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

Example 41 with DoubleMaxAggregatorFactory

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

the class ApproximateHistogramTopNQueryTest method testTopNWithApproximateHistogramAgg.

@Test
public void testTopNWithApproximateHistogramAgg() {
    ApproximateHistogramAggregatorFactory factory = new ApproximateHistogramAggregatorFactory("apphisto", "index", 10, 5, Float.NEGATIVE_INFINITY, Float.POSITIVE_INFINITY);
    TopNQuery query = new TopNQueryBuilder().dataSource(QueryRunnerTestHelper.dataSource).granularity(QueryRunnerTestHelper.allGran).dimension(QueryRunnerTestHelper.marketDimension).metric(QueryRunnerTestHelper.dependentPostAggMetric).threshold(4).intervals(QueryRunnerTestHelper.fullOnInterval).aggregators(Lists.<AggregatorFactory>newArrayList(Iterables.concat(QueryRunnerTestHelper.commonAggregators, Lists.newArrayList(new DoubleMaxAggregatorFactory("maxIndex", "index"), new DoubleMinAggregatorFactory("minIndex", "index"), factory)))).postAggregators(Arrays.<PostAggregator>asList(QueryRunnerTestHelper.addRowsIndexConstant, QueryRunnerTestHelper.dependentPostAgg, new QuantilePostAggregator("quantile", "apphisto", 0.5f))).build();
    List<Result<TopNResultValue>> expectedResults = Arrays.asList(new Result<TopNResultValue>(new DateTime("2011-01-12T00:00:00.000Z"), new TopNResultValue(Arrays.<Map<String, Object>>asList(ImmutableMap.<String, Object>builder().put(QueryRunnerTestHelper.marketDimension, "total_market").put("rows", 186L).put("index", 215679.82879638672D).put("addRowsIndexConstant", 215866.82879638672D).put(QueryRunnerTestHelper.dependentPostAggMetric, 216053.82879638672D).put("uniques", QueryRunnerTestHelper.UNIQUES_2).put("maxIndex", 1743.9217529296875D).put("minIndex", 792.3260498046875D).put("quantile", 1085.6775f).put("apphisto", new Histogram(new float[] { 554.4271240234375f, 792.3260498046875f, 1030.2249755859375f, 1268.1239013671875f, 1506.0228271484375f, 1743.9217529296875f }, new double[] { 0.0D, 39.42073059082031D, 103.29110717773438D, 34.93659591674805D, 8.351564407348633D })).build(), ImmutableMap.<String, Object>builder().put(QueryRunnerTestHelper.marketDimension, "upfront").put("rows", 186L).put("index", 192046.1060180664D).put("addRowsIndexConstant", 192233.1060180664D).put(QueryRunnerTestHelper.dependentPostAggMetric, 192420.1060180664D).put("uniques", QueryRunnerTestHelper.UNIQUES_2).put("maxIndex", 1870.06103515625D).put("minIndex", 545.9906005859375D).put("quantile", 880.9881f).put("apphisto", new Histogram(new float[] { 214.97299194335938f, 545.9906005859375f, 877.0081787109375f, 1208.0257568359375f, 1539.0433349609375f, 1870.06103515625f }, new double[] { 0.0D, 67.53287506103516D, 72.22068786621094D, 31.984678268432617D, 14.261756896972656D })).build(), ImmutableMap.<String, Object>builder().put(QueryRunnerTestHelper.marketDimension, "spot").put("rows", 837L).put("index", 95606.57232284546D).put("addRowsIndexConstant", 96444.57232284546D).put(QueryRunnerTestHelper.dependentPostAggMetric, 97282.57232284546D).put("uniques", QueryRunnerTestHelper.UNIQUES_9).put("maxIndex", 277.2735290527344D).put("minIndex", 59.02102279663086D).put("quantile", 101.78856f).put("apphisto", new Histogram(new float[] { 4.457897186279297f, 59.02102279663086f, 113.58415222167969f, 168.14727783203125f, 222.7104034423828f, 277.2735290527344f }, new double[] { 0.0D, 462.4309997558594D, 357.5404968261719D, 15.022850036621094D, 2.0056631565093994D })).build()))));
    HashMap<String, Object> context = new HashMap<String, Object>();
    TestHelper.assertExpectedResults(expectedResults, runner.run(query, context));
}