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

Example 16 with DoubleMinAggregatorFactory

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

the class MaterializedViewQueryTest method testQuerySerialization.

@Test
public void testQuerySerialization() throws IOException {
    TopNQuery topNQuery = new TopNQueryBuilder().dataSource(QueryRunnerTestHelper.DATA_SOURCE).granularity(QueryRunnerTestHelper.ALL_GRAN).dimension(QueryRunnerTestHelper.MARKET_DIMENSION).metric(QueryRunnerTestHelper.INDEX_METRIC).threshold(4).intervals(QueryRunnerTestHelper.FULL_ON_INTERVAL_SPEC).aggregators(Lists.newArrayList(Iterables.concat(QueryRunnerTestHelper.COMMON_DOUBLE_AGGREGATORS, Lists.newArrayList(new DoubleMaxAggregatorFactory("maxIndex", "index"), new DoubleMinAggregatorFactory("minIndex", "index"))))).postAggregators(QueryRunnerTestHelper.ADD_ROWS_INDEX_CONSTANT).build();
    MaterializedViewQuery query = new MaterializedViewQuery(topNQuery, optimizer);
    String json = JSON_MAPPER.writeValueAsString(query);
    Query serdeQuery = JSON_MAPPER.readValue(json, Query.class);
    Assert.assertEquals(query, serdeQuery);
    Assert.assertEquals(new TableDataSource(QueryRunnerTestHelper.DATA_SOURCE), query.getDataSource());
    Assert.assertEquals(QueryRunnerTestHelper.ALL_GRAN, query.getGranularity());
    Assert.assertEquals(QueryRunnerTestHelper.FULL_ON_INTERVAL_SPEC.getIntervals(), query.getIntervals());
}

Example 17 with DoubleMinAggregatorFactory

use of org.apache.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<>();
    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"));
        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(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);
}

Example 18 with DoubleMinAggregatorFactory

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

the class GroupByBenchmark method setupQueries.

