvolutionTimeseries.

@Test
@Parameters(method = "doVectorize")
public void testHyperUniqueEvolutionTimeseries(boolean doVectorize) {
    final TimeseriesQueryRunnerFactory factory = QueryRunnerTestHelper.newTimeseriesQueryRunnerFactory();
    final TimeseriesQuery query = Druids.newTimeseriesQueryBuilder().dataSource(DATA_SOURCE).intervals("1000/3000").aggregators(ImmutableList.of(new HyperUniquesAggregatorFactory("uniques", "uniques"))).context(ImmutableMap.of(QueryContexts.VECTORIZE_KEY, doVectorize)).build();
    // index1 has no "uniques" column
    Assert.assertEquals(timeseriesResult(ImmutableMap.of("uniques", 0d)), runQuery(query, factory, ImmutableList.of(index1)));
    // index1 (no uniques) + index2 and index3 (yes uniques); we should be able to combine
    Assert.assertEquals(timeseriesResult(ImmutableMap.of("uniques", 4.003911343725148d)), runQuery(query, factory, ImmutableList.of(index1, index2, index3)));
}

Example 9 with TimeseriesQueryRunnerFactory

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

the class SchemaEvolutionTest method testNumericEvolutionFiltering.

@Test
@Parameters(method = "doVectorize")
public void testNumericEvolutionFiltering(boolean doVectorize) {
    final TimeseriesQueryRunnerFactory factory = QueryRunnerTestHelper.newTimeseriesQueryRunnerFactory();
    // "c1" changes from string(1) -> long(2) -> float(3) -> nonexistent(4)
    // test behavior of filtering
    final TimeseriesQuery query = Druids.newTimeseriesQueryBuilder().dataSource(DATA_SOURCE).intervals("1000/3000").filters(new BoundDimFilter("c1", "9", "11", false, false, null, null, StringComparators.NUMERIC)).aggregators(ImmutableList.of(new LongSumAggregatorFactory("a", "c1"), new DoubleSumAggregatorFactory("b", "c1"), new FloatSumAggregatorFactory("d", "c1"), new LongMinAggregatorFactory("e", "c1"), new CountAggregatorFactory("c"))).context(ImmutableMap.of(QueryContexts.VECTORIZE_KEY, doVectorize)).build();
    // Only string(1) -- which we can filter but not aggregate
    Assert.assertEquals(timeseriesResult(ImmutableMap.of("a", 19L, "b", 19.1, "c", 2L, "d", 19.1f, "e", 9L)), runQuery(query, factory, ImmutableList.of(index1)));
    // Only long(2) -- which we can filter and aggregate
    Assert.assertEquals(timeseriesResult(ImmutableMap.of("a", 19L, "b", 19.0, "c", 2L, "d", 19.0f, "e", 9L)), runQuery(query, factory, ImmutableList.of(index2)));
    // Only float(3) -- which we can't filter, but can aggregate
    Assert.assertEquals(timeseriesResult(ImmutableMap.of("a", 19L, "b", 19.1, "c", 2L, "d", 19.1f, "e", 9L)), runQuery(query, factory, ImmutableList.of(index3)));
    // Only nonexistent(4)
    Assert.assertEquals(timeseriesResult(TestHelper.createExpectedMap("a", NullHandling.defaultLongValue(), "b", NullHandling.defaultDoubleValue(), "c", 0L, "d", NullHandling.defaultFloatValue(), "e", NullHandling.sqlCompatible() ? null : Long.MAX_VALUE)), runQuery(query, factory, ImmutableList.of(index4)));
    // string(1) + long(2) + float(3) + nonexistent(4)
    Assert.assertEquals(timeseriesResult(ImmutableMap.of("a", 57L, "b", 57.2, "c", 6L, "d", 57.20000076293945, "e", 9L)), runQuery(query, factory, ImmutableList.of(index1, index2, index3, index4)));
}

Example 10 with TimeseriesQueryRunnerFactory

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

the class SchemaEvolutionTest method testNumericEvolutionTimeseriesAggregation.

@Test
@Parameters(method = "doVectorize")
public void testNumericEvolutionTimeseriesAggregation(boolean doVectorize) {
    final TimeseriesQueryRunnerFactory factory = QueryRunnerTestHelper.newTimeseriesQueryRunnerFactory();
    // "c1" changes from string(1) -> long(2) -> float(3) -> nonexistent(4)
    // test behavior of longSum/doubleSum with/without expressions
    final TimeseriesQuery query = Druids.newTimeseriesQueryBuilder().dataSource(DATA_SOURCE).intervals("1000/3000").aggregators(ImmutableList.of(new LongSumAggregatorFactory("a", "c1"), new DoubleSumAggregatorFactory("b", "c1"), new LongSumAggregatorFactory("c", null, "c1 * 1", TestExprMacroTable.INSTANCE), new DoubleSumAggregatorFactory("d", null, "c1 * 1", TestExprMacroTable.INSTANCE))).context(ImmutableMap.of(QueryContexts.VECTORIZE_KEY, doVectorize)).build();
    // Only string(1)
    // Note: Expressions implicitly cast strings to numbers, leading to the a/b vs c/d difference.
    Assert.assertEquals(timeseriesResult(ImmutableMap.of("a", 31L, "b", THIRTY_ONE_POINT_ONE, "c", 31L, "d", THIRTY_ONE_POINT_ONE)), runQuery(query, factory, ImmutableList.of(index1)));
    // Only long(2)
    Assert.assertEquals(timeseriesResult(ImmutableMap.of("a", 31L, "b", 31.0, "c", 31L, "d", 31.0)), runQuery(query, factory, ImmutableList.of(index2)));
    // Only float(3)
    Assert.assertEquals(timeseriesResult(ImmutableMap.of("a", 31L, "b", THIRTY_ONE_POINT_ONE, "c", 31L, "d", THIRTY_ONE_POINT_ONE)), runQuery(query, factory, ImmutableList.of(index3)));
    // Only nonexistent(4)
    Map<String, Object> result = new HashMap<>();
    result.put("a", NullHandling.defaultLongValue());
    result.put("b", NullHandling.defaultDoubleValue());
    result.put("c", NullHandling.defaultLongValue());
    result.put("d", NullHandling.defaultDoubleValue());
    Assert.assertEquals(timeseriesResult(result), runQuery(query, factory, ImmutableList.of(index4)));
    // string(1) + long(2) + float(3) + nonexistent(4)
    // Note: Expressions implicitly cast strings to numbers, leading to the a/b vs c/d difference.
    Assert.assertEquals(timeseriesResult(ImmutableMap.of("a", 31L * 3, "b", THIRTY_ONE_POINT_ONE * 2 + 31, "c", 31L * 3, "d", THIRTY_ONE_POINT_ONE * 2 + 31)), runQuery(query, factory, ImmutableList.of(index1, index2, index3, index4)));
    // long(2) + float(3) + nonexistent(4)
    Assert.assertEquals(timeseriesResult(ImmutableMap.of("a", 31L * 2, "b", THIRTY_ONE_POINT_ONE + 31, "c", 31L * 2, "d", THIRTY_ONE_POINT_ONE + 31)), runQuery(query, factory, ImmutableList.of(index2, index3, index4)));
}