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

Example 91 with TimeseriesQuery

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

the class StringLastTimeseriesQueryTest method testTimeseriesQuery.

@Test
public void testTimeseriesQuery() {
    TimeseriesQueryEngine engine = new TimeseriesQueryEngine();
    TimeseriesQuery query = Druids.newTimeseriesQueryBuilder().dataSource(QueryRunnerTestHelper.DATA_SOURCE).granularity(QueryRunnerTestHelper.ALL_GRAN).intervals(QueryRunnerTestHelper.FULL_ON_INTERVAL_SPEC).aggregators(ImmutableList.of(new StringLastAggregatorFactory("nonfolding", CLIENT_TYPE, null, 1024), new StringLastAggregatorFactory("folding", LAST_CLIENT_TYPE, null, 1024), new StringLastAggregatorFactory("nonexistent", "nonexistent", null, 1024), new StringLastAggregatorFactory("numeric", "cnt", null, 1024))).build();
    List<Result<TimeseriesResultValue>> expectedResults = Collections.singletonList(new Result<>(TIME1, new TimeseriesResultValue(ImmutableMap.<String, Object>builder().put("nonfolding", new SerializablePairLongString(TIME2.getMillis(), "android")).put("folding", new SerializablePairLongString(TIME2.getMillis(), "android")).put("nonexistent", new SerializablePairLongString(DateTimes.MIN.getMillis(), null)).put("numeric", new SerializablePairLongString(DateTimes.MIN.getMillis(), null)).build())));
    final Iterable<Result<TimeseriesResultValue>> iiResults = engine.process(query, new IncrementalIndexStorageAdapter(incrementalIndex)).toList();
    final Iterable<Result<TimeseriesResultValue>> qiResults = engine.process(query, new QueryableIndexStorageAdapter(queryableIndex)).toList();
    TestHelper.assertExpectedResults(expectedResults, iiResults, "incremental index");
    TestHelper.assertExpectedResults(expectedResults, qiResults, "queryable index");
}

Example 92 with TimeseriesQuery

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

the class FinalizingFieldAccessPostAggregatorTest method testResultArraySignature.

@Test
public void testResultArraySignature() {
    final TimeseriesQuery query = Druids.newTimeseriesQueryBuilder().dataSource("dummy").intervals("2000/3000").granularity(Granularities.HOUR).aggregators(new CountAggregatorFactory("count"), new StringFirstAggregatorFactory("stringo", "col", null, 1024)).postAggregators(new FieldAccessPostAggregator("a", "stringo"), new FinalizingFieldAccessPostAggregator("b", "stringo")).build();
    Assert.assertEquals(RowSignature.builder().addTimeColumn().add("count", ColumnType.LONG).add("stringo", null).add("a", StringFirstAggregatorFactory.TYPE).add("b", ColumnType.STRING).build(), new TimeseriesQueryQueryToolChest().resultArraySignature(query));
}

Example 93 with TimeseriesQuery

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

the class DoubleMeanAggregationTest method testAggretatorUsingTimeseriesQuery.

@Test
@Parameters(method = "doVectorize")
public void testAggretatorUsingTimeseriesQuery(boolean doVectorize) throws Exception {
    TimeseriesQuery query = Druids.newTimeseriesQueryBuilder().dataSource("test").granularity(Granularities.ALL).intervals("1970/2050").aggregators(new DoubleMeanAggregatorFactory("meanOnDouble", SimpleTestIndex.DOUBLE_COL), new DoubleMeanAggregatorFactory("meanOnString", SimpleTestIndex.SINGLE_VALUE_DOUBLE_AS_STRING_DIM), new DoubleMeanAggregatorFactory("meanOnMultiValue", SimpleTestIndex.MULTI_VALUE_DOUBLE_AS_STRING_DIM)).context(ImmutableMap.of(QueryContexts.VECTORIZE_KEY, doVectorize)).build();
    // do json serialization and deserialization of query to ensure there are no serde issues
    ObjectMapper jsonMapper = timeseriesQueryTestHelper.getObjectMapper();
    query = (TimeseriesQuery) jsonMapper.readValue(jsonMapper.writeValueAsString(query), Query.class);
    Sequence seq = timeseriesQueryTestHelper.runQueryOnSegmentsObjs(segments, query);
    TimeseriesResultValue result = ((Result<TimeseriesResultValue>) Iterables.getOnlyElement(seq.toList())).getValue();
    Assert.assertEquals(6.2d, result.getDoubleMetric("meanOnDouble").doubleValue(), 0.0001d);
    Assert.assertEquals(6.2d, result.getDoubleMetric("meanOnString").doubleValue(), 0.0001d);
    Assert.assertEquals(4.1333d, result.getDoubleMetric("meanOnMultiValue").doubleValue(), 0.0001d);
}

Example 94 with TimeseriesQuery

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

the class SpecificSegmentQueryRunnerTest method testRetry.

