Examples with DimensionSpec io.druid.query.dimension.DimensionSpec used on opensource projects

Example 1 with DimensionSpec

use of io.druid.query.dimension.DimensionSpec in project druid by druid-io.

the class ApproximateHistogramGroupByQueryTest method testGroupByWithApproximateHistogramAgg.

@Test
public void testGroupByWithApproximateHistogramAgg() {
    ApproximateHistogramAggregatorFactory aggFactory = new ApproximateHistogramAggregatorFactory("apphisto", "index", 10, 5, Float.NEGATIVE_INFINITY, Float.POSITIVE_INFINITY);
    GroupByQuery query = new GroupByQuery.Builder().setDataSource(QueryRunnerTestHelper.dataSource).setGranularity(QueryRunnerTestHelper.allGran).setDimensions(Arrays.<DimensionSpec>asList(new DefaultDimensionSpec(QueryRunnerTestHelper.marketDimension, "marketalias"))).setInterval(QueryRunnerTestHelper.fullOnInterval).setLimitSpec(new DefaultLimitSpec(Lists.newArrayList(new OrderByColumnSpec("marketalias", OrderByColumnSpec.Direction.DESCENDING)), 1)).setAggregatorSpecs(Lists.newArrayList(QueryRunnerTestHelper.rowsCount, aggFactory)).setPostAggregatorSpecs(Arrays.<PostAggregator>asList(new QuantilePostAggregator("quantile", "apphisto", 0.5f))).build();
    List<Row> expectedResults = Arrays.asList(GroupByQueryRunnerTestHelper.createExpectedRow("1970-01-01T00:00:00.000Z", "marketalias", "upfront", "rows", 186L, "quantile", 880.9881f, "apphisto", new Histogram(new float[] { 214.97299194335938f, 545.9906005859375f, 877.0081787109375f, 1208.0257568359375f, 1539.0433349609375f, 1870.06103515625f }, new double[] { 0.0, 67.53287506103516, 72.22068786621094, 31.984678268432617, 14.261756896972656 })));
    Iterable<Row> results = GroupByQueryRunnerTestHelper.runQuery(factory, runner, query);
    TestHelper.assertExpectedObjects(expectedResults, results, "approx-histo");
}

Example 2 with DimensionSpec

use of io.druid.query.dimension.DimensionSpec in project druid by druid-io.

the class ApproximateHistogramGroupByQueryTest method testGroupByWithSameNameComplexPostAgg.

@Test(expected = IllegalArgumentException.class)
public void testGroupByWithSameNameComplexPostAgg() {
    ApproximateHistogramAggregatorFactory aggFactory = new ApproximateHistogramAggregatorFactory("quantile", "index", 10, 5, Float.NEGATIVE_INFINITY, Float.POSITIVE_INFINITY);
    GroupByQuery query = new GroupByQuery.Builder().setDataSource(QueryRunnerTestHelper.dataSource).setGranularity(QueryRunnerTestHelper.allGran).setDimensions(Arrays.<DimensionSpec>asList(new DefaultDimensionSpec(QueryRunnerTestHelper.marketDimension, "marketalias"))).setInterval(QueryRunnerTestHelper.fullOnInterval).setLimitSpec(new DefaultLimitSpec(Lists.newArrayList(new OrderByColumnSpec("marketalias", OrderByColumnSpec.Direction.DESCENDING)), 1)).setAggregatorSpecs(Lists.newArrayList(QueryRunnerTestHelper.rowsCount, aggFactory)).setPostAggregatorSpecs(Arrays.<PostAggregator>asList(new QuantilePostAggregator("quantile", "quantile", 0.5f))).build();
    List<Row> expectedResults = Arrays.asList(GroupByQueryRunnerTestHelper.createExpectedRow("1970-01-01T00:00:00.000Z", "marketalias", "upfront", "rows", 186L, "quantile", 880.9881f));
    Iterable<Row> results = GroupByQueryRunnerTestHelper.runQuery(factory, runner, query);
    TestHelper.assertExpectedObjects(expectedResults, results, "approx-histo");
}

Example 3 with DimensionSpec

use of io.druid.query.dimension.DimensionSpec in project druid by druid-io.

the class VarianceGroupByQueryTest method testPostAggHavingSpec.

