Examples with DoubleMinAggregatorFactory io.druid.query.aggregation.DoubleMinAggregatorFactory used on opensource projects

Example 16 with DoubleMinAggregatorFactory

use of io.druid.query.aggregation.DoubleMinAggregatorFactory in project druid by druid-io.

the class TimeseriesQueryRunnerTest method testFullOnTimeseriesMaxMin.

@Test
public void testFullOnTimeseriesMaxMin() {
    TimeseriesQuery query = Druids.newTimeseriesQueryBuilder().dataSource(QueryRunnerTestHelper.dataSource).granularity(Granularities.ALL).intervals(QueryRunnerTestHelper.fullOnInterval).aggregators(Arrays.asList(new DoubleMaxAggregatorFactory("maxIndex", "index"), new DoubleMinAggregatorFactory("minIndex", "index"))).descending(descending).build();
    DateTime expectedEarliest = new DateTime("2011-01-12");
    DateTime expectedLast = new DateTime("2011-04-15");
    Iterable<Result<TimeseriesResultValue>> results = Sequences.toList(runner.run(query, CONTEXT), Lists.<Result<TimeseriesResultValue>>newArrayList());
    Result<TimeseriesResultValue> result = results.iterator().next();
    Assert.assertEquals(expectedEarliest, result.getTimestamp());
    Assert.assertFalse(String.format("Timestamp[%s] > expectedLast[%s]", result.getTimestamp(), expectedLast), result.getTimestamp().isAfter(expectedLast));
    final TimeseriesResultValue value = result.getValue();
    Assert.assertEquals(result.toString(), 1870.06103515625, value.getDoubleMetric("maxIndex"), 0.0);
    Assert.assertEquals(result.toString(), 59.02102279663086, value.getDoubleMetric("minIndex"), 0.0);
}

Example 17 with DoubleMinAggregatorFactory

use of io.druid.query.aggregation.DoubleMinAggregatorFactory in project druid by druid-io.

the class TimeseriesBenchmark method setupQueries.

private void setupQueries() {
    // queries for the basic schema
    Map<String, TimeseriesQuery> basicQueries = new LinkedHashMap<>();
    BenchmarkSchemaInfo basicSchema = BenchmarkSchemas.SCHEMA_MAP.get("basic");
    {
        // basic.A
        QuerySegmentSpec intervalSpec = new MultipleIntervalSegmentSpec(Arrays.asList(basicSchema.getDataInterval()));
        List<AggregatorFactory> queryAggs = new ArrayList<>();
        queryAggs.add(new LongSumAggregatorFactory("sumLongSequential", "sumLongSequential"));
        queryAggs.add(new LongMaxAggregatorFactory("maxLongUniform", "maxLongUniform"));
        queryAggs.add(new DoubleSumAggregatorFactory("sumFloatNormal", "sumFloatNormal"));
        queryAggs.add(new DoubleMinAggregatorFactory("minFloatZipf", "minFloatZipf"));
        queryAggs.add(new HyperUniquesAggregatorFactory("hyperUniquesMet", "hyper"));
        TimeseriesQuery queryA = Druids.newTimeseriesQueryBuilder().dataSource("blah").granularity(Granularities.ALL).intervals(intervalSpec).aggregators(queryAggs).descending(false).build();
        basicQueries.put("A", queryA);
    }
    {
        QuerySegmentSpec intervalSpec = new MultipleIntervalSegmentSpec(Arrays.asList(basicSchema.getDataInterval()));
        List<AggregatorFactory> queryAggs = new ArrayList<>();
        LongSumAggregatorFactory lsaf = new LongSumAggregatorFactory("sumLongSequential", "sumLongSequential");
        BoundDimFilter timeFilter = new BoundDimFilter(Column.TIME_COLUMN_NAME, "200000", "300000", false, false, null, null, StringComparators.NUMERIC);
        queryAggs.add(new FilteredAggregatorFactory(lsaf, timeFilter));
        TimeseriesQuery timeFilterQuery = Druids.newTimeseriesQueryBuilder().dataSource("blah").granularity(Granularities.ALL).intervals(intervalSpec).aggregators(queryAggs).descending(false).build();
        basicQueries.put("timeFilterNumeric", timeFilterQuery);
    }
    {
        QuerySegmentSpec intervalSpec = new MultipleIntervalSegmentSpec(Arrays.asList(basicSchema.getDataInterval()));
        List<AggregatorFactory> queryAggs = new ArrayList<>();
        LongSumAggregatorFactory lsaf = new LongSumAggregatorFactory("sumLongSequential", "sumLongSequential");
        BoundDimFilter timeFilter = new BoundDimFilter(Column.TIME_COLUMN_NAME, "200000", "300000", false, false, null, null, StringComparators.ALPHANUMERIC);
        queryAggs.add(new FilteredAggregatorFactory(lsaf, timeFilter));
        TimeseriesQuery timeFilterQuery = Druids.newTimeseriesQueryBuilder().dataSource("blah").granularity(Granularities.ALL).intervals(intervalSpec).aggregators(queryAggs).descending(false).build();
        basicQueries.put("timeFilterAlphanumeric", timeFilterQuery);
    }
    {
        QuerySegmentSpec intervalSpec = new MultipleIntervalSegmentSpec(Arrays.asList(new Interval(200000, 300000)));
        List<AggregatorFactory> queryAggs = new ArrayList<>();
        LongSumAggregatorFactory lsaf = new LongSumAggregatorFactory("sumLongSequential", "sumLongSequential");
        queryAggs.add(lsaf);
        TimeseriesQuery timeFilterQuery = Druids.newTimeseriesQueryBuilder().dataSource("blah").granularity(Granularities.ALL).intervals(intervalSpec).aggregators(queryAggs).descending(false).build();
        basicQueries.put("timeFilterByInterval", timeFilterQuery);
    }
    SCHEMA_QUERY_MAP.put("basic", basicQueries);
}