private void setupQueries() {
    // queries for the basic schema
    Map<String, GroupByQuery> 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 CountAggregatorFactory("cnt"));
        queryAggs.add(new LongSumAggregatorFactory("sumLongSequential", "sumLongSequential"));
        GroupByQuery queryA = GroupByQuery.builder().setDataSource("blah").setQuerySegmentSpec(intervalSpec).setDimensions(new DefaultDimensionSpec("dimSequential", null), new DefaultDimensionSpec("dimZipf", null)).setAggregatorSpecs(queryAggs).setGranularity(Granularity.fromString(queryGranularity)).setContext(ImmutableMap.of("vectorize", vectorize)).build();
        basicQueries.put("A", queryA);
    }
    {
        // basic.sorted
        QuerySegmentSpec intervalSpec = new MultipleIntervalSegmentSpec(Collections.singletonList(basicSchema.getDataInterval()));
        List<AggregatorFactory> queryAggs = new ArrayList<>();
        queryAggs.add(new LongSumAggregatorFactory("sumLongSequential", "sumLongSequential"));
        GroupByQuery queryA = GroupByQuery.builder().setDataSource("blah").setQuerySegmentSpec(intervalSpec).setDimensions(new DefaultDimensionSpec("dimSequential", null), new DefaultDimensionSpec("dimZipf", null)).setAggregatorSpecs(queryAggs).setGranularity(Granularity.fromString(queryGranularity)).setLimitSpec(new DefaultLimitSpec(Collections.singletonList(new OrderByColumnSpec("sumLongSequential", OrderByColumnSpec.Direction.DESCENDING, StringComparators.NUMERIC)), 100)).build();
        basicQueries.put("sorted", queryA);
    }
    {
        // basic.nested
        QuerySegmentSpec intervalSpec = new MultipleIntervalSegmentSpec(Collections.singletonList(basicSchema.getDataInterval()));
        List<AggregatorFactory> queryAggs = new ArrayList<>();
        queryAggs.add(new LongSumAggregatorFactory("sumLongSequential", "sumLongSequential"));
        GroupByQuery subqueryA = GroupByQuery.builder().setDataSource("blah").setQuerySegmentSpec(intervalSpec).setDimensions(new DefaultDimensionSpec("dimSequential", null), new DefaultDimensionSpec("dimZipf", null)).setAggregatorSpecs(queryAggs).setGranularity(Granularities.DAY).setContext(ImmutableMap.of("vectorize", vectorize)).build();
        GroupByQuery queryA = GroupByQuery.builder().setDataSource(subqueryA).setQuerySegmentSpec(intervalSpec).setDimensions(new DefaultDimensionSpec("dimSequential", null)).setAggregatorSpecs(queryAggs).setGranularity(Granularities.WEEK).setContext(ImmutableMap.of("vectorize", vectorize)).build();
        basicQueries.put("nested", queryA);
    }
    {
        // basic.filter
        final QuerySegmentSpec intervalSpec = new MultipleIntervalSegmentSpec(Collections.singletonList(basicSchema.getDataInterval()));
        // Use multiple aggregators to see how the number of aggregators impact to the query performance
        List<AggregatorFactory> queryAggs = ImmutableList.of(new LongSumAggregatorFactory("sumLongSequential", "sumLongSequential"), new LongSumAggregatorFactory("rows", "rows"), new DoubleSumAggregatorFactory("sumFloatNormal", "sumFloatNormal"), new DoubleMinAggregatorFactory("minFloatZipf", "minFloatZipf"));
        GroupByQuery queryA = GroupByQuery.builder().setDataSource("blah").setQuerySegmentSpec(intervalSpec).setDimensions(new DefaultDimensionSpec("dimUniform", null)).setAggregatorSpecs(queryAggs).setGranularity(Granularity.fromString(queryGranularity)).setDimFilter(new BoundDimFilter("dimUniform", "0", "100", true, true, null, null, null)).setContext(ImmutableMap.of("vectorize", vectorize)).build();
        basicQueries.put("filter", queryA);
    }
    {
        // basic.singleZipf
        final QuerySegmentSpec intervalSpec = new MultipleIntervalSegmentSpec(Collections.singletonList(basicSchema.getDataInterval()));
        // Use multiple aggregators to see how the number of aggregators impact to the query performance
        List<AggregatorFactory> queryAggs = ImmutableList.of(new LongSumAggregatorFactory("sumLongSequential", "sumLongSequential"), new LongSumAggregatorFactory("rows", "rows"), new DoubleSumAggregatorFactory("sumFloatNormal", "sumFloatNormal"), new DoubleMinAggregatorFactory("minFloatZipf", "minFloatZipf"));