@Test
public void testPostAggHavingSpec() {
    VarianceTestHelper.RowBuilder expect = new VarianceTestHelper.RowBuilder(new String[] { "alias", "rows", "index", "index_var", "index_stddev" });
    List<Row> expectedResults = expect.add("2011-04-01", "automotive", 2L, 269L, 299.0009819048282, 17.29164485827847).add("2011-04-01", "mezzanine", 6L, 4420L, 254083.76447001836, 504.06722217380724).add("2011-04-01", "premium", 6L, 4416L, 252279.2020389339, 502.27403082275106).build();
    GroupByQuery query = GroupByQuery.builder().setDataSource(VarianceTestHelper.dataSource).setInterval("2011-04-02/2011-04-04").setDimensions(Lists.<DimensionSpec>newArrayList(new DefaultDimensionSpec("quality", "alias"))).setAggregatorSpecs(Arrays.asList(VarianceTestHelper.rowsCount, VarianceTestHelper.indexLongSum, VarianceTestHelper.indexVarianceAggr)).setPostAggregatorSpecs(ImmutableList.<PostAggregator>of(VarianceTestHelper.stddevOfIndexPostAggr)).setGranularity(new PeriodGranularity(new Period("P1M"), null, null)).setHavingSpec(new OrHavingSpec(ImmutableList.<HavingSpec>of(// 3 rows
    new GreaterThanHavingSpec(VarianceTestHelper.stddevOfIndexMetric, 15L)))).build();
    Iterable<Row> results = GroupByQueryRunnerTestHelper.runQuery(factory, runner, query);
    TestHelper.assertExpectedObjects(expectedResults, results, "");
    query = query.withLimitSpec(new DefaultLimitSpec(Arrays.<OrderByColumnSpec>asList(OrderByColumnSpec.asc(VarianceTestHelper.stddevOfIndexMetric)), 2));
    expectedResults = expect.add("2011-04-01", "automotive", 2L, 269L, 299.0009819048282, 17.29164485827847).add("2011-04-01", "premium", 6L, 4416L, 252279.2020389339, 502.27403082275106).build();
    results = GroupByQueryRunnerTestHelper.runQuery(factory, runner, query);
    TestHelper.assertExpectedObjects(expectedResults, results, "");
}

Example 4 with DimensionSpec

use of io.druid.query.dimension.DimensionSpec in project druid by druid-io.

the class RowBasedGrouperHelper method makeValueConvertFunctions.

@SuppressWarnings("unchecked")
private static Function<Comparable, Comparable>[] makeValueConvertFunctions(final Map<String, ValueType> rawInputRowSignature, final List<DimensionSpec> dimensions) {
    final List<ValueType> valueTypes = Lists.newArrayListWithCapacity(dimensions.size());
    for (DimensionSpec dimensionSpec : dimensions) {
        final ValueType valueType = rawInputRowSignature.get(dimensionSpec);
        valueTypes.add(valueType == null ? ValueType.STRING : valueType);
    }
    return makeValueConvertFunctions(valueTypes);
}

Example 5 with DimensionSpec

use of io.druid.query.dimension.DimensionSpec in project druid by druid-io.

the class GroupByQueryHelper method createIndexAccumulatorPair.

public static <T> Pair<IncrementalIndex, Accumulator<IncrementalIndex, T>> createIndexAccumulatorPair(final GroupByQuery query, final GroupByQueryConfig config, StupidPool<ByteBuffer> bufferPool, final boolean combine) {
    final GroupByQueryConfig querySpecificConfig = config.withOverrides(query);
    final Granularity gran = query.getGranularity();
    final long timeStart = query.getIntervals().get(0).getStartMillis();
    long granTimeStart = timeStart;
    if (!(Granularities.ALL.equals(gran))) {
        granTimeStart = gran.bucketStart(new DateTime(timeStart)).getMillis();
    }
    final List<AggregatorFactory> aggs;
    if (combine) {
        aggs = Lists.transform(query.getAggregatorSpecs(), new Function<AggregatorFactory, AggregatorFactory>() {

            @Override
            public AggregatorFactory apply(AggregatorFactory input) {
                return input.getCombiningFactory();
            }
        });
    } else {
        aggs = query.getAggregatorSpecs();
    }
    final List<String> dimensions = Lists.transform(query.getDimensions(), new Function<DimensionSpec, String>() {

        @Override
        public String apply(DimensionSpec input) {
            return input.getOutputName();
        }
    });
    final IncrementalIndex index;
    final boolean sortResults = query.getContextValue(CTX_KEY_SORT_RESULTS, true);
    // All groupBy dimensions are strings, for now.
    final List<DimensionSchema> dimensionSchemas = Lists.newArrayList();
    for (DimensionSpec dimension : query.getDimensions()) {
        dimensionSchemas.add(new StringDimensionSchema(dimension.getOutputName()));
    }
    final IncrementalIndexSchema indexSchema = new IncrementalIndexSchema.Builder().withDimensionsSpec(new DimensionsSpec(dimensionSchemas, null, null)).withMetrics(aggs.toArray(new AggregatorFactory[aggs.size()])).withQueryGranularity(gran).withMinTimestamp(granTimeStart).build();
    if (query.getContextValue("useOffheap", false)) {
        index = new OffheapIncrementalIndex(indexSchema, false, true, sortResults, querySpecificConfig.getMaxResults(), bufferPool);
    } else {
        index = new OnheapIncrementalIndex(indexSchema, false, true, sortResults, querySpecificConfig.getMaxResults());
    }
    Accumulator<IncrementalIndex, T> accumulator = new Accumulator<IncrementalIndex, T>() {

        @Override
        public IncrementalIndex accumulate(IncrementalIndex accumulated, T in) {
            if (in instanceof MapBasedRow) {
                try {
                    MapBasedRow row = (MapBasedRow) in;
                    accumulated.add(new MapBasedInputRow(row.getTimestamp(), dimensions, row.getEvent()));
                } catch (IndexSizeExceededException e) {
                    throw new ResourceLimitExceededException(e.getMessage());
                }
            } else {
                throw new ISE("Unable to accumulate something of type [%s]", in.getClass());
            }
            return accumulated;
        }
    };
    return new Pair<>(index, accumulator);
}