Example 18 with DoubleMinAggregatorFactory

use of io.druid.query.aggregation.DoubleMinAggregatorFactory in project druid by druid-io.

the class TopNBenchmark method setupQueries.

private void setupQueries() {
    // queries for the basic schema
    Map<String, TopNQueryBuilder> basicQueries = new LinkedHashMap<>();
    BenchmarkSchemaInfo basicSchema = BenchmarkSchemas.SCHEMA_MAP.get("basic");
    {
        // basic.A
        QuerySegmentSpec intervalSpec = new MultipleIntervalSegmentSpec(Arrays.asList(basicSchema.getDataInterval()));
        List<AggregatorFactory> queryAggs = new ArrayList<>();
        queryAggs.add(new LongSumAggregatorFactory("sumLongSequential", "sumLongSequential"));
        queryAggs.add(new LongMaxAggregatorFactory("maxLongUniform", "maxLongUniform"));
        queryAggs.add(new DoubleSumAggregatorFactory("sumFloatNormal", "sumFloatNormal"));
        queryAggs.add(new DoubleMinAggregatorFactory("minFloatZipf", "minFloatZipf"));
        queryAggs.add(new HyperUniquesAggregatorFactory("hyperUniquesMet", "hyper"));
        TopNQueryBuilder queryBuilderA = new TopNQueryBuilder().dataSource("blah").granularity(Granularities.ALL).dimension("dimSequential").metric("sumFloatNormal").intervals(intervalSpec).aggregators(queryAggs);
        basicQueries.put("A", queryBuilderA);
    }
    {
        // basic.numericSort
        QuerySegmentSpec intervalSpec = new MultipleIntervalSegmentSpec(Arrays.asList(basicSchema.getDataInterval()));
        List<AggregatorFactory> queryAggs = new ArrayList<>();
        queryAggs.add(new LongSumAggregatorFactory("sumLongSequential", "sumLongSequential"));
        TopNQueryBuilder queryBuilderA = new TopNQueryBuilder().dataSource("blah").granularity(Granularities.ALL).dimension("dimUniform").metric(new DimensionTopNMetricSpec(null, StringComparators.NUMERIC)).intervals(intervalSpec).aggregators(queryAggs);
        basicQueries.put("numericSort", queryBuilderA);
    }
    {
        // basic.alphanumericSort
        QuerySegmentSpec intervalSpec = new MultipleIntervalSegmentSpec(Arrays.asList(basicSchema.getDataInterval()));
        List<AggregatorFactory> queryAggs = new ArrayList<>();
        queryAggs.add(new LongSumAggregatorFactory("sumLongSequential", "sumLongSequential"));
        TopNQueryBuilder queryBuilderA = new TopNQueryBuilder().dataSource("blah").granularity(Granularities.ALL).dimension("dimUniform").metric(new DimensionTopNMetricSpec(null, StringComparators.ALPHANUMERIC)).intervals(intervalSpec).aggregators(queryAggs);
        basicQueries.put("alphanumericSort", queryBuilderA);
    }
    SCHEMA_QUERY_MAP.put("basic", basicQueries);
}

Example 19 with DoubleMinAggregatorFactory

use of io.druid.query.aggregation.DoubleMinAggregatorFactory in project druid by druid-io.

the class SchemalessTestFullTest method testFullOnTimeseries.

private void testFullOnTimeseries(QueryRunner runner, List<Result<TimeseriesResultValue>> expectedResults, String failMsg) {
    TimeseriesQuery query = Druids.newTimeseriesQueryBuilder().dataSource(dataSource).granularity(allGran).intervals(fullOnInterval).aggregators(Lists.<AggregatorFactory>newArrayList(Iterables.concat(commonAggregators, Lists.newArrayList(new DoubleMaxAggregatorFactory("maxIndex", "index"), new DoubleMinAggregatorFactory("minIndex", "index"))))).postAggregators(Arrays.<PostAggregator>asList(addRowsIndexConstant)).build();
    failMsg += " timeseries ";
    HashMap<String, Object> context = new HashMap<>();
    Iterable<Result<TimeseriesResultValue>> actualResults = Sequences.toList(runner.run(query, context), Lists.<Result<TimeseriesResultValue>>newArrayList());
    TestHelper.assertExpectedResults(expectedResults, actualResults, failMsg);
}

Example 20 with DoubleMinAggregatorFactory

use of io.druid.query.aggregation.DoubleMinAggregatorFactory in project druid by druid-io.

the class SchemalessTestFullTest method testFilteredTimeseries.

private void testFilteredTimeseries(QueryRunner runner, List<Result<TimeseriesResultValue>> expectedResults, String failMsg) {
    TimeseriesQuery query = Druids.newTimeseriesQueryBuilder().dataSource(dataSource).granularity(allGran).intervals(fullOnInterval).filters(marketDimension, "spot").aggregators(Lists.<AggregatorFactory>newArrayList(Iterables.concat(commonAggregators, Lists.newArrayList(new DoubleMaxAggregatorFactory("maxIndex", "index"), new DoubleMinAggregatorFactory("minIndex", "index"))))).postAggregators(Arrays.<PostAggregator>asList(addRowsIndexConstant)).build();
    failMsg += " filtered timeseries ";
    HashMap<String, Object> context = new HashMap<>();
    Iterable<Result<TimeseriesResultValue>> actualResults = Sequences.toList(runner.run(query, context), Lists.<Result<TimeseriesResultValue>>newArrayList());
    TestHelper.assertExpectedResults(expectedResults, actualResults, failMsg);
}