        GroupByQuery queryA = GroupByQuery.builder().setDataSource("blah").setQuerySegmentSpec(intervalSpec).setDimensions(new DefaultDimensionSpec("dimZipf", null)).setAggregatorSpecs(queryAggs).setGranularity(Granularity.fromString(queryGranularity)).setContext(ImmutableMap.of("vectorize", vectorize)).build();
        basicQueries.put("singleZipf", queryA);
    }
    SCHEMA_QUERY_MAP.put("basic", basicQueries);
    // simple one column schema, for testing performance difference between querying on numeric values as Strings and
    // directly as longs
    Map<String, GroupByQuery> simpleQueries = new LinkedHashMap<>();
    GeneratorSchemaInfo simpleSchema = GeneratorBasicSchemas.SCHEMA_MAP.get("simple");
    {
        // simple.A
        QuerySegmentSpec intervalSpec = new MultipleIntervalSegmentSpec(Collections.singletonList(simpleSchema.getDataInterval()));
        List<AggregatorFactory> queryAggs = new ArrayList<>();
        queryAggs.add(new LongSumAggregatorFactory("rows", "rows"));
        GroupByQuery queryA = GroupByQuery.builder().setDataSource("blah").setQuerySegmentSpec(intervalSpec).setDimensions(new DefaultDimensionSpec("dimSequential", "dimSequential", ColumnType.STRING)).setAggregatorSpecs(queryAggs).setGranularity(Granularity.fromString(queryGranularity)).setContext(ImmutableMap.of("vectorize", vectorize)).build();
        simpleQueries.put("A", queryA);
    }
    SCHEMA_QUERY_MAP.put("simple", simpleQueries);
    Map<String, GroupByQuery> simpleLongQueries = new LinkedHashMap<>();
    GeneratorSchemaInfo simpleLongSchema = GeneratorBasicSchemas.SCHEMA_MAP.get("simpleLong");
    {
        // simpleLong.A
        QuerySegmentSpec intervalSpec = new MultipleIntervalSegmentSpec(Collections.singletonList(simpleLongSchema.getDataInterval()));
        List<AggregatorFactory> queryAggs = new ArrayList<>();
        queryAggs.add(new LongSumAggregatorFactory("rows", "rows"));
        GroupByQuery queryA = GroupByQuery.builder().setDataSource("blah").setQuerySegmentSpec(intervalSpec).setDimensions(new DefaultDimensionSpec("dimSequential", "dimSequential", ColumnType.LONG)).setAggregatorSpecs(queryAggs).setGranularity(Granularity.fromString(queryGranularity)).setContext(ImmutableMap.of("vectorize", vectorize)).build();
        simpleLongQueries.put("A", queryA);
    }
    SCHEMA_QUERY_MAP.put("simpleLong", simpleLongQueries);
    Map<String, GroupByQuery> simpleFloatQueries = new LinkedHashMap<>();
    GeneratorSchemaInfo simpleFloatSchema = GeneratorBasicSchemas.SCHEMA_MAP.get("simpleFloat");
    {
        // simpleFloat.A
        QuerySegmentSpec intervalSpec = new MultipleIntervalSegmentSpec(Collections.singletonList(simpleFloatSchema.getDataInterval()));
        List<AggregatorFactory> queryAggs = new ArrayList<>();
        queryAggs.add(new LongSumAggregatorFactory("rows", "rows"));
        GroupByQuery queryA = GroupByQuery.builder().setDataSource("blah").setQuerySegmentSpec(intervalSpec).setDimensions(new DefaultDimensionSpec("dimSequential", "dimSequential", ColumnType.FLOAT)).setAggregatorSpecs(queryAggs).setGranularity(Granularity.fromString(queryGranularity)).setContext(ImmutableMap.of("vectorize", vectorize)).build();
        simpleFloatQueries.put("A", queryA);
    }
    SCHEMA_QUERY_MAP.put("simpleFloat", simpleFloatQueries);
    // simple one column schema, for testing performance difference between querying on numeric values as Strings and
    // directly as longs
    Map<String, GroupByQuery> nullQueries = new LinkedHashMap<>();
    GeneratorSchemaInfo nullSchema = GeneratorBasicSchemas.SCHEMA_MAP.get("nulls");
    {
        // simple-null
        QuerySegmentSpec intervalSpec = new MultipleIntervalSegmentSpec(Collections.singletonList(nullSchema.getDataInterval()));
        List<AggregatorFactory> queryAggs = new ArrayList<>();
        queryAggs.add(new DoubleSumAggregatorFactory("doubleSum", "doubleZipf"));
        GroupByQuery queryA = GroupByQuery.builder().setDataSource("blah").setQuerySegmentSpec(intervalSpec).setDimensions(new DefaultDimensionSpec("stringZipf", "stringZipf", ColumnType.STRING)).setAggregatorSpecs(queryAggs).setGranularity(Granularity.fromString(queryGranularity)).setContext(ImmutableMap.of("vectorize", vectorize)).build();
        nullQueries.put("A", queryA);
    }
    SCHEMA_QUERY_MAP.put("nulls", nullQueries);
}

