use of org.apache.druid.segment.IncrementalIndexSegment in project druid by druid-io.
the class IncrementalIndexTest method testSingleThreadedIndexingAndQuery.
@Test
public void testSingleThreadedIndexingAndQuery() throws Exception {
final int dimensionCount = 5;
final ArrayList<AggregatorFactory> ingestAggregatorFactories = new ArrayList<>();
ingestAggregatorFactories.add(new CountAggregatorFactory("rows"));
for (int i = 0; i < dimensionCount; ++i) {
ingestAggregatorFactories.add(new LongSumAggregatorFactory(StringUtils.format("sumResult%s", i), StringUtils.format("Dim_%s", i)));
ingestAggregatorFactories.add(new DoubleSumAggregatorFactory(StringUtils.format("doubleSumResult%s", i), StringUtils.format("Dim_%s", i)));
}
final IncrementalIndex index = indexCreator.createIndex((Object) ingestAggregatorFactories.toArray(new AggregatorFactory[0]));
final long timestamp = System.currentTimeMillis();
final int rows = 50;
// ingesting same data twice to have some merging happening
for (int i = 0; i < rows; i++) {
index.add(getLongRow(timestamp + i, dimensionCount));
}
for (int i = 0; i < rows; i++) {
index.add(getLongRow(timestamp + i, dimensionCount));
}
// run a timeseries query on the index and verify results
final ArrayList<AggregatorFactory> queryAggregatorFactories = new ArrayList<>();
queryAggregatorFactories.add(new CountAggregatorFactory("rows"));
for (int i = 0; i < dimensionCount; ++i) {
queryAggregatorFactories.add(new LongSumAggregatorFactory(StringUtils.format("sumResult%s", i), StringUtils.format("sumResult%s", i)));
queryAggregatorFactories.add(new DoubleSumAggregatorFactory(StringUtils.format("doubleSumResult%s", i), StringUtils.format("doubleSumResult%s", i)));
}
TimeseriesQuery query = Druids.newTimeseriesQueryBuilder().dataSource("xxx").granularity(Granularities.ALL).intervals(ImmutableList.of(Intervals.of("2000/2030"))).aggregators(queryAggregatorFactories).build();
final Segment incrementalIndexSegment = new IncrementalIndexSegment(index, null);
final QueryRunnerFactory factory = new TimeseriesQueryRunnerFactory(new TimeseriesQueryQueryToolChest(), new TimeseriesQueryEngine(), QueryRunnerTestHelper.NOOP_QUERYWATCHER);
final QueryRunner<Result<TimeseriesResultValue>> runner = new FinalizeResultsQueryRunner<Result<TimeseriesResultValue>>(factory.createRunner(incrementalIndexSegment), factory.getToolchest());
List<Result<TimeseriesResultValue>> results = runner.run(QueryPlus.wrap(query)).toList();
Result<TimeseriesResultValue> result = Iterables.getOnlyElement(results);
boolean isRollup = index.isRollup();
Assert.assertEquals(rows * (isRollup ? 1 : 2), result.getValue().getLongMetric("rows").intValue());
for (int i = 0; i < dimensionCount; ++i) {
Assert.assertEquals("Failed long sum on dimension " + i, 2 * rows, result.getValue().getLongMetric("sumResult" + i).intValue());
Assert.assertEquals("Failed double sum on dimension " + i, 2 * rows, result.getValue().getDoubleMetric("doubleSumResult" + i).intValue());
}
}
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