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

Example 11 with DoubleMinAggregatorFactory

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

the class SchemalessTestSimpleTest method testFullOnTimeseries.

@Test
public void testFullOnTimeseries() {
    TimeseriesQuery query = Druids.newTimeseriesQueryBuilder().dataSource(dataSource).granularity(ALL_GRAN).intervals(fullOnInterval).aggregators(Lists.newArrayList(Iterables.concat(commonAggregators, Lists.newArrayList(new DoubleMaxAggregatorFactory("maxIndex", "index"), new DoubleMinAggregatorFactory("minIndex", "index"))))).postAggregators(addRowsIndexConstant).build();
    List<Result<TimeseriesResultValue>> expectedResults = Collections.singletonList(new Result(DateTimes.of("2011-01-12T00:00:00.000Z"), new TimeseriesResultValue(ImmutableMap.<String, Object>builder().put("rows", coalesceAbsentAndEmptyDims ? 10L : 11L).put("index", 900.0).put("addRowsIndexConstant", coalesceAbsentAndEmptyDims ? 911.0 : 912.0).put("uniques", 2.000977198748901D).put("maxIndex", 100.0).put("minIndex", NullHandling.replaceWithDefault() ? 0.0 : 100.0).build())));
    QueryRunner runner = TestQueryRunners.makeTimeSeriesQueryRunner(segment);
    TestHelper.assertExpectedResults(expectedResults, runner.run(QueryPlus.wrap(query)));
}

Example 12 with DoubleMinAggregatorFactory

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

the class SchemalessTestSimpleTest method testFullOnTopN.

// @Test TODO: Handling of null values is inconsistent right now, need to make it all consistent and re-enable test
// TODO: Complain to Eric when you see this.  It shouldn't be like this...
@Ignore
@SuppressWarnings("unused")
public void testFullOnTopN() {
    TopNQuery query = new TopNQueryBuilder().dataSource(dataSource).granularity(ALL_GRAN).dimension(marketDimension).metric(indexMetric).threshold(3).intervals(fullOnInterval).aggregators(Lists.newArrayList(Iterables.concat(commonAggregators, Lists.newArrayList(new DoubleMaxAggregatorFactory("maxIndex", "index"), new DoubleMinAggregatorFactory("minIndex", "index"))))).postAggregators(addRowsIndexConstant).build();
    List<Result<TopNResultValue>> expectedResults = Collections.singletonList(new Result<>(DateTimes.of("2011-01-12T00:00:00.000Z"), new TopNResultValue(Arrays.asList(new DimensionAndMetricValueExtractor(ImmutableMap.<String, Object>builder().put("market", "spot").put("rows", 4L).put("index", 400.0D).put("addRowsIndexConstant", 405.0D).put("uniques", 1.0002442201269182D).put("maxIndex", 100.0).put("minIndex", 100.0).build()), new DimensionAndMetricValueExtractor(ImmutableMap.<String, Object>builder().put("market", "").put("rows", 2L).put("index", 200.0D).put("addRowsIndexConstant", 203.0D).put("uniques", 0.0).put("maxIndex", 100.0D).put("minIndex", 100.0D).build()), new DimensionAndMetricValueExtractor(ImmutableMap.<String, Object>builder().put("market", "total_market").put("rows", 2L).put("index", 200.0D).put("addRowsIndexConstant", 203.0D).put("uniques", 1.0002442201269182D).put("maxIndex", 100.0D).put("minIndex", 100.0D).build())))));
    try (CloseableStupidPool<ByteBuffer> pool = TestQueryRunners.createDefaultNonBlockingPool()) {
        QueryRunner runner = TestQueryRunners.makeTopNQueryRunner(segment, pool);
        TestHelper.assertExpectedResults(expectedResults, runner.run(QueryPlus.wrap(query)));
    }
}