Example 19 with DoubleMinAggregatorFactory

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

the class VarianceTopNQueryTest method testFullOnTopNOverUniques.

@Test
public void testFullOnTopNOverUniques() {
    TopNQuery query = new TopNQueryBuilder().dataSource(QueryRunnerTestHelper.DATA_SOURCE).granularity(QueryRunnerTestHelper.ALL_GRAN).dimension(QueryRunnerTestHelper.MARKET_DIMENSION).metric(QueryRunnerTestHelper.UNIQUE_METRIC).threshold(3).intervals(QueryRunnerTestHelper.FULL_ON_INTERVAL_SPEC).aggregators(Lists.newArrayList(Iterables.concat(VarianceTestHelper.COMMON_PLUS_VAR_AGGREGATORS, Lists.newArrayList(new DoubleMaxAggregatorFactory("maxIndex", "index"), new DoubleMinAggregatorFactory("minIndex", "index"))))).postAggregators(QueryRunnerTestHelper.ADD_ROWS_INDEX_CONSTANT).build();
    List<Result<TopNResultValue>> expectedResults = Collections.singletonList(new Result<>(DateTimes.of("2011-01-12T00:00:00.000Z"), new TopNResultValue(Arrays.<Map<String, Object>>asList(ImmutableMap.<String, Object>builder().put("market", "spot").put("rows", 837L).put("index", 95606.57232284546D).put("addRowsIndexConstant", 96444.57232284546D).put("uniques", QueryRunnerTestHelper.UNIQUES_9).put("maxIndex", 277.2735290527344D).put("minIndex", 59.02102279663086D).put("index_var", 439.3851694586573D).build(), ImmutableMap.<String, Object>builder().put("market", "total_market").put("rows", 186L).put("index", 215679.82879638672D).put("addRowsIndexConstant", 215866.82879638672D).put("uniques", QueryRunnerTestHelper.UNIQUES_2).put("maxIndex", 1743.9217529296875D).put("minIndex", 792.3260498046875D).put("index_var", 27679.900887366413D).build(), ImmutableMap.<String, Object>builder().put("market", "upfront").put("rows", 186L).put("index", 192046.1060180664D).put("addRowsIndexConstant", 192233.1060180664D).put("uniques", QueryRunnerTestHelper.UNIQUES_2).put("maxIndex", 1870.06103515625D).put("minIndex", 545.9906005859375D).put("index_var", 79699.9780741607D).build()))));
    assertExpectedResults(expectedResults, query);
}

Example 20 with DoubleMinAggregatorFactory

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

the class TopNQueryRunnerTest method testTopNWithExtractionFilterAndFilteredAggregatorCaseNoExistingValue.

@Test
public void testTopNWithExtractionFilterAndFilteredAggregatorCaseNoExistingValue() {
    Map<String, String> extractionMap = new HashMap<>();
    MapLookupExtractor mapLookupExtractor = new MapLookupExtractor(extractionMap, false);
    LookupExtractionFn lookupExtractionFn;
    if (NullHandling.replaceWithDefault()) {
        lookupExtractionFn = new LookupExtractionFn(mapLookupExtractor, false, null, true, false);
        extractionMap.put("", "NULL");
    } else {
        lookupExtractionFn = new LookupExtractionFn(mapLookupExtractor, false, "NULL", true, false);
    }
    DimFilter extractionFilter = new ExtractionDimFilter("null_column", "NULL", lookupExtractionFn, null);
    TopNQueryBuilder topNQueryBuilder = new TopNQueryBuilder().dataSource(QueryRunnerTestHelper.DATA_SOURCE).granularity(QueryRunnerTestHelper.ALL_GRAN).dimension("null_column").metric(QueryRunnerTestHelper.INDEX_METRIC).threshold(4).intervals(QueryRunnerTestHelper.FULL_ON_INTERVAL_SPEC).aggregators(Lists.newArrayList(Iterables.concat(commonAggregators, Lists.newArrayList(new FilteredAggregatorFactory(new DoubleMaxAggregatorFactory("maxIndex", "index"), extractionFilter), new DoubleMinAggregatorFactory("minIndex", "index"))))).postAggregators(QueryRunnerTestHelper.ADD_ROWS_INDEX_CONSTANT);
    TopNQuery topNQueryWithNULLValueExtraction = topNQueryBuilder.filters(extractionFilter).build();
    Map<String, Object> map = new HashMap<>();
    map.put("null_column", null);
    map.put("rows", 1209L);
    map.put("index", 503332.5071372986D);
    map.put("addRowsIndexConstant", 504542.5071372986D);
    map.put("uniques", QueryRunnerTestHelper.UNIQUES_9);
    map.put("maxIndex", 1870.061029D);
    map.put("minIndex", 59.02102279663086D);
    List<Result<TopNResultValue>> expectedResults = Collections.singletonList(new Result<>(DateTimes.of("2011-01-12T00:00:00.000Z"), new TopNResultValue(Collections.singletonList(map))));
    assertExpectedResults(expectedResults, topNQueryWithNULLValueExtraction);
}