use of org.apache.druid.query.filter.InDimFilter in project druid by druid-io.
the class FilteredAggregatorBenchmark method setup.
/**
* Setup everything common for benchmarking both the incremental-index and the queriable-index.
*/
@Setup
public void setup() {
log.info("SETUP CALLED AT " + System.currentTimeMillis());
ComplexMetrics.registerSerde("hyperUnique", new HyperUniquesSerde());
schemaInfo = GeneratorBasicSchemas.SCHEMA_MAP.get(schema);
generator = new DataGenerator(schemaInfo.getColumnSchemas(), RNG_SEED, schemaInfo.getDataInterval(), rowsPerSegment);
filter = new OrDimFilter(Arrays.asList(new BoundDimFilter("dimSequential", "-1", "-1", true, true, null, null, StringComparators.ALPHANUMERIC), new RegexDimFilter("dimSequential", "X", null), new SearchQueryDimFilter("dimSequential", new ContainsSearchQuerySpec("X", false), null), new InDimFilter("dimSequential", Collections.singletonList("X"), null)));
filteredMetric = new FilteredAggregatorFactory(new CountAggregatorFactory("rows"), filter);
factory = new TimeseriesQueryRunnerFactory(new TimeseriesQueryQueryToolChest(), new TimeseriesQueryEngine(), QueryBenchmarkUtil.NOOP_QUERYWATCHER);
GeneratorSchemaInfo basicSchema = GeneratorBasicSchemas.SCHEMA_MAP.get("basic");
QuerySegmentSpec intervalSpec = new MultipleIntervalSegmentSpec(Collections.singletonList(basicSchema.getDataInterval()));
List<AggregatorFactory> queryAggs = Collections.singletonList(filteredMetric);
query = Druids.newTimeseriesQueryBuilder().dataSource("blah").granularity(Granularities.ALL).intervals(intervalSpec).aggregators(queryAggs).descending(descending).build();
}
use of org.apache.druid.query.filter.InDimFilter in project druid by druid-io.
the class IncrementalIndexReadBenchmark method readWithFilters.
@Benchmark
@BenchmarkMode(Mode.AverageTime)
@OutputTimeUnit(TimeUnit.MICROSECONDS)
public void readWithFilters(Blackhole blackhole) {
DimFilter filter = new OrDimFilter(Arrays.asList(new BoundDimFilter("dimSequential", "-1", "-1", true, true, null, null, StringComparators.ALPHANUMERIC), new JavaScriptDimFilter("dimSequential", "function(x) { return false }", null, JavaScriptConfig.getEnabledInstance()), new RegexDimFilter("dimSequential", "X", null), new SearchQueryDimFilter("dimSequential", new ContainsSearchQuerySpec("X", false), null), new InDimFilter("dimSequential", Collections.singletonList("X"), null)));
IncrementalIndexStorageAdapter sa = new IncrementalIndexStorageAdapter(incIndex);
Sequence<Cursor> cursors = makeCursors(sa, filter);
Cursor cursor = cursors.limit(1).toList().get(0);
List<DimensionSelector> selectors = new ArrayList<>();
selectors.add(makeDimensionSelector(cursor, "dimSequential"));
selectors.add(makeDimensionSelector(cursor, "dimZipf"));
selectors.add(makeDimensionSelector(cursor, "dimUniform"));
selectors.add(makeDimensionSelector(cursor, "dimSequentialHalfNull"));
cursor.reset();
while (!cursor.isDone()) {
for (DimensionSelector selector : selectors) {
IndexedInts row = selector.getRow();
blackhole.consume(selector.lookupName(row.get(0)));
}
cursor.advance();
}
}
use of org.apache.druid.query.filter.InDimFilter in project druid by druid-io.
the class SearchBenchmark method basicC.
private static SearchQueryBuilder basicC(final GeneratorSchemaInfo basicSchema) {
final QuerySegmentSpec intervalSpec = new MultipleIntervalSegmentSpec(Collections.singletonList(basicSchema.getDataInterval()));
final List<String> dimUniformFilterVals = new ArrayList<>();
final int resultNum = (int) (100000 * 0.1);
final int step = 100000 / resultNum;
for (int i = 1; i < 100001 && dimUniformFilterVals.size() < resultNum; i += step) {
dimUniformFilterVals.add(String.valueOf(i));
}
final String dimName = "dimUniform";
final List<DimFilter> dimFilters = new ArrayList<>();
dimFilters.add(new InDimFilter(dimName, dimUniformFilterVals, IdentityExtractionFn.getInstance()));
dimFilters.add(new SelectorDimFilter(dimName, "3", StrlenExtractionFn.instance()));
dimFilters.add(new BoundDimFilter(dimName, "100", "10000", true, true, true, new DimExtractionFn() {
@Override
public byte[] getCacheKey() {
return new byte[] { 0xF };
}
@Override
public String apply(String value) {
return String.valueOf(Long.parseLong(value) + 1);
}
@Override
public boolean preservesOrdering() {
return false;
}
@Override
public ExtractionType getExtractionType() {
return ExtractionType.ONE_TO_ONE;
}
}, null));
dimFilters.add(new InDimFilter(dimName, dimUniformFilterVals, new LowerExtractionFn(null)));
dimFilters.add(new InDimFilter(dimName, dimUniformFilterVals, new UpperExtractionFn(null)));
dimFilters.add(new InDimFilter(dimName, dimUniformFilterVals, new SubstringDimExtractionFn(1, 3)));
return Druids.newSearchQueryBuilder().dataSource("blah").granularity(Granularities.ALL).intervals(intervalSpec).query("").dimensions(Collections.singletonList("dimUniform")).filters(new AndDimFilter(dimFilters));
}
use of org.apache.druid.query.filter.InDimFilter in project druid by druid-io.
the class MultiValuedDimensionTest method testGroupByWithDimFilterEmptyResults.