@Test
public void testRetry() throws Exception {
    final ObjectMapper mapper = new DefaultObjectMapper();
    SegmentDescriptor descriptor = new SegmentDescriptor(Intervals.of("2012-01-01T00:00:00Z/P1D"), "version", 0);
    final SpecificSegmentQueryRunner queryRunner = new SpecificSegmentQueryRunner(new QueryRunner() {

        @Override
        public Sequence run(QueryPlus queryPlus, ResponseContext responseContext) {
            return new Sequence() {

                @Override
                public Object accumulate(Object initValue, Accumulator accumulator) {
                    throw new SegmentMissingException("FAILSAUCE");
                }

                @Override
                public Yielder<Object> toYielder(Object initValue, YieldingAccumulator accumulator) {
                    throw new SegmentMissingException("FAILSAUCE");
                }
            };
        }
    }, new SpecificSegmentSpec(descriptor));
    // from accumulate
    ResponseContext responseContext = ResponseContext.createEmpty();
    TimeseriesQuery query = Druids.newTimeseriesQueryBuilder().dataSource("foo").granularity(Granularities.ALL).intervals(ImmutableList.of(Intervals.of("2012-01-01T00:00:00Z/P1D"))).aggregators(ImmutableList.of(new CountAggregatorFactory("rows"))).build();
    Sequence results = queryRunner.run(QueryPlus.wrap(query), responseContext);
    results.toList();
    validate(mapper, descriptor, responseContext);
    // from toYielder
    responseContext = ResponseContext.createEmpty();
    results = queryRunner.run(QueryPlus.wrap(query), responseContext);
    results.toYielder(null, new YieldingAccumulator() {

        final List lists = new ArrayList<>();

        @Override
        public Object accumulate(Object accumulated, Object in) {
            lists.add(in);
            return in;
        }
    });
    validate(mapper, descriptor, responseContext);
}

Example 95 with TimeseriesQuery

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

the class SpecificSegmentQueryRunnerTest method testRetry2.

@SuppressWarnings("unchecked")
@Test
public void testRetry2() throws Exception {
    final ObjectMapper mapper = new DefaultObjectMapper();
    SegmentDescriptor descriptor = new SegmentDescriptor(Intervals.of("2012-01-01T00:00:00Z/P1D"), "version", 0);
    TimeseriesResultBuilder builder = new TimeseriesResultBuilder(DateTimes.of("2012-01-01T00:00:00Z"));
    CountAggregator rows = new CountAggregator();
    rows.aggregate();
    builder.addMetric("rows", rows.get());
    final Result<TimeseriesResultValue> value = builder.build();
    final SpecificSegmentQueryRunner queryRunner = new SpecificSegmentQueryRunner(new QueryRunner() {

        @Override
        public Sequence run(QueryPlus queryPlus, ResponseContext responseContext) {
            return Sequences.withEffect(Sequences.simple(Collections.singletonList(value)), new Runnable() {

                @Override
                public void run() {
                    throw new SegmentMissingException("FAILSAUCE");
                }
            }, Execs.directExecutor());
        }
    }, new SpecificSegmentSpec(descriptor));
    final ResponseContext responseContext = ResponseContext.createEmpty();
    TimeseriesQuery query = Druids.newTimeseriesQueryBuilder().dataSource("foo").granularity(Granularities.ALL).intervals(ImmutableList.of(Intervals.of("2012-01-01T00:00:00Z/P1D"))).aggregators(ImmutableList.of(new CountAggregatorFactory("rows"))).build();
    Sequence results = queryRunner.run(QueryPlus.wrap(query), responseContext);
    List<Result<TimeseriesResultValue>> res = results.toList();
    Assert.assertEquals(1, res.size());
    Result<TimeseriesResultValue> theVal = res.get(0);
    Assert.assertTrue(1L == theVal.getValue().getLongMetric("rows"));
    validate(mapper, descriptor, responseContext);
}