Example 13 with DoubleMinAggregatorFactory

use of org.apache.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(ALL_GRAN).intervals(fullOnInterval).aggregators(Lists.newArrayList(Iterables.concat(commonAggregators, Lists.newArrayList(new DoubleMaxAggregatorFactory("maxIndex", "index"), new DoubleMinAggregatorFactory("minIndex", "index"))))).postAggregators(addRowsIndexConstant).build();
    failMsg += " timeseries ";
    Iterable<Result<TimeseriesResultValue>> actualResults = runner.run(QueryPlus.wrap(query)).toList();
    TestHelper.assertExpectedResults(expectedResults, actualResults, failMsg);
}

Example 14 with DoubleMinAggregatorFactory

use of org.apache.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<>();
    GeneratorSchemaInfo basicSchema = GeneratorBasicSchemas.SCHEMA_MAP.get("basic");
    {
        // basic.A
        QuerySegmentSpec intervalSpec = new MultipleIntervalSegmentSpec(Collections.singletonList(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(descending).build();
        basicQueries.put("A", queryA);
    }
    {
        QuerySegmentSpec intervalSpec = new MultipleIntervalSegmentSpec(Collections.singletonList(basicSchema.getDataInterval()));
        List<AggregatorFactory> queryAggs = new ArrayList<>();
        LongSumAggregatorFactory lsaf = new LongSumAggregatorFactory("sumLongSequential", "sumLongSequential");
        BoundDimFilter timeFilter = new BoundDimFilter(ColumnHolder.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(descending).build();
        basicQueries.put("timeFilterNumeric", timeFilterQuery);
    }
    {
        QuerySegmentSpec intervalSpec = new MultipleIntervalSegmentSpec(Collections.singletonList(basicSchema.getDataInterval()));
        List<AggregatorFactory> queryAggs = new ArrayList<>();
        LongSumAggregatorFactory lsaf = new LongSumAggregatorFactory("sumLongSequential", "sumLongSequential");
        BoundDimFilter timeFilter = new BoundDimFilter(ColumnHolder.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(descending).build();
        basicQueries.put("timeFilterAlphanumeric", timeFilterQuery);
    }
    {
        QuerySegmentSpec intervalSpec = new MultipleIntervalSegmentSpec(Collections.singletonList(Intervals.utc(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(descending).build();
        basicQueries.put("timeFilterByInterval", timeFilterQuery);
    }
    SCHEMA_QUERY_MAP.put("basic", basicQueries);
}

Example 15 with DoubleMinAggregatorFactory

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

the class TopNTypeInterfaceBenchmark method setupQueries.

private void setupQueries() {
    // queries for the basic schema
    Map<String, TopNQueryBuilder> basicQueries = new LinkedHashMap<>();
    GeneratorSchemaInfo basicSchema = GeneratorBasicSchemas.SCHEMA_MAP.get("basic");
    {
        // basic.A
        QuerySegmentSpec intervalSpec = new MultipleIntervalSegmentSpec(Collections.singletonList(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"));
        // Use an IdentityExtractionFn to force usage of HeapBasedTopNAlgorithm
        TopNQueryBuilder queryBuilderString = new TopNQueryBuilder().dataSource("blah").granularity(Granularities.ALL).dimension(new ExtractionDimensionSpec("dimSequential", "dimSequential", IdentityExtractionFn.getInstance())).metric("sumFloatNormal").intervals(intervalSpec).aggregators(queryAggs);
        // HeapBasedTopNAlgorithm is always used for numeric columns
        TopNQueryBuilder queryBuilderLong = new TopNQueryBuilder().dataSource("blah").granularity(Granularities.ALL).dimension("metLongUniform").metric("sumFloatNormal").intervals(intervalSpec).aggregators(queryAggs);
        TopNQueryBuilder queryBuilderFloat = new TopNQueryBuilder().dataSource("blah").granularity(Granularities.ALL).dimension("metFloatNormal").metric("sumFloatNormal").intervals(intervalSpec).aggregators(queryAggs);
        basicQueries.put("string", queryBuilderString);
        basicQueries.put("long", queryBuilderLong);
        basicQueries.put("float", queryBuilderFloat);
    }
    {
        // basic.numericSort
        QuerySegmentSpec intervalSpec = new MultipleIntervalSegmentSpec(Collections.singletonList(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(Collections.singletonList(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);
}