@Test
public void testGroupByWithDimFilterEmptyResults() {
GroupByQuery query = GroupByQuery.builder().setDataSource("xx").setQuerySegmentSpec(new LegacySegmentSpec("1970/3000")).setGranularity(Granularities.ALL).setDimensions(new DefaultDimensionSpec("tags", "tags")).setAggregatorSpecs(new CountAggregatorFactory("count")).setDimFilter(new InDimFilter("product", ImmutableList.of("product_5"), null)).setContext(context).build();
Sequence<ResultRow> result = helper.runQueryOnSegmentsObjs(ImmutableList.of(new QueryableIndexSegment(queryableIndexNullSampler, SegmentId.dummy("sid1")), new IncrementalIndexSegment(incrementalIndexNullSampler, SegmentId.dummy("sid2"))), query);
List<ResultRow> expectedResults = Collections.singletonList(GroupByQueryRunnerTestHelper.createExpectedRow(query, "1970-01-01T00:00:00.000Z", "tags", null, "count", 2L));
TestHelper.assertExpectedObjects(expectedResults, result.toList(), "filter-empty");
}
use of org.apache.druid.query.filter.InDimFilter in project druid by druid-io.
the class GroupByQueryRunnerTest method testGroupByNestedWithInnerQueryOutputNullNumerics.
@Test
public void testGroupByNestedWithInnerQueryOutputNullNumerics() {
cannotVectorize();
if (config.getDefaultStrategy().equals(GroupByStrategySelector.STRATEGY_V1)) {
expectedException.expect(UnsupportedOperationException.class);
expectedException.expectMessage("GroupBy v1 only supports dimensions with an outputType of STRING.");
}
// Following extractionFn will generate null value for one kind of quality
ExtractionFn extractionFn = new SearchQuerySpecDimExtractionFn(new ContainsSearchQuerySpec("1200", false));
GroupByQuery subquery = makeQueryBuilder().setDataSource(QueryRunnerTestHelper.DATA_SOURCE).setQuerySegmentSpec(QueryRunnerTestHelper.FIRST_TO_THIRD).setDimensions(new DefaultDimensionSpec("quality", "alias"), new ExtractionDimensionSpec("qualityLong", "ql_alias", ColumnType.LONG, extractionFn), new ExtractionDimensionSpec("qualityFloat", "qf_alias", ColumnType.FLOAT, extractionFn), new ExtractionDimensionSpec("qualityDouble", "qd_alias", ColumnType.DOUBLE, extractionFn)).setDimFilter(new InDimFilter("quality", Arrays.asList("entertainment", "business"), null)).setAggregatorSpecs(QueryRunnerTestHelper.ROWS_COUNT, new LongSumAggregatorFactory("idx", "index")).setGranularity(QueryRunnerTestHelper.DAY_GRAN).build();
GroupByQuery outerQuery = makeQueryBuilder().setDataSource(subquery).setQuerySegmentSpec(QueryRunnerTestHelper.FIRST_TO_THIRD).setDimensions(new DefaultDimensionSpec("ql_alias", "quallong", ColumnType.LONG), new DefaultDimensionSpec("qf_alias", "qualfloat", ColumnType.FLOAT), new DefaultDimensionSpec("qd_alias", "qualdouble", ColumnType.DOUBLE)).setAggregatorSpecs(new LongSumAggregatorFactory("ql_alias_sum", "ql_alias"), new DoubleSumAggregatorFactory("qf_alias_sum", "qf_alias"), new DoubleSumAggregatorFactory("qd_alias_sum", "qd_alias")).setGranularity(QueryRunnerTestHelper.ALL_GRAN).build();
List<ResultRow> expectedResults = Arrays.asList(makeRow(outerQuery, "2011-04-01", "quallong", NullHandling.defaultLongValue(), "qualfloat", NullHandling.defaultFloatValue(), "qualdouble", NullHandling.defaultDoubleValue(), "ql_alias_sum", NullHandling.defaultLongValue(), "qf_alias_sum", NullHandling.defaultFloatValue(), "qd_alias_sum", NullHandling.defaultDoubleValue()), makeRow(outerQuery, "2011-04-01", "quallong", 1200L, "qualfloat", 12000.0, "qualdouble", 12000.0, "ql_alias_sum", 2400L, "qf_alias_sum", 24000.0, "qd_alias_sum", 24000.0));
Iterable<ResultRow> results = GroupByQueryRunnerTestHelper.runQuery(factory, runner, outerQuery);
TestHelper.assertExpectedObjects(expectedResults, results, "numerics");